Particle Swarm Optimization
|
|
- Phyllis McKenzie
- 5 years ago
- Views:
Transcription
1 Paricle Swarm Opimizaion Speaker: Jeng-Shyang Pan Deparmen of Elecronic Engineering, Kaohsiung Universiy of Applied Science, Taiwan 7/26/2004 ppso 1
2 Wha is he Paricle Swarm Opimizaion (PSO)? PSO is a recenly proposed algorihm, moivaed from he simulaion of social behavior. PSO is based on he evoluionary compuaion echnique. 7/26/2004 ppso 2
3 Wha is he Paricle Swarm Opimizaion (PSO)? A swarm of objecs moving in space and hus objecs are said o possess posiion and velociy and are influenced by he ohers in he swarm. PSO process he search scheme using populaions of paricles which correspond o he use of individuals in GAs. 7/26/2004 ppso 3
4 Wha is he Paricle Swarm Opimizaion (PSO)? Each paricle (individual) adjuss is flying (adjus velociy) according o is own flying experience and is companions flying experience. Each paricle is equivalen o a candidae soluion of a problem. 7/26/2004 ppso 4
5 Definiion The ih paricle posiion a he h ieraion can be represened as: X i = i i ( x (1), x (2), L, x ( D)). i 7/26/2004 ppso 5
6 Definiion The bes previous posiion (he posiion giving he bes finess value) of he ih paricle from he firs ieraion o he h ieraion is represened as: P i = i i ( p (1), p (2), L, p ( D)). i 7/26/2004 ppso 6
7 Definiion The bes posiion amongs all paricles from he firs ieraion o he h ieraion can be defined as: G = ( X (1), X (2), L, X ( D)). 7/26/2004 ppso 7
8 Definiion The rae of posiion change (velociy) for he ih paricle is recorded as: V i = i i ( v (1), v (2), L, v ( D)). i 7/26/2004 ppso 8
9 Definiion The paricles are manipulaed according o he following equaion: V + 1 i = W Vi + C1 r1 ( Pi X i ) + C2 r2 ( G X i ) (a) i = X i + Vi Where and are wo posiive consans, r 2 X C1 2 and are wo random funcions in he range [0,1]. W is he ineria weigh. C 1 (b) 7/26/2004 ppso 9 r
10 Applicaions Y. Fukuyama and H. Yoshida (2001), A paricle swarm opimizaion for reacive power and volage conrol in elecric power sysems. B. R. Secres and G. B. Lamon (2001), Communicaion in paricle swarm opimizaion illusraed by he raveling salesman problem. 7/26/2004 ppso 10
11 Applicaions V. Tandon (2000), Closing he gap beween CAD/CAM and opimized CNC end milling. H. Yoshida, K. Kawaa, Y. Fukuyama (1999) and Y. Nakanishi, A paricle swarm opimizaion for reacive power and volage conrol considering volage sabiliy. 7/26/2004 ppso 11
12 Applicaions R. Eberhar and X. Hu (1999), Human remor analysis using paricle swarm opimizaion. R. C. Eberhar and Y. Shi (1998), Evolving arificial neural neworks. 7/26/2004 ppso 12
13 Drawback of PSO Paricle swarm opimizaion algorihm and is relaed improved mehods are effecive for parameers of soluions which are independen or are loosely correlaed. However, i is no effecive when parameers of soluions are highly correlaed. (as shown in previous work by Shi & Eberhar (2001)) 7/26/2004 ppso 13
14 Why We Propose Parallel PSO algorihm? In 1987, Cohoon proposed he parallel geneic algorihms ha worked by dividing he populaion ino several groups and running he same algorihm over each group using differen processors. In order o achieve lower overall compuaion and ge beer soluions, a level of communicaion beween he groups is performed every fixed number of generaions. 7/26/2004 ppso 14
15 Why We Propose Parallel PSO algorihm? The parallel geneic algorihm periodically selecs promising individuals from each subpopulaion and migraes hem o differen subpopulaions. Wih his migraion, each subpopulaion will receive some new and promising chromosomes o replace he poorer chromosomes in a subpopulaion. This sraegy helps o avoid premaure convergence. 7/26/2004 ppso 15
16 Why We Propose Parallel PSO algorihm? The spiri of he daa parallelism mehod is uilized o creae a parallel paricle swarm opimizaion algorihm. PPSO is presened ogeher wih hree communicaion sraegies which can be used according o he independence of he daa. 7/26/2004 ppso 16
