Research of Dispatching Method in Elevator Group Control System Based on Fuzzy Neural Network. Yufeng Dai a, Yun Du b
|
|
- Griselda Barnett
- 5 years ago
- Views:
Transcription
1 2nd Internatonal Conference on Computer Engneerng, Informaton Scence & Applcaton Technology (ICCIA 207) Research of Dspatchng Method n Elevator Group Control System Based on Fuzzy Neural Network Yufeng Da a, Yun Du b School of electrcal engneerng, Hebe Unversty of Scence and Technology, Shjazhuang 0008, Chna a da39387@63.com, b @qq.com Keywords: Elevator group control system, Comprehensve evaluaton functon, Fuzzy neural network, Dspatchng method. Abstract. Elevator group control system (EGCS) s a complex optmzaton system to wth multobjectve, stochastc and nonlnear characterstcs. It s hard to descrbe EGCS wth exact mathematc model and to ncrease the capablty of the system wth tradtonal control method. The fuzzy control technology and neural network technology are combned n ths paper and a dspatchng method appled to varous passenger traffc condtons s proposed. The comprehensve evaluaton functon of traffc sgnal s establshed and the rght heavy of every evaluaton factor (watng tme, rdng tme, energy consume) s studed by the neural network, so the elevator s dspatched optmally. The result of smulaton shows that ths method realzes reasonable elevator dspatchng under varous passenger traffc condtons and ndcates the valdty of ths method.. Introducton Wth the contnuous development and progress of human socety, the number of hgh-rse buldngs has become a symbol of a cty's development and prosperty, and the elevator s an ndspensable part of the hgh-rse buldng, so the elevator technology rapdly developed. Elevator n the control technology gradually developed from a lft to the centralzed control of elevators. Frst of all, through the analyss of buldng passenger flow, the traffc pattern of elevator group s classfed. Fuzzy neural network s used to dentfy the traffc pattern of elevator group. Accordng to the dentfcaton of the system to determne the elevator group s currently n the traffc model. Then, the fuzzy neural network s used to calculate the credblty of the elevator n response to the call sgnal of the elevator, and the elevator wth the hghest relablty s selected to fnally complete the servce [6]. 2. Classfcaton and dentfcaton of traffc patterns 2. The classfcaton of the traffc patterns. Accordng to the dfferent needs of the buldng and the people who work n the buldng are also dfferent, so there are a varety of traffc patterns correspondng to them [2].In ths paper, the hgh-rse offce buldng as the research object, ac-cordng to the fxed tme traffc flow changes, the elevator traffc model s dvded nto 6 categores: up peak traffc pattern, down peak traffc pattern, dle traffc mode, the mddle layer of busy mode, sngle mode and double layer busy mode. 2.2 Fuzzy neural network. After the classfcaton of traffc patterns, we need to dentfy the current traffc pattern of elevator group. In ths paper, fuzzy neural network s used to dentfy. In the fuzzy neural network structure, the number of layers s fxed, whch are nput layer, fuzzy layer, rule layer, ntegrated layer and output layer []. () Input layer: the nput layer s the frst layer of the fuzzy neural network topology, each node n the nput layer represents an nput varable, and the number of neurons s equal to the number of nput varables. Copyrght 207, the Authors. Publshed by Atlants Press. Ths s an open access artcle under the CC BY-NC lcense ( 247
2 (2) Fuzzy level: each nput varable should be defned by ther fuzzy subsets, and the membershp functons of all fuzzy subsets are calculated by ths layer. (3) Rule layer: the node s a rule node, whch represents the logc rules, and each node has the logc operaton functon. (4) Synthess layer: ths layer node performs a fuzzy "or" operaton to synthesze rules wth the same result. () Output layer: Ths layer s also called the ant-fuzzy layer. 2.3 Traffc pattern recognton. The hgh-rse offce buldng as an example, n mnutes as a unt of tme, characterstc values are: unt tme total passenger traffc, passenger flow, passenger flow nto the left, the largest passenger flow, the mddle floor large mddle floor. After normalzaton, the nput varables belong to [0, ]. The fuzzy neural network needs to be traned before pattern recognton, and the recognton can be carred out after the tranng []. Because the tranng nput data need to be normalzed, the nput value can only be n the [0, ], so the nput sample nterval value s 0.2. The structure of fuzzy neural network n traffc pattern recognton s and Accordng to the prevous learnng methods to tran the network, the fuzzy rule extracton threshold s =0.0. Network tranng results s as Table 2.. Table Network tranng results Learnng Error back Error precson Network type Rule base effcency propagaton Frst step Second step It can be seen from the table that the rules are deleted and merged by compettve learnng. Now, the traned fuzzy neural network s used to dentfy the traffc pattern of the offce buldng. The smulaton results are as Fg -4. Fg. Traffc statstcs of the hall Fg.2 The total traffc volume of the offce buldng and ts specal floor traffc characterstcs 248