17 Communicaion Sraegies ( ) The firs sraegy is based on he observaion ha if parameers are independen or are only loosely correlaed. If we une he value of one parameer o ge a beer soluion cos by keeping he oher parameers consan, he value of his parameer is always near o he value of his parameer of he bes soluion. 7/26/2004 ppso 17
18 The Firs Sraegy Muliple copies of he bes paricles for all groups are muaed and hose muaed paricles migrae and replace he poorer paricles in he oher R 1 G groups every ieraions. 7/26/2004 ppso 18
19 f 2 2 1, x2) = ( x1 1) + ( x2 2) ( x x Global opimum 1 x 1 7/26/2004 ppso 19
20 Communicaion Sraegies ( ) The second sraegy is based on self-adjusmen in each group ha if he parameers of a soluion are srongly correlaed. In fac, he beer soluions spread among all he search space. We need o keep he parameers be divergen o all possible searching space. I is beer he communicaion only for he neighbourhood in order o keep he divergence. 7/26/2004 ppso 20
21 The Second Sraegy The bes paricle in G j each group is migraed o is neighbour groups o replace some of he more poorly performing paricles every ieraions. R 2 7/26/2004 ppso 21
22 f , x2) = ( x2 2) ( x1 + 3) + ( x2 5) ( x x 2 1 x1 = 3, x2 = 2 x 2 x = 0, x2 1 = 5 x 1 7/26/2004 ppso 22
23 Communicaion Sraegies ( ) If he properies of he parameers are unknown, we may apply he communicaion sraegy 3 which is he hybrid version of he communicaion sraegy 1 and 2. 7/26/2004 ppso 23
24 The Third Sraegy The hybrid sraegy separaes he groups ino wo equal sized subgroups wih he firs subgroup applying he firs R 1 sraegy every ieraions and all groups applying he second sraegy every ieraions. R 2 7/26/2004 ppso 24
25 PPSO wih Three Communicaion Sraegies 1. Iniializaion: Generae paricles for he jh group, i=0, N j -1, j=0,.s-1, S is he number of groups, is he paricle size for he N j jh group and is he ieraion number. Se =1. 2. Evaluaion: The value of f ) for every paricle N j in each group is evaluaed. ( X i, j X i, j 7/26/2004 ppso 25
26 PPSO wih hree communicaion sraegies 3. Updae: Updae he velociy and paricle posiions using equaions (a) and (b). 4. Communicaion: Three possible communicaion sraegies are adoped. 7/26/2004 ppso 26
27 PPSO wih hree communicaion sraegies 5. Terminaion: Sep 2 o 5 are repeaed unil he predefined value of he funcion or some maximum number of ieraions has been reached. Record he bes value of he funcion f ( G ) and he bes paricle posiion among all paricles G. 7/26/2004 ppso 27
28 Experimens For comparison, hree benchmark funcion repored in Shi & Eberhar (1999) are used. The firs funcion is he Rosenbrock funcion: n f1 ( X ) = (100( xi+ 1 xi ) + ( xi 1) ) i= /26/2004 ppso 28
29 Experimens The second funcion is he generalized Rasrigrin funcion: n 2 f 2 ( X ) = ( x i 10 cos(2π xi ) + 10) i= 1 The las funcion is he generalized Griewank funcion : 1 n n 2 xi f 3 ( X ) = xi cos( ) i= 1 i= 1 i 7/26/2004 ppso 29
30 Experimens Percenage of cos f 1 ( X ) Migraion PSO PPSO(2,80) PPSO(4,40) PPSO(8,20) None % % % % Performance comparison of PSO & PPSO wih he firs communicaion sraegy for Rosenbrock funcion 7/26/2004 ppso 30
31 Experimens Percenage of cos f 2 ( X ) Migraion PSO PPSO(2,80) PPSO(4,40) PPSO(8,20) None % % % % Performance comparison of PSO & PPSO wih he firs communicaion sraegy for Rasrigrin funcion 7/26/2004 ppso 31
32 Experimens Number of cos f 3 ( X ) Migraion PSO PPSO(2,80) PPSO(4,40) PPSO(8,20) None Performance comparison of PSO & PPSO wih he second communicaion sraegy for Griewank funcion 7/26/2004 ppso 32
33 Experimens Funcion cos PSO PPSO(4,40) PPSO(8,20) Rosenbrock Rasrigrin Griewank Performance comparison of PSO & PPSO wih he hird communicaion sraegy 7/26/2004 ppso 33
34 T H A N K Y O U!
Air Quality Index Prediction Using Error Back Propagation Algorithm and Improved Particle Swarm Optimization
Air Qualiy Index Predicion Using Error Back Propagaion Algorihm and Improved Paricle Swarm Opimizaion Jia Xu ( ) and Lang Pei College of Compuer Science, Wuhan Qinchuan Universiy, Wuhan, China 461406563@qq.com
More informationSTUDY ON VELOCITY CLAMPING IN PSO USING CEC`13 BENCHMARK
STUDY ON VELOCITY CLAMPING IN PSO USING CEC`13 BENCHMARK Michal Pluhacek, Roman Senkerik, Adam Vikorin and Tomas Kadavy Tomas Baa Universiy in Zlin, Faculy of Applied Informaics Nam T.G. Masaryka 5555,
More informationParticle Swarm Optimization Combining Diversification and Intensification for Nonlinear Integer Programming Problems
Paricle Swarm Opimizaion Combining Diversificaion and Inensificaion for Nonlinear Ineger Programming Problems Takeshi Masui, Masaoshi Sakawa, Kosuke Kao and Koichi Masumoo Hiroshima Universiy 1-4-1, Kagamiyama,
More informationWeightless Swarm Algorithm (WSA) for Dynamic Optimization Problems
Weighless Swarm Algorihm (WSA) for Dynamic Opimizaion Problems T.O. Ting 1,*, Ka Lok Man 2, Sheng-Uei Guan 2, Mohamed Nayel 1, and Kaiyu Wan 2 1 Dep. Elecrical and Elecronic Eng. 2 Dep. Compuer Science
More informationOptimizing Back-Propagation using PSO_Hill and PSO_A*
Inernaional Journal of Scienific and Research Publicaions, Volume 3, Issue 4, April 2013 1 Opimizing Back-Propagaion using PSO_Hill and PSO_A* Priyanka Sharma *, Asha Mishra ** * M.Tech Scholar of compuer
More informationMODULE - 9 LECTURE NOTES 2 GENETIC ALGORITHMS
1 MODULE - 9 LECTURE NOTES 2 GENETIC ALGORITHMS INTRODUCTION Mos real world opimizaion problems involve complexiies like discree, coninuous or mixed variables, muliple conflicing objecives, non-lineariy,
More informationSingle-Pass-Based Heuristic Algorithms for Group Flexible Flow-shop Scheduling Problems
Single-Pass-Based Heurisic Algorihms for Group Flexible Flow-shop Scheduling Problems PEI-YING HUANG, TZUNG-PEI HONG 2 and CHENG-YAN KAO, 3 Deparmen of Compuer Science and Informaion Engineering Naional
More informationVehicle Arrival Models : Headway
Chaper 12 Vehicle Arrival Models : Headway 12.1 Inroducion Modelling arrival of vehicle a secion of road is an imporan sep in raffic flow modelling. I has imporan applicaion in raffic flow simulaion where
More informationAppendix to Online l 1 -Dictionary Learning with Application to Novel Document Detection
Appendix o Online l -Dicionary Learning wih Applicaion o Novel Documen Deecion Shiva Prasad Kasiviswanahan Huahua Wang Arindam Banerjee Prem Melville A Background abou ADMM In his secion, we give a brief
More informationMulti-area Load Frequency Control using IP Controller Tuned by Particle Swarm Optimization
esearch Journal of Applied Sciences, Engineering and echnology (): 96-, ISSN: -767 axwell Scienific Organizaion, Submied: July, Acceped: Sepember 8, Published: ecember 6, uli-area Load Frequency Conrol
More informationA Framework for Efficient Document Ranking Using Order and Non Order Based Fitness Function
A Framework for Efficien Documen Ranking Using Order and Non Order Based Finess Funcion Hazra Imran, Adii Sharan Absrac One cenral problem of informaion rerieval is o deermine he relevance of documens
More informationMachine Loading in Flexible Manufacturing System: A Swarm Optimization Approach
Machine Loading in Flexible Manufacuring Sysem: A Swarm Opimizaion Approach Sandhyarani Biswas Naional Insiue of Technology sandhya_biswas@yahoo.co.in S.S.Mahapara Naional Insiue of Technology mahaparass2003@yahoo.com
More informationParticle Swarm Optimization Algorithm for Agent-Based Artificial Markets. Tong Zhang and B. Wade Brorsen
Paricle Swarm Opimizaion Algorihm for Agen-Based Arificial Markes Tong Zhang and B. Wade Brorsen Absrac Paricle swarm opimizaion (PSO) is adaped o simulae dynamic economic games. The robusness and speed