3 Fg. 3 The proporton of the up peak pattern Fg. 4 The proporton of the downward peak mode Fgure and Fgure 2 s a traffc statstcal feature curve of a workng day n an offce buldng, and the statstcal tme nterval s mnutes. Usng fuzzy neural network to dentfy traffc n Fg and Fg 2, t dentfes the proporton of up peak pattern and down peak pattern as shown n Fg 3 and Fg Elevator group control system ladder algorthm The elevator group dspatch algorthm s a mult-objectve optmzaton. It needs to consder the entre populaton and the average watng tme, average operaton tme of all people n the elevator, the tme of watng and the proporton of the overall energy consumpton of elevator group and other factors. The elevator group control system needs to control multple elevators to respond to the varous callng sgnals at the same tme, so the general mathematcal model cannot be acheved [4]. We wll contnue to use fuzzy neural network to acheve mult-objectve optmzaton. Total passenger flow Passenger flow out of the buldng Maxmum floor passenger flow Second floor passenger flow dle traffc pattern Interlayer traffc patterns When the layer rato s large, the second network s dentfed Second network dentfcaton Total passenger flow Frst network dentfcaton Passenger flow nto the buldng AWT up peak traffc pattern down peak traffc pattern Sngle mddle layer pattern ART The weghts of AWT, ART and RNC are determned accordng to the proporton of each traffc pattern RNC Double mddle layer pattern HCWT Callng sgnal Car nformaton S AWT Collect nformaton, calculate and judge CV maxhcwt GD fuzzy neural network S S ART Weghted average output S RNC Fg. Schematc dagram of elevator group control 249
4 Ths elevator performance of multple ndcators, the most mportance s the passengers average watng tme AWT, the average passenger elevator tme ART and energy consumpton RNC these three ndcators. Objectve functon: () S AWT S AWT ART S ART RNC S RNC Where S s the confdence of the average watng tme of the elevator, S s the confdence of the average rde tme, and S s the confdence of the energy loss. Indcates the relablty of the -th elevator response call. AWT ART RNC s the weghtng factor, and the sum s.the weghtng factor s determned by the pattern of traffc flow dentfed n the prevous chapter. Wth the formula (), the relablty of the n elevators n response to the call sgnal can be obtaned, and then the elevator wth the hghest degree of confdence s selected to respond to the call sgnal. (2) se max( s, s2,..., sn) When a call sgnal generated, the system wll mmedately through the HCWT, maxhcwt, CV and GD these four parameters to calculate the average watng tme for each elevator elevator AWT, the average passenger elevator tme ART and energy consumpton RNC ndcators [3]. The HCWT generates a call sgnal to respond to the elevator's arrval tme and watng tme for the layer. maxhcwt s the maxmum watng tme for all call sgnals that a elevator responds to.cv rep-resents the ablty to respond to future calls. GD represents the shortest dstance between the newly generated call sgnal floor and all sgnal floors that the elevator responds to [7]. The ntra-vector components are the weghts of AWT, ART, and RNC, respectvely. The traffc rato of the up peak traffc pattern, down peak traffc pattern, nterlayer traffc pattern, dle traffc pattern, sngle mddle layer pattern and double mddle layer pattern are A, A2, A3, A4, A, A6 respectvely. Also there A A2 A3 A4 A A6. Then the fnal calculaton of the AWT, ART, RNC weghts are as follows: (3) A A2 2 A3 3 A4 4 A A6 6 The fuzzy neural network model s establshed. The nput varables are HCWT, max HCWT, CV and GD, and the output varables are AWT, ART and RNC. Accordng to dfferent modes of transport, t can adjust the weght of the three confdence, calculate the fnal credblty. By comparng the relablty of the elevator n response to the call sgnal, select the most relable elevator to complete the escalator. AWT ART RNC 4. Elevator group control system smulaton In ths paper, accordng to the actual stuaton of a certan offce buldng statstcs tranng data, s got consderng the tme perod and the mode of traffc flow. The sample data were collected n 0 groups. The data of the 40 groups were tranng data, and the remanng 0 groups of data were test data. The error precson s controlled wthn the preset threshold by repettve learnng tranng, e <0.00. Fgure 6 shows that n the tranng samples, the center and wdth of the membershp functon of the nput vector of the fuzzy neural network by the error back propagaton algorthm s optmzed. If you follow the checklst your paper wll conform to the requrements of the publsher and facltate a problem-free publcaton process. Tranng network error curve error Number of tranng steps Fg. 6 Varaton of network error performance durng tranng 20
5 It can be seen that after 30 teratons, the gradent curve has stablzed, ndcatng that the tranng of the fuzzy neural network has been completed. After the end of the network tranng, use the test sample to test the output error range, as shown n Fgure Test sample error curve x 0 error Test samples Fg. 7 Error result of test sample data It can be seen from Fgure 7 that the errors are wthn the set range, ndcatng that the fuzzy neural network tranng s completed.. Concluson In ths paper, a 20-story buldng elevator group as an example of the smulaton, the buldng has sx elevators, each elevator rated people. AWT, ART and RNC weghts are calculated accordng to the current traffc pattern. The parameters of AWT, ART and RNC are calculated by HCWT, max HCWT, CV and GD. AWT, ART and RNC are calculated accordng to the current traffc pattern., RNC three of the credblty, accordng to the traffc model to calculate the fnal credblty. By comparng the sze of the fnal relablty of the sx elevators, select the most relable elevator to send ladder. In ths paper, the smulaton experment s carred out by usng MATLAB software, and the expermental results are obtaned. How to adjust the weghtng system reasonably and make the algorthm more optmzed. References []. Bao H: Research on Fuzzy Neural Network Based recognton of traffc patterns of Elevator Group Control System and mult-target dspatchng algorthm.