More informationApplying Genetic Algorithms for Inventory Lot-Sizing Problem with Supplier Selection under Storage Capacity Constraints
IJCSI Inernaional Journal of Compuer Science Issues, Vol 9, Issue 1, No 1, January 2012 wwwijcsiorg 18 Applying Geneic Algorihms for Invenory Lo-Sizing Problem wih Supplier Selecion under Sorage Capaciy
More informationPhysics 235 Chapter 2. Chapter 2 Newtonian Mechanics Single Particle
Chaper 2 Newonian Mechanics Single Paricle In his Chaper we will review wha Newon s laws of mechanics ell us abou he moion of a single paricle. Newon s laws are only valid in suiable reference frames,
More informationOptimal Capacitor Placement for Loss Reduction in Distribution Systems Using Bat Algorithm
IOSR Journal of Engineering (IOSRJEN) e-issn: 2250-3021, p-issn: 2278-8719, Volume 2, Issue 10 (Ocober 2012), PP 23-27 Opimal Capacior Placemen for Loss Reducion in Disribuion Sysems Using Ba Algorihm
More informationConvergence Improvement of Reliability-Based MultiobjectiveOptimization Using Hybrid MOPSO
10 h World Congress on Srucural and Mulidisciplinary Opimizaion May 19-4, 013, Orlando, Florida, USA Convergence Improvemen of Reliabiliy-Based MuliobjeciveOpimizaion Using Hybrid MOPSO Shoichiro KAWAJI
More informationKeywords Digital Infinite-Impulse Response (IIR) filter, Digital Finite-Impulse Response (FIR) filter, DE, exploratory move
Volume 5, Issue 7, July 2015 ISSN: 2277 128X Inernaional Journal of Advanced Research in Compuer Science and Sofware Engineering Research Paper Available online a: www.ijarcsse.com A Hybrid Differenial
More informationOptimal Design of LQR Weighting Matrices based on Intelligent Optimization Methods
Opimal Design of LQR Weighing Marices based on Inelligen Opimizaion Mehods Inernaional Journal of Inelligen Informaion Processing, Volume, Number, March Opimal Design of LQR Weighing Marices based on Inelligen
More informationAn Optimal Dynamic Generation Scheduling for a Wind-Thermal Power System *
Energy and Power Engineering, 2013, 5, 1016-1021 doi:10.4236/epe.2013.54b194 Published Online July 2013 (hp://www.scirp.org/journal/epe) An Opimal Dynamic Generaion Scheduling for a Wind-Thermal Power
More informationApplying Genetic Algorithms for Inventory Lot-Sizing Problem with Supplier Selection under Storage Space
Inernaional Journal of Indusrial and Manufacuring Engineering Applying Geneic Algorihms for Invenory Lo-Sizing Problem wih Supplier Selecion under Sorage Space Vichai Rungreunganaun and Chirawa Woarawichai
More informationA Modified Particle Swarm Optimization For Engineering Constrained Optimization Problems
Inernaional Journal of Compuer Science and Elecronics Engineering (IJCSEE Volume 3, Issue 1 (015 ISSN 30 408 (Online A Modified Paricle Swarm Opimizaion For Engineering Consrained Opimizaion Problems Choosak
More informationOptimal Placement of Unified Power Quality Conditioner using Ant Lion Optimization Method
Research India Publicaions. hp://www.ripublicaion.com Opimal Placemen of Unified Power Qualiy Condiioner using An Lion Opimizaion Mehod M. Laxmidevi Ramanaiah 1 and Dr. M. Damodar Reddy 2 Research Scholar
More informationOpen Access Modeling and Optimization Control for Aircraft AC Generator Brushless Excitation System Based on Improved Adaptive PSO
Send Orders for Reprins o reprins@benhamscience.ae The Open Auomaion and Conrol Sysems Journal, 2015, 7, 21-30 21 Open Access Modeling and Opimizaion Conrol for Aircraf AC Generaor Brushless Exciaion Sysem
More informationRandom Walk with Anti-Correlated Steps
Random Walk wih Ani-Correlaed Seps John Noga Dirk Wagner 2 Absrac We conjecure he expeced value of random walks wih ani-correlaed seps o be exacly. We suppor his conjecure wih 2 plausibiliy argumens and
More informationSliding Mode Extremum Seeking Control for Linear Quadratic Dynamic Game
Sliding Mode Exremum Seeking Conrol for Linear Quadraic Dynamic Game Yaodong Pan and Ümi Özgüner ITS Research Group, AIST Tsukuba Eas Namiki --, Tsukuba-shi,Ibaraki-ken 5-856, Japan e-mail: pan.yaodong@ais.go.jp