[d] Tongj Unversty, Chna [2]. Guo JL: Research on Elevator Group Control System Based on Fuzzy Neural Network. [D]Northeastern Unversty, Chna 203. [3]. Lu XY,He P,Chang JH : Research of Dspatchng Method n Elevator Group Control System Based on Fuzzy Neural Network. Computer Technology and Development. (2008)8(): [4]. L XL: Studes of Elevator Group Control System Based on Fuzzy Neural Network. [D] Soochow Unversty, Chna []. Tang HY: Research on optmal Control of Elevator Group Based on Fuzzy Neural Network. Harbn Insttute of Technology, [D] Chna [6]. Wang QX,Jn X :Research on Elevator Group Control Algorthm based on Fuzzy Neural Network. Chna New Technologes and Products20,9(2):4- [7]. Zhang SQ Applcaton Research of Fuzzy Neural Network n Elevator Group Control system. Northeastern Unversty, [D] Chna
A Preliminary Study on Targets Association Algorithm of Radar and AIS Using BP Neural Network
Avalable onlne at www.scencedrect.com Proceda Engneerng 5 (2 44 445 A Prelmnary Study on Targets Assocaton Algorthm of Radar and AIS Usng BP Neural Networ Hu Xaoru a, Ln Changchuan a a Navgaton Insttute
More informationMTBF PREDICTION REPORT
MTBF PREDICTION REPORT PRODUCT NAME: BLE112-A-V2 Issued date: 01-23-2015 Rev:1.0 Copyrght@2015 Bluegga Technologes. All rghts reserved. 1 MTBF PREDICTION REPORT... 1 PRODUCT NAME: BLE112-A-V2... 1 1.0
More informationHigh Speed, Low Power And Area Efficient Carry-Select Adder
Internatonal Journal of Scence, Engneerng and Technology Research (IJSETR), Volume 5, Issue 3, March 2016 Hgh Speed, Low Power And Area Effcent Carry-Select Adder Nelant Harsh M.tech.VLSI Desgn Electroncs
More informationA New Type of Weighted DV-Hop Algorithm Based on Correction Factor in WSNs
Journal of Communcatons Vol. 9, No. 9, September 2014 A New Type of Weghted DV-Hop Algorthm Based on Correcton Factor n WSNs Yng Wang, Zhy Fang, and Ln Chen Department of Computer scence and technology,
More informationUncertainty in measurements of power and energy on power networks
Uncertanty n measurements of power and energy on power networks E. Manov, N. Kolev Department of Measurement and Instrumentaton, Techncal Unversty Sofa, bul. Klment Ohrdsk No8, bl., 000 Sofa, Bulgara Tel./fax:
More informationLearning Ensembles of Convolutional Neural Networks
Learnng Ensembles of Convolutonal Neural Networks Lran Chen The Unversty of Chcago Faculty Mentor: Greg Shakhnarovch Toyota Technologcal Insttute at Chcago 1 Introducton Convolutonal Neural Networks (CNN)
More informationGrain Moisture Sensor Data Fusion Based on Improved Radial Basis Function Neural Network
Gran Mosture Sensor Data Fuson Based on Improved Radal Bass Functon Neural Network Lu Yang, Gang Wu, Yuyao Song, and Lanlan Dong 1 College of Engneerng, Chna Agrcultural Unversty, Bejng,100083, Chna zhjunr@gmal.com,{yanglu,maozhhua}@cau.edu.cn
More informationCalculation of the received voltage due to the radiation from multiple co-frequency sources
Rec. ITU-R SM.1271-0 1 RECOMMENDATION ITU-R SM.1271-0 * EFFICIENT SPECTRUM UTILIZATION USING PROBABILISTIC METHODS Rec. ITU-R SM.1271 (1997) The ITU Radocommuncaton Assembly, consderng a) that communcatons
More informationPerformance Analysis of Multi User MIMO System with Block-Diagonalization Precoding Scheme
Performance Analyss of Mult User MIMO System wth Block-Dagonalzaton Precodng Scheme Yoon Hyun m and Jn Young m, wanwoon Unversty, Department of Electroncs Convergence Engneerng, Wolgye-Dong, Nowon-Gu,
More informationPRACTICAL, COMPUTATION EFFICIENT HIGH-ORDER NEURAL NETWORK FOR ROTATION AND SHIFT INVARIANT PATTERN RECOGNITION. Evgeny Artyomov and Orly Yadid-Pecht
68 Internatonal Journal "Informaton Theores & Applcatons" Vol.11 PRACTICAL, COMPUTATION EFFICIENT HIGH-ORDER NEURAL NETWORK FOR ROTATION AND SHIFT INVARIANT PATTERN RECOGNITION Evgeny Artyomov and Orly
More informationANNUAL OF NAVIGATION 11/2006
ANNUAL OF NAVIGATION 11/2006 TOMASZ PRACZYK Naval Unversty of Gdyna A FEEDFORWARD LINEAR NEURAL NETWORK WITH HEBBA SELFORGANIZATION IN RADAR IMAGE COMPRESSION ABSTRACT The artcle presents the applcaton
More informationFast Code Detection Using High Speed Time Delay Neural Networks
Fast Code Detecton Usng Hgh Speed Tme Delay Neural Networks Hazem M. El-Bakry 1 and Nkos Mastoraks 1 Faculty of Computer Scence & Informaton Systems, Mansoura Unversty, Egypt helbakry0@yahoo.com Department
More informationTraffic balancing over licensed and unlicensed bands in heterogeneous networks
Correspondence letter Traffc balancng over lcensed and unlcensed bands n heterogeneous networks LI Zhen, CUI Qme, CUI Zhyan, ZHENG We Natonal Engneerng Laboratory for Moble Network Securty, Bejng Unversty
More informationD-STATCOM Optimal Allocation Based On Investment Decision Theory
Internatonal Conference on Computer Engneerng, Informaton Scence & Applcaton Technology (ICCIA 2016) D-STATCOM Optmal Allocaton Based On Investment Decson Theory Yongjun Zhang1, a, Yfu Mo1, b and Huazhen
More informationThe Spectrum Sharing in Cognitive Radio Networks Based on Competitive Price Game
8 Y. B. LI, R. YAG, Y. LI, F. YE, THE SPECTRUM SHARIG I COGITIVE RADIO ETWORKS BASED O COMPETITIVE The Spectrum Sharng n Cogntve Rado etworks Based on Compettve Prce Game Y-bng LI, Ru YAG., Yun LI, Fang
More informationThe PWM speed regulation of DC motor based on intelligent control