More informationCHAPTER 12 DIRECT CURRENT CIRCUITS
CHAPTER 12 DIRECT CURRENT CIUITS DIRECT CURRENT CIUITS 257 12.1 RESISTORS IN SERIES AND IN PARALLEL When wo resisors are conneced ogeher as shown in Figure 12.1 we said ha hey are conneced in series. As
More informationApplication of Artificial Bee Colony in Model Parameter Identification of Solar Cells
Energies 015, 8, 7563-7581; doi:10.3390/en8087563 Aricle OPEN ACCESS energies ISSN 1996-1073 www.mdpi.com/journal/energies Applicaion of Arificial Bee Colony in Model Parameer Idenificaion of Solar Cells
More informationSwarm. Particle Swarm Optimization. Swarm. Swarm. Swarm. Swarm
Paricle Opimizaion Krzyszof Troanowski IPI PAN & UKSW, Warszawa maa r Inroducion PSO Precursors In 986 I made a compuer model of coordinaed animal moion such as bird flocks and fish schools I was based
More informationModal identification of structures from roving input data by means of maximum likelihood estimation of the state space model
Modal idenificaion of srucures from roving inpu daa by means of maximum likelihood esimaion of he sae space model J. Cara, J. Juan, E. Alarcón Absrac The usual way o perform a forced vibraion es is o fix
More informationThe field of mathematics has made tremendous impact on the study of
A Populaion Firing Rae Model of Reverberaory Aciviy in Neuronal Neworks Zofia Koscielniak Carnegie Mellon Universiy Menor: Dr. G. Bard Ermenrou Universiy of Pisburgh Inroducion: The field of mahemaics
More informationA Primal-Dual Type Algorithm with the O(1/t) Convergence Rate for Large Scale Constrained Convex Programs
PROC. IEEE CONFERENCE ON DECISION AND CONTROL, 06 A Primal-Dual Type Algorihm wih he O(/) Convergence Rae for Large Scale Consrained Convex Programs Hao Yu and Michael J. Neely Absrac This paper considers
More informationEnsamble methods: Bagging and Boosting
Lecure 21 Ensamble mehods: Bagging and Boosing Milos Hauskrech milos@cs.pi.edu 5329 Senno Square Ensemble mehods Mixure of expers Muliple base models (classifiers, regressors), each covers a differen par
More informationA DISTRIBUTED QUANTUM EVOLUTIONARY ALGORITHM WITH A NEW CYCLING OPERATOR AND ITS APPLICATION IN FRACTAL IMAGE COMPRESSION
Inernaional Journal of Arificial Inelligence & Applicaions (IJAIA), Vol.3, No., January 0 A DISTRIBUTED QUANTUM EVOLUTIONARY ALGORITHM WITH A NEW CYCLING OPERATOR AND ITS APPLICATION IN FRACTAL IMAGE COMPRESSION
More informationSTATE-SPACE MODELLING. A mass balance across the tank gives:
B. Lennox and N.F. Thornhill, 9, Sae Space Modelling, IChemE Process Managemen and Conrol Subjec Group Newsleer STE-SPACE MODELLING Inroducion: Over he pas decade or so here has been an ever increasing
More informationA Forward-Backward Splitting Method with Component-wise Lazy Evaluation for Online Structured Convex Optimization
A Forward-Backward Spliing Mehod wih Componen-wise Lazy Evaluaion for Online Srucured Convex Opimizaion Yukihiro Togari and Nobuo Yamashia March 28, 2016 Absrac: We consider large-scale opimizaion problems
More informationOn Comparison between Evolutionary Programming Network based Learning and Novel Evolution Strategy Algorithm-based Learning
Proceedings of he ICEECE December -4 (003), Dhaka, Bangladesh On Comparison beween Evoluionary Programming Nework based Learning and vel Evoluion Sraegy Algorihm-based Learning M. A. Khayer Azad, Md. Shafiqul
More informationIterative Learning Control Based on Niche Shuffled Frog Leaping Algorithm Research. Xiaohong Hao, Dongjiang Wang
nd Inernaional Conference on Auomaion, Mechanical Conrol and Compuaional Engineering (AMCCE 17) Ieraive Learning Conrol Based on Niche Shuffled Frog Leaping Algorihm Research Xiaohong Hao, Dongjiang Wang
More informationLecture 2-1 Kinematics in One Dimension Displacement, Velocity and Acceleration Everything in the world is moving. Nothing stays still.