Avalable onlne at www.scencedrect.com Systems Engneerng Proceda 3 (22) 259 267 The 2 nd Internatonal Conference on Complexty Scence & Informaton Engneerng The PWM speed regulaton of DC motor based on ntellgent
More informationDynamic Optimization. Assignment 1. Sasanka Nagavalli January 29, 2013 Robotics Institute Carnegie Mellon University
Dynamc Optmzaton Assgnment 1 Sasanka Nagavall snagaval@andrew.cmu.edu 16-745 January 29, 213 Robotcs Insttute Carnege Mellon Unversty Table of Contents 1. Problem and Approach... 1 2. Optmzaton wthout
More informationThe Impact of Spectrum Sensing Frequency and Packet- Loading Scheme on Multimedia Transmission over Cognitive Radio Networks
Ths artcle has been accepted for publcaton n a future ssue of ths journal, but has not been fully edted. Content may change pror to fnal publcaton. The Impact of Spectrum Sensng Frequency and Pacet- Loadng
More informationIEE Electronics Letters, vol 34, no 17, August 1998, pp ESTIMATING STARTING POINT OF CONDUCTION OF CMOS GATES
IEE Electroncs Letters, vol 34, no 17, August 1998, pp. 1622-1624. ESTIMATING STARTING POINT OF CONDUCTION OF CMOS GATES A. Chatzgeorgou, S. Nkolads 1 and I. Tsoukalas Computer Scence Department, 1 Department
More informationControl of Chaos in Positive Output Luo Converter by means of Time Delay Feedback
Control of Chaos n Postve Output Luo Converter by means of Tme Delay Feedback Nagulapat nkran.ped@gmal.com Abstract Faster development n Dc to Dc converter technques are undergong very drastc changes due
More informationA Patent Quality Classification System Using a Kernel-PCA with SVM
ADVCOMP 05 : The nth Internatonal Conference on Advanced Engneerng Computng and Applcatons n Scences A Patent Qualty Classfcaton System Usng a Kernel-PCA wth SVM Pe-Chann Chang Innovaton Center for Bg
More informationEfficient Large Integers Arithmetic by Adopting Squaring and Complement Recoding Techniques
The th Worshop on Combnatoral Mathematcs and Computaton Theory Effcent Large Integers Arthmetc by Adoptng Squarng and Complement Recodng Technques Cha-Long Wu*, Der-Chyuan Lou, and Te-Jen Chang *Department
More informationSide-Match Vector Quantizers Using Neural Network Based Variance Predictor for Image Coding
Sde-Match Vector Quantzers Usng Neural Network Based Varance Predctor for Image Codng Shuangteng Zhang Department of Computer Scence Eastern Kentucky Unversty Rchmond, KY 40475, U.S.A. shuangteng.zhang@eku.edu
More informationTime-frequency Analysis Based State Diagnosis of Transformers Windings under the Short-Circuit Shock
Tme-frequency Analyss Based State Dagnoss of Transformers Wndngs under the Short-Crcut Shock YUYING SHAO, ZHUSHI RAO School of Mechancal Engneerng ZHIJIAN JIN Hgh Voltage Lab Shangha Jao Tong Unversty
More informationResearch on Controller of Micro-hydro Power System Nan XIE 1,a, Dezhi QI 2,b,Weimin CHEN 2,c, Wei WANG 2,d
Advanced Materals Research Submtted: 2014-05-13 ISSN: 1662-8985, Vols. 986-987, pp 1121-1124 Accepted: 2014-05-19 do:10.4028/www.scentfc.net/amr.986-987.1121 Onlne: 2014-07-18 2014 Trans Tech Publcatons,
More informationOpen Access Research on PID Controller in Active Magnetic Levitation Based on Particle Swarm Optimization Algorithm
Send Orders for Reprnts to reprnts@benthamscence.ae 1870 The Open Automaton and Control Systems Journal, 2015, 7, 1870-1874 Open Access Research on PID Controller n Actve Magnetc Levtaton Based on Partcle
More informationResearch on the Process-level Production Scheduling Optimization Based on the Manufacturing Process Simplifies
Internatonal Journal of Smart Home Vol.8, No. (04), pp.7-6 http://dx.do.org/0.457/sh.04.8.. Research on the Process-level Producton Schedulng Optmzaton Based on the Manufacturng Process Smplfes Y. P. Wang,*,
More informationTopology Control for C-RAN Architecture Based on Complex Network
Topology Control for C-RAN Archtecture Based on Complex Network Zhanun Lu, Yung He, Yunpeng L, Zhaoy L, Ka Dng Chongqng key laboratory of moble communcatons technology Chongqng unversty of post and telecommuncaton
More informationNOVEL ITERATIVE TECHNIQUES FOR RADAR TARGET DISCRIMINATION
NOVEL ITERATIVE TECHNIQUES FOR RADAR TARGET DISCRIMINATION Phaneendra R.Venkata, Nathan A. Goodman Department of Electrcal and Computer Engneerng, Unversty of Arzona, 30 E. Speedway Blvd, Tucson, Arzona
More informationWalsh Function Based Synthesis Method of PWM Pattern for Full-Bridge Inverter
Walsh Functon Based Synthess Method of PWM Pattern for Full-Brdge Inverter Sej Kondo and Krt Choesa Nagaoka Unversty of Technology 63-, Kamtomoka-cho, Nagaoka 9-, JAPAN Fax: +8-58-7-95, Phone: +8-58-7-957
More informationMethods for Preventing Voltage Collapse
Methods for Preventng Voltage Collapse Cláuda Res 1, Antóno Andrade 2, and F. P. Macel Barbosa 3 1 Telecommuncatons Insttute of Avero Unversty, Unversty Campus of Avero, Portugal cres@av.t.pt 2 Insttute
More informationTo: Professor Avitabile Date: February 4, 2003 From: Mechanical Student Subject: Experiment #1 Numerical Methods Using Excel
To: Professor Avtable Date: February 4, 3 From: Mechancal Student Subject:.3 Experment # Numercal Methods Usng Excel Introducton Mcrosoft Excel s a spreadsheet program that can be used for data analyss,
More informationVoltage security constrained reactive power optimization incorporating wind generation
Unversty of Wollongong Research Onlne Faculty of Engneerng and Informaton Scences - Papers: Part A Faculty of Engneerng and Informaton Scences 2012 Voltage securty constraned reactve power optmzaton ncorporatng
More informationComparative Analysis of Reuse 1 and 3 in Cellular Network Based On SIR Distribution and Rate
Comparatve Analyss of Reuse and 3 n ular Network Based On IR Dstrbuton and Rate Chandra Thapa M.Tech. II, DEC V College of Engneerng & Technology R.V.. Nagar, Chttoor-5727, A.P. Inda Emal: chandra2thapa@gmal.com
More informationAdaptive System Control with PID Neural Networks
Adaptve System Control wth PID Neural Networs F. Shahra a, M.A. Fanae b, A.R. Aromandzadeh a a Department of Chemcal Engneerng, Unversty of Sstan and Baluchestan, Zahedan, Iran. b Department of Chemcal
More informationSensors for Motion and Position Measurement
Sensors for Moton and Poston Measurement Introducton An ntegrated manufacturng envronment conssts of 5 elements:- - Machne tools - Inspecton devces - Materal handlng devces - Packagng machnes - Area where
More informationDevelopment of an UWB Rescue Radar System - Detection of Survivors Using Fuzzy Reasoning -
Development of an UWB Rescue Radar System - Detecton of Survvors Usng Fuzzy Reasonng - Iwak Akyama Shonan Insttute of Technology Fujsawa 251-8511 Japan akyama@wak.org Masatosh Enokto Shonan Insttute of
More informationPower Distribution Strategy Considering Active Power Loss for DFIGs Wind Farm
Journal of Power and Energy Engneerng, 014,, 13-19 Publshed Onlne Aprl 014 n cres. http://www.scrp.org/journal/jpee http://dx.do.org/10.436/jpee.014.4030 Power Dstrbuton trategy Consderng Actve Power Loss
More informationWebinar Series TMIP VISION
Webnar Seres TMIP VISION TMIP provdes techncal support and promotes knowledge and nformaton exchange n the transportaton plannng and modelng communty. DISCLAIMER The vews and opnons expressed durng ths
More informationImprovement of the Vehicle License Plate Recognition System in the Environment of Rain and Fog Zhun Wang 1, a *, Zhenyu Liu 2,b
Internatonal Conference on Informaton Technology and Management Innovaton (ICITMI 05) Improvement of the Vehcle Lcense Plate Recognton System n the Envronment of Ran and Fog Zhun Wang, a *, Zhenyu Lu,b
More informationA Novel Spatial Interpolation Method Based on the Integrated RBF Neural Network
Avalable onlne at www.scencedrect.com Proceda Envronmental Scences 10 (2011 ) 568 575 2011 3rd Internatonal Conference on Envronmental Scence and Informaton Applcaton Technology (ESIAT 2011) www.elsever.com/locate/proceda
More informationOptimizing a System of Threshold-based Sensors with Application to Biosurveillance
Optmzng a System of Threshold-based Sensors wth Applcaton to Bosurvellance Ronald D. Frcker, Jr. Thrd Annual Quanttatve Methods n Defense and Natonal Securty Conference May 28, 2008 What s Bosurvellance?
More informationFigure.1. Basic model of an impedance source converter JCHPS Special Issue 12: August Page 13
A Hgh Gan DC - DC Converter wth Soft Swtchng and Power actor Correcton for Renewable Energy Applcaton T. Selvakumaran* and. Svachdambaranathan Department of EEE, Sathyabama Unversty, Chenna, Inda. *Correspondng
More informationOptimal Sizing and Allocation of Residential Photovoltaic Panels in a Distribution Network for Ancillary Services Application
Optmal Szng and Allocaton of Resdental Photovoltac Panels n a Dstrbuton Networ for Ancllary Servces Applcaton Reza Ahmad Kordhel, Student Member, IEEE, S. Al Pourmousav, Student Member, IEEE, Jayarshnan
More informationAdvanced Bio-Inspired Plausibility Checking in a Wireless Sensor Network Using Neuro-Immune Systems
Fourth Internatonal Conference on Sensor Technologes and Applcatons Advanced Bo-Inspred Plausblty Checkng n a reless Sensor Network Usng Neuro-Immune Systems Autonomous Fault Dagnoss n an Intellgent Transportaton
More informationAn Algorithm Forecasting Time Series Using Wavelet
IJCSI Internatonal Journal of Computer Scence Issues, Vol., Issue, No, January 04 ISSN (Prnt): 94-084 ISSN (Onlne): 94-0784 www.ijcsi.org 0 An Algorthm Forecastng Tme Seres Usng Wavelet Kas Ismal Ibraheem,Eman
More informationRejection of PSK Interference in DS-SS/PSK System Using Adaptive Transversal Filter with Conditional Response Recalculation
SERBIAN JOURNAL OF ELECTRICAL ENGINEERING Vol., No., November 23, 3-9 Rejecton of PSK Interference n DS-SS/PSK System Usng Adaptve Transversal Flter wth Condtonal Response Recalculaton Zorca Nkolć, Bojan
More informationResearch on Peak-detection Algorithm for High-precision Demodulation System of Fiber Bragg Grating
, pp. 337-344 http://dx.do.org/10.1457/jht.014.7.6.9 Research on Peak-detecton Algorthm for Hgh-precson Demodulaton System of Fber ragg Gratng Peng Wang 1, *, Xu Han 1, Smn Guan 1, Hong Zhao and Mngle
More informationA study of turbo codes for multilevel modulations in Gaussian and mobile channels
A study of turbo codes for multlevel modulatons n Gaussan and moble channels Lamne Sylla and Paul Forter (sylla, forter)@gel.ulaval.ca Department of Electrcal and Computer Engneerng Laval Unversty, Ste-Foy,
More informationResearch Article Dynamic Relay Satellite Scheduling Based on ABC-TOPSIS Algorithm
Mathematcal Problems n Engneerng Volume 2016, Artcle ID 3161069, 11 pages http://dx.do.org/10.1155/2016/3161069 Research Artcle Dynamc Relay Satellte Schedulng Based on ABC-TOPSIS Algorthm Shufeng Zhuang,
More informationStatic Security Based Available Transfer Capability (ATC) Computation for Real-Time Power Markets
SERBIAN JOURNAL OF ELECTRICAL ENGINEERING Vol. 7, No. 2, November 2010, 269-289 UDK: 004.896:621.311.15 Statc Securty Based Avalable Transfer Capablty (ATC) Computaton for Real-Tme Power Markets Chntham