Lecure - Kinemaics in One Dimension Displacemen, Velociy and Acceleraion Everyhing in he world is moving. Nohing says sill. Moion occurs a all scales of he universe, saring from he moion of elecrons in
More informationEnsamble methods: Boosting
Lecure 21 Ensamble mehods: Boosing Milos Hauskrech milos@cs.pi.edu 5329 Senno Square Schedule Final exam: April 18: 1:00-2:15pm, in-class Term projecs April 23 & April 25: a 1:00-2:30pm in CS seminar room
More informationMechanical Fatigue and Load-Induced Aging of Loudspeaker Suspension. Wolfgang Klippel,
Mechanical Faigue and Load-Induced Aging of Loudspeaker Suspension Wolfgang Klippel, Insiue of Acousics and Speech Communicaion Dresden Universiy of Technology presened a he ALMA Symposium 2012, Las Vegas
More informationAn introduction to the theory of SDDP algorithm
An inroducion o he heory of SDDP algorihm V. Leclère (ENPC) Augus 1, 2014 V. Leclère Inroducion o SDDP Augus 1, 2014 1 / 21 Inroducion Large scale sochasic problem are hard o solve. Two ways of aacking
More informationDEPSO: Hybrid Particle Swarm with Differential Evolution Operator
IEEE Inernaional Conference on Sysems, Man & Cyberneics (SMCC), Washingon D C, USA, 2003: 386-382 [Cooperaive Group Opimizaion] hp://www.wiomax.com/opimizaion DEPSO: Hybri Paricle Swarm wih Differenial
More informationRecent Developments In Evolutionary Data Assimilation And Model Uncertainty Estimation For Hydrologic Forecasting Hamid Moradkhani
Feb 6-8, 208 Recen Developmens In Evoluionary Daa Assimilaion And Model Uncerainy Esimaion For Hydrologic Forecasing Hamid Moradkhani Cener for Complex Hydrosysems Research Deparmen of Civil, Consrucion
More information2016 Possible Examination Questions. Robotics CSCE 574
206 Possible Examinaion Quesions Roboics CSCE 574 ) Wha are he differences beween Hydraulic drive and Shape Memory Alloy drive? Name one applicaion in which each one of hem is appropriae. 2) Wha are he
More informationSimulation-Solving Dynamic Models ABE 5646 Week 2, Spring 2010
Simulaion-Solving Dynamic Models ABE 5646 Week 2, Spring 2010 Week Descripion Reading Maerial 2 Compuer Simulaion of Dynamic Models Finie Difference, coninuous saes, discree ime Simple Mehods Euler Trapezoid
More informationRefinement of Document Clustering by Using NMF *
Refinemen of Documen Clusering by Using NMF * Hiroyuki Shinnou and Minoru Sasaki Deparmen of Compuer and Informaion Sciences, Ibaraki Universiy, 4-12-1 Nakanarusawa, Hiachi, Ibaraki JAPAN 316-8511 {shinnou,
More informationAnalyze patterns and relationships. 3. Generate two numerical patterns using AC
envision ah 2.0 5h Grade ah Curriculum Quarer 1 Quarer 2 Quarer 3 Quarer 4 andards: =ajor =upporing =Addiional Firs 30 Day 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 andards: Operaions and Algebraic Thinking
More informationEvolutionary Based Optimisation of Multivariable Fuzzy Control System of a Binary Distillation Column
2016 UKSim-AMSS 18h Inernaional Conference on Compuer Modelling and Simulaion Evoluionary Based Opimisaion of Mulivariable Fuzzy Conrol Sysem of a Binary Disillaion Column Yousif Al-Dunainawi Elecronic
More informationCHAPTER 10 VALIDATION OF TEST WITH ARTIFICAL NEURAL NETWORK
175 CHAPTER 10 VALIDATION OF TEST WITH ARTIFICAL NEURAL NETWORK 10.1 INTRODUCTION Amongs he research work performed, he bes resuls of experimenal work are validaed wih Arificial Neural Nework. From he
More informationNavneet Saini, Mayank Goyal, Vishal Bansal (2013); Term Project AML310; Indian Institute of Technology Delhi
Creep in Viscoelasic Subsances Numerical mehods o calculae he coefficiens of he Prony equaion using creep es daa and Herediary Inegrals Mehod Navnee Saini, Mayank Goyal, Vishal Bansal (23); Term Projec
More informationSection 3.5 Nonhomogeneous Equations; Method of Undetermined Coefficients
Secion 3.5 Nonhomogeneous Equaions; Mehod of Undeermined Coefficiens Key Terms/Ideas: Linear Differenial operaor Nonlinear operaor Second order homogeneous DE Second order nonhomogeneous DE Soluion o homogeneous
More information) were both constant and we brought them from under the integral.
YIELD-PER-RECRUIT (coninued The yield-per-recrui model applies o a cohor, bu we saw in he Age Disribuions lecure ha he properies of a cohor do no apply in general o a collecion of cohors, which is wha
More informationSubway stations energy and air quality management
Subway saions energy and air qualiy managemen wih sochasic opimizaion Trisan Rigau 1,2,4, Advisors: P. Carpenier 3, J.-Ph. Chancelier 2, M. De Lara 2 EFFICACITY 1 CERMICS, ENPC 2 UMA, ENSTA 3 LISIS, IFSTTAR
More informationZápadočeská Univerzita v Plzni, Czech Republic and Groupe ESIEE Paris, France
ADAPTIVE SIGNAL PROCESSING USING MAXIMUM ENTROPY ON THE MEAN METHOD AND MONTE CARLO ANALYSIS Pavla Holejšovsá, Ing. *), Z. Peroua, Ing. **), J.-F. Bercher, Prof. Assis. ***) Západočesá Univerzia v Plzni,
More informationTask-based Configuration Optimization of Modular and Reconfigurable Robots using a Multi-solution Inverse Kinematics Solver
CARV 2007 Task-based Configuraion Opimizaion of Modular and Reconfigurable Robos using a Muli-soluion Inverse Kinemaics Solver S. Tabandeh 1, C. Clark 2, W. Melek 3 Absrac: Modular and Reconfigurable Robos
More informationDimitri Solomatine. D.P. Solomatine. Data-driven modelling (part 2). 2
Daa-driven modelling. Par. Daa-driven Arificial di Neural modelling. Newors Par Dimiri Solomaine Arificial neural newors D.P. Solomaine. Daa-driven modelling par. 1 Arificial neural newors ANN: main pes
More informationThe Rosenblatt s LMS algorithm for Perceptron (1958) is built around a linear neuron (a neuron with a linear
In The name of God Lecure4: Percepron and AALIE r. Majid MjidGhoshunih Inroducion The Rosenbla s LMS algorihm for Percepron 958 is buil around a linear neuron a neuron ih a linear acivaion funcion. Hoever,
More informationEnsemble Confidence Estimates Posterior Probability
Ensemble Esimaes Poserior Probabiliy Michael Muhlbaier, Aposolos Topalis, and Robi Polikar Rowan Universiy, Elecrical and Compuer Engineering, Mullica Hill Rd., Glassboro, NJ 88, USA {muhlba6, opali5}@sudens.rowan.edu
More informationJournal of Chemical and Pharmaceutical Research, 2014, 6(5): Research Article
Available online www.jocpr.com Journal of Chemical and Pharmaceuical Research, 204, 6(5):70-705 Research Aricle ISSN : 0975-7384 CODEN(USA) : JCPRC5 Cells formaion wih a muli-objecive geneic algorihm Jun
More informationArticle Multi-Objective Optimization Algorithm Based on Sperm Fertilization Procedure (MOSFP)
Aricle Muli-Objecive Opimizaion Algorihm Based on Sperm Ferilizaion Procedure (MOSFP) Hisham A. Shehadeh, Mohd Yamani Idna ldris * and Ismail Ahmedy Deparmen of Compuer Sysem and Technology, Faculy of
More informationImproved Gene Expression Programming to Solve the Inverse Problem for Ordinary Differential Equations
Improved Gene Expression Programming o Solve he Inverse Problem for Ordinary Differenial Equaions Kangshun Li a, Yan Chen a,, Wei Li a,b, Jun He c, Yu Xue d a Souh China Agriculural Universiy, College
More informationMOMENTUM CONSERVATION LAW
1 AAST/AEDT AP PHYSICS B: Impulse and Momenum Le us run an experimen: The ball is moving wih a velociy of V o and a force of F is applied on i for he ime inerval of. As he resul he ball s velociy changes