More informationRC Filters TEP Related Topics Principle Equipment
RC Flters TEP Related Topcs Hgh-pass, low-pass, Wen-Robnson brdge, parallel-t flters, dfferentatng network, ntegratng network, step response, square wave, transfer functon. Prncple Resstor-Capactor (RC)
More informationCoverage Maximization in Mobile Wireless Sensor Networks Utilizing Immune Node Deployment Algorithm
CCECE 2014 1569888203 Coverage Maxmzaton n Moble Wreless Sensor Networs Utlzng Immune Node Deployment Algorthm Mohammed Abo-Zahhad, Sabah M. Ahmed and Nabl Sabor Electrcal and Electroncs Engneerng Department
More informationImplementation of Adaptive Neuro Fuzzy Inference System in Speed Control of Induction Motor Drives
J. Intellgent Learnng Systems & Applcatons, 00, : 0-8 do:0.436/jlsa.00.04 Publshed Onlne May 00 (http://www.scrp.org/journal/jlsa) Implementaton of Adaptve Neuro Fuzzy Inference System n Speed Control
More informationA NSGA-II algorithm to solve a bi-objective optimization of the redundancy allocation problem for series-parallel systems
0 nd Internatonal Conference on Industral Technology and Management (ICITM 0) IPCSIT vol. 49 (0) (0) IACSIT Press, Sngapore DOI: 0.776/IPCSIT.0.V49.8 A NSGA-II algorthm to solve a b-obectve optmzaton of
More informationEquivalent Circuit Model of Electromagnetic Behaviour of Wire Objects by the Matrix Pencil Method
ERBIAN JOURNAL OF ELECTRICAL ENGINEERING Vol. 5, No., May 008, -0 Equvalent Crcut Model of Electromagnetc Behavour of Wre Objects by the Matrx Pencl Method Vesna Arnautovsk-Toseva, Khall El Khamlch Drss,
More informationBP Neural Network based on PSO Algorithm for Temperature Characteristics of Gas Nanosensor
2318 JOURNAL OF COMPUTERS, VOL. 7, NO. 9, SEPTEMBER 2012 BP Neural Network based on PSO Algorthm for Temperature Characterstcs of Gas Nanosensor Weguo Zhao Center of Educaton Technology, Hebe Unversty
More informationSTUDY OF MATRIX CONVERTER BASED UNIFIED POWER FLOW CONTROLLER APPLIED PI-D CONTROLLER
Journal of Engneerng Scence and Technology Specal Issue on Appled Engneerng and Scences, October (214) 3-38 School of Engneerng, Taylor s Unversty STUDY OF MATRIX CONVERTER BASED UNIFIED POWER FLOW CONTROLLER
More informationISSN: (p); (e) DEVELOPMENT OF FUZZY IX-MR CONTROL CHART USING FUZZY MODE AND FUZZY RULES APPROACHES
DEVELOPMENT OF FUZZY IX-MR CONTROL CHART USING FUZZY MODE AND FUZZY RULES APPROACHES Azam Morad Tad, Soroush Avakh Darestan 2* Department of Industral Engneerng, Scence and Research Branch, Islamc Azad
More informationarxiv: v1 [cs.lg] 8 Jul 2016
Overcomng Challenges n Fxed Pont Tranng of Deep Convolutonal Networks arxv:1607.02241v1 [cs.lg] 8 Jul 2016 Darryl D. Ln Qualcomm Research, San Dego, CA 92121 USA Sachn S. Talath Qualcomm Research, San
More informationTh P5 13 Elastic Envelope Inversion SUMMARY. J.R. Luo* (Xi'an Jiaotong University), R.S. Wu (UC Santa Cruz) & J.H. Gao (Xi'an Jiaotong University)
-4 June 5 IFEMA Madrd h P5 3 Elastc Envelope Inverson J.R. Luo* (X'an Jaotong Unversty), R.S. Wu (UC Santa Cruz) & J.H. Gao (X'an Jaotong Unversty) SUMMARY We developed the elastc envelope nverson method.
More informationWhite Paper. OptiRamp Model-Based Multivariable Predictive Control. Advanced Methodology for Intelligent Control Actions
Whte Paper OptRamp Model-Based Multvarable Predctve Control Advanced Methodology for Intellgent Control Actons Vadm Shapro Dmtry Khots, Ph.D. Statstcs & Control, Inc., (S&C) propretary nformaton. All rghts
More informationA MODIFIED DIFFERENTIAL EVOLUTION ALGORITHM IN SPARSE LINEAR ANTENNA ARRAY SYNTHESIS
A MODIFIED DIFFERENTIAL EVOLUTION ALORITHM IN SPARSE LINEAR ANTENNA ARRAY SYNTHESIS Kaml Dmller Department of Electrcal-Electroncs Engneerng rne Amercan Unversty North Cyprus, Mersn TURKEY kdmller@gau.edu.tr
More informationNATIONAL RADIO ASTRONOMY OBSERVATORY Green Bank, West Virginia SPECTRAL PROCESSOR MEMO NO. 25. MEMORANDUM February 13, 1985
NATONAL RADO ASTRONOMY OBSERVATORY Green Bank, West Vrgna SPECTRAL PROCESSOR MEMO NO. 25 MEMORANDUM February 13, 1985 To: Spectral Processor Group From: R. Fsher Subj: Some Experments wth an nteger FFT
More informationWireless Sensor Network Coverage Optimization Based on Fruit Fly Algorithm
Wreless Sensor Network Coverage Optmzaton Based on Frut Fly Algorthm https://do.org/10.3991/joe.v1406.8698 Ren Song!! ", Zhchao Xu, Yang Lu Jln Unversty of Fnance and Economcs, Jln, Chna rensong1579@163.com
More informationOptimal Placement of PMU and RTU by Hybrid Genetic Algorithm and Simulated Annealing for Multiarea Power System State Estimation
T. Kerdchuen and W. Ongsakul / GMSARN Internatonal Journal (09) - Optmal Placement of and by Hybrd Genetc Algorthm and Smulated Annealng for Multarea Power System State Estmaton Thawatch Kerdchuen and
More informationPower System State Estimation Using Phasor Measurement Units
Unversty of Kentucky UKnowledge Theses and Dssertatons--Electrcal and Computer Engneerng Electrcal and Computer Engneerng 213 Power System State Estmaton Usng Phasor Measurement Unts Jaxong Chen Unversty
More informationMASTER TIMING AND TOF MODULE-
MASTER TMNG AND TOF MODULE- G. Mazaher Stanford Lnear Accelerator Center, Stanford Unversty, Stanford, CA 9409 USA SLAC-PUB-66 November 99 (/E) Abstract n conjuncton wth the development of a Beam Sze Montor
More informationDetection of short circuit in pulse gas metal arc welding process
of Achevements n Materals and Manufacturng Engneerng VOLUME 4 ISSUE 1 September 007 Detecton of short crcut n pulse gas metal arc weldng process.k.d.v. Yarlagadda a, * co-operatng wth. raveen a, *, V.K.
More informationOptimal Phase Arrangement of Distribution Feeders Using Immune Algorithm
The 4th Internatonal Conference on Intellgent System Applcatons to Power Systems, ISAP 2007 Optmal Phase Arrangement of Dstrbuton Feeders Usng Immune Algorthm C.H. Ln, C.S. Chen, M.Y. Huang, H.J. Chuang,
More informationResearch on Algorithm for Feature Extraction and Classification of Motor Imagery EEG Signals
BIO Web of Conferences 8, 3 (7) DOI:.5/ boconf/783 ICMSB6 Research on Algorthm for Feature Extracton and Classfcaton of Motor Imagery EEG Sgnals uan Tan, a and Zhaochen Zhang College of Medcal Informaton
More informationOpen Access Node Localization Method for Wireless Sensor Networks Based on Hybrid Optimization of Differential Evolution and Particle Swarm Algorithm
Send Orders for Reprnts to reprnts@benthamscence.ae The Open Automaton and Control Systems Journal, 014, 6, 61-68 61 Open Access Node Localzaton Method for Wreless Sensor Networks Based on Hybrd Optmzaton
More informationProceedings of the 6th WSEAS International Conference on Applications of Electrical Engineering, Istanbul, Turkey, May 27-29,
Proceedngs o the 6th WSEAS Internatonal Conerence on Applcatons o Electrcal Engneerng, Istanbul, Turkey, May 27-29, 2007 189 THE SPEED CONTROL OF DC SERVO MOTOR WITH PROPORTIONAL INTEGRAL, FUZZY LOGIC
More informationThe Performance Improvement of BASK System for Giga-Bit MODEM Using the Fuzzy System
Int. J. Communcatons, Network and System Scences, 10, 3, 1-5 do:10.36/jcns.10.358 Publshed Onlne May 10 (http://www.scrp.org/journal/jcns/) The Performance Improvement of BASK System for Gga-Bt MODEM Usng
More informationApplying Rprop Neural Network for the Prediction of the Mobile Station Location
Sensors 0,, 407-430; do:0.3390/s040407 OPE ACCESS sensors ISS 44-80 www.mdp.com/journal/sensors Communcaton Applyng Rprop eural etwork for the Predcton of the Moble Staton Locaton Chen-Sheng Chen, * and
More informationNetworks. Backpropagation. Backpropagation. Introduction to. Backpropagation Network training. Backpropagation Learning Details 1.04.
Networs Introducton to - In 1986 a method for learnng n mult-layer wor,, was nvented by Rumelhart Paper Why are what and where processed by separate cortcal vsual systems? - The algorthm s a sensble approach
More informationRBF NN Based Marine Diesel Engine Generator Modeling
005 Amercan Control Conference June 8-0, 005. Portland, OR, USA ThB4.6 RBF Based Marne Desel Engne Generator Modelng Wefeng Sh, Janmn Yang, Tanhao Tang, Member, IEEE Abstract For buldng a real tme marne
More informationRadio Link Parameters Based QoE Measurement of Voice Service in GSM Network *
Communcatons and etwork, 2013, 5, 448-454 http://dx.do.org/10.4236/cn.2013.53b2083 Publshed Onlne September 2013 (http://www.scrp.org/journal/cn) Rado Lnk Parameters Based QoE Measurement of Voce Servce
More informationIndirect Symmetrical PST Protection Based on Phase Angle Shift and Optimal Radial Basis Function Neural Network
Indrect Symmetrcal PST Protecton Based on Phase Angle Shft and Optmal Radal Bass Functon Neural Networ Shalendra Kumar Bhaser Department of Electrcal Engneerng Indan Insttute of Technology Rooree, Inda
More information熊本大学学術リポジトリ. Kumamoto University Repositor
熊本大学学術リポジトリ Kumamoto Unversty Repostor Ttle Wreless LAN Based Indoor Poston and Its Smulaton Author(s) Ktasuka, Teruak; Nakansh, Tsune CtatonIEEE Pacfc RIM Conference on Comm Computers, and Sgnal Processng
More informationOptimization of Shortest Path of Multiple Transportation Model Based on Cost Analyses
Optmzaton of Shortest Path of Multple Transportaton Model Based on Cost Analyses Yang Yang 1,2 Ruyng Wang 1 Qanqan Zhang 1 1 Chna Unversty of Mnng & Technology (Bejng), School of Management, Bejng, 100083,
More informationHigh Accuracy Signal Recognition Algorithm Based on Machine Learning for Heterogeneous Cognitive Wireless Networks
Journal of Communcatons Vol., o. 3, March 7 Hgh Accuracy Sgnal Recognton Algorthm Based on Machne Learnng for Heterogeneous Cogntve Wreless etworks Jan Lu, Jbn Wang, and San Umar Abdullah School of Computer
More informationPriority based Dynamic Multiple Robot Path Planning
2nd Internatonal Conference on Autonomous obots and Agents Prorty based Dynamc Multple obot Path Plannng Abstract Taxong Zheng Department of Automaton Chongqng Unversty of Post and Telecommuncaton, Chna
More informationOptimum Allocation of Distributed Generations Based on Evolutionary Programming for Loss Reduction and Voltage Profile Correction
ISSN : 0976-8491(Onlne) ISSN : 2229-4333(rnt) Optmum Allocaton of Dstrbuted Generatons Based on Evolutonary rogrammng for Reducton and Voltage rofle Correcton 1 Mohammad Saleh Male, 2 Soodabeh Soleyman
More informationYarn tenacity modeling using artificial neural networks and development of a decision support system based on genetic algorithms
Journal of AI and Data Mnng Vol 2, No, 204, 73-78 Yarn tenacty modelng usng artfcal neural networks and development of a decson support system based on genetc algorthms M Dasht, V Derham 2*, E Ekhtyar
More informationPredicting Freeway Travelling Time Using Multiple- Source Data
1 2 3 4 5 6 7 8 9 10 Artcle Predctng Freeway Travellng Tme Usng Multple- Source Data Kejun Long 1, Wuka Yao 2, Jan Gu 1 *and We Wu 1 1 Hunan Provncal Key Laboratory of Smart Roadway and Cooperatve Vehcle-Infrastructure
More informationShort Term Load Forecasting based on An Optimized Architecture of Hybrid Neural Network Model
Short Term Load Forecastng based on An Optmzed Archtecture of Hybrd Neural Network Model Fras Shhab Ahmed Turksh Aeronautcal Assocaton Unversty Department of Informaton Technology Ankara, Turkey Mnstry
More informationA Method Based on Dial's Algorithm for Multi-time Dynamic Traffic Assignment
Sensors & Transducers, Vol. 66, Issue 3, March 04, pp. 48-54 Sensors & Transducers 04 by IFSA Publshng, S. L. http://www.sensorsportal.com A Method Based on Dal's Algorthm for Mult-tme Dynamc Traffc Assgnment
More informationAn Optimal Model and Solution of Deployment of Airships for High Altitude Platforms
An Optmal Model and Soluton of Deployment of Arshps for Hgh Alttude Platforms Xuyu Wang, Xnbo Gao, Ru Zong, Peng Cheng. VIPS Lab, School of Electronc Engneerng, Xdan Unversty, X an 77, Chna. Department
More informationJournal of Chemical and Pharmaceutical Research, 2016, 8(4): Research Article
Avalable onlne www.ocpr.com Journal of Chemcal and Pharmaceutcal Research, 2016, 8(4):788-793 Research Artcle ISSN : 0975-7384 CODEN(USA) : JCPRC5 Vrtual Force Coverage Enhancement Optmzaton Algorthm Based
More informationQoS Provisioning in Wireless Data Networks under Non-Continuously Backlogged Users
os Provsonng n Wreless Data Networks under Non-Contnuously Backlogged Users Tmotheos Kastrnoganns, and Symeon Papavasslou, Member, IEEE School of Electrcal and Computer Engneerng Natonal Techncal Unversty
More informationMulti-focus Image Fusion Using Spatial Frequency and Genetic Algorithm
0 IJCSNS Internatonal Journal of Computer Scence and Network Securty, VOL.8 No., February 008 Mult-focus Image Fuson Usng Spatal Frequency and Genetc Algorthm Jun Kong,, Kayuan Zheng,, Jngbo Zhang,,*,,
More informationStudy on Shunt Active Power Filter with Improved Control Method Yaheng Ren1,a*, Xiaozhi Gao2,b, Runduo Wang3,c
Internatonal Conference on Advances n Energy and Envronmental Scence (ICAEES 015) Study on Shunt Actve Power Flter wth Improved Control Method Yaheng Ren1,a*, Xaozh Gao,b, Runduo Wang3,c 1 Insttute of
More informationGas Monitoring System Based on ZigBee Pro and a New Method for Safety Grade Evaluation
www.ijcsi.org 501 Gas Montorng System Based on ZgBee Pro and a New Method for Safety Grade Evaluaton Shutao Wang 1, Meme L 2, Quanmn Zhu 3, Mnghua Lu 4, Hongjn L 5 12,4,5 Insttute of Electrcal Engneerng,Yanshan
More informationResearch Article. Adaptive Neuro-Fuzzy Inference System based control of six DOF robot manipulator. Srinivasan Alavandar * and M. J.
Jestr Journal of Engneerng Scence and Technology Revew (8) 6- Research Artcle Adaptve Neuro-Fuzzy Inference System based control of sx DOF robot manpulator Srnvasan Alavandar * and M. J. Ngam JOURNAL OF
More informationPerformance Analysis of the Weighted Window CFAR Algorithms
Performance Analyss of the Weghted Wndow CFAR Algorthms eng Xangwe Guan Jan He You Department of Electronc Engneerng, Naval Aeronautcal Engneerng Academy, Er a road 88, Yanta Cty 6400, Shandong Provnce,
More informationJ. Electrical Systems 13-3 (2017): Regular paper
Mng-Yuan Cho 1, Hoang Th Thom 1,* J. Electrcal Systems 13-3 (2017): 415-428 Regular paper Fault Dagnoss for Dstrbuton Networks Usng Enhanced Support Vector Machne Classfer wth Classcal Multdmensonal Scalng
More informationEXPERIMENTAL KOHONEN NEURAL NETWORK IMPLEMENTED IN CMOS 0.18 m TECHNOLOGY
15 th Internatonal Conference MIXED DESIGN MIXDES 008 Pozna, POLAND 19-1 June 008 EXPERIMENTAL KOHONEN NEURAL NETWORK IMPLEMENTED IN CMOS 0.18m TECHNOLOGY R. DLUGOSZ 1,, T. TALASKA 3, J. DALECKI 3, R.
More information@IJMTER-2015, All rights Reserved 383
SIL of a Safety Fuzzy Logc Controller 1oo usng Fault Tree Analyss (FAT and realablty Block agram (RB r.-ing Mohammed Bsss 1, Fatma Ezzahra Nadr, Prof. Amam Benassa 3 1,,3 Faculty of Scence and Technology,
More informationEnsemble Evolution of Checkers Players with Knowledge of Opening, Middle and Endgame
Ensemble Evoluton of Checkers Players wth Knowledge of Openng, Mddle and Endgame Kyung-Joong Km and Sung-Bae Cho Department of Computer Scence, Yonse Unversty 134 Shnchon-dong, Sudaemoon-ku, Seoul 120-749
More information