More informationAn recursive analytical technique to estimate time dependent physical parameters in the presence of noise processes
WHAT IS A KALMAN FILTER An recursive analyical echnique o esimae ime dependen physical parameers in he presence of noise processes Example of a ime and frequency applicaion: Offse beween wo clocks PREDICTORS,
More informationMakespan Minimization of Machines and Automated Guided Vehicles Schedule Using Binary Particle Swarm Optimization
Makespan Minimizaion of Machines and Auomaed Guided Vehicles Schedule Using Binary Paricle Swarm Opimizaion Muhammad Hafidz Fazli bin Md Fauadi and Tomohiro Muraa Absrac An efficien and opimized Auomaed
More informationINVERSE RESPONSE COMPENSATION BY ESTIMATING PARAMETERS OF A PROCESS COMPRISING OF TWO FIRST ORDER SYSTEMS
Inernaional Journal of Informaion Technology and nowledge Managemen July-December 0, Volume 5, No., pp. 433-438 INVERSE RESPONSE COMPENSATION BY ESTIMATING PARAMETERS OF A PROCESS COMPRISING OF TWO FIRST
More informationResource Allocation in Visible Light Communication Networks NOMA vs. OFDMA Transmission Techniques
Resource Allocaion in Visible Ligh Communicaion Neworks NOMA vs. OFDMA Transmission Techniques Eirini Eleni Tsiropoulou, Iakovos Gialagkolidis, Panagiois Vamvakas, and Symeon Papavassiliou Insiue of Communicaions
More informationRobust estimation based on the first- and third-moment restrictions of the power transformation model
h Inernaional Congress on Modelling and Simulaion, Adelaide, Ausralia, 6 December 3 www.mssanz.org.au/modsim3 Robus esimaion based on he firs- and hird-momen resricions of he power ransformaion Nawaa,
More informationAnalytical Solutions of an Economic Model by the Homotopy Analysis Method
Applied Mahemaical Sciences, Vol., 26, no. 5, 2483-249 HIKARI Ld, www.m-hikari.com hp://dx.doi.org/.2988/ams.26.6688 Analyical Soluions of an Economic Model by he Homoopy Analysis Mehod Jorge Duare ISEL-Engineering
More informationStat 601 The Design of Experiments
Sa 601 The Design of Experimens Yuqing Xu Deparmen of Saisics Universiy of Wisconsin Madison, WI 53706, USA December 1, 2016 Yuqing Xu (UW-Madison) Sa 601 Week 12 December 1, 2016 1 / 17 Lain Squares Definiion
More informationRecursive Least-Squares Fixed-Interval Smoother Using Covariance Information based on Innovation Approach in Linear Continuous Stochastic Systems
8 Froniers in Signal Processing, Vol. 1, No. 1, July 217 hps://dx.doi.org/1.2266/fsp.217.112 Recursive Leas-Squares Fixed-Inerval Smooher Using Covariance Informaion based on Innovaion Approach in Linear
More informationA new improved filter for target tracking: compressed iterative particle filter
Vol.3, No.4, 301-306 (011) hp://d.doi.org/10.436/ns.011.34039 Naural Science A ne improved filer for arge racking: compressed ieraive paricle filer Hongbo Zhu 1 *, Hai Zhao, Dan Liu, Chunhe Song 1 Sofare
More informationWeek 1 Lecture 2 Problems 2, 5. What if something oscillates with no obvious spring? What is ω? (problem set problem)
Week 1 Lecure Problems, 5 Wha if somehing oscillaes wih no obvious spring? Wha is ω? (problem se problem) Sar wih Try and ge o SHM form E. Full beer can in lake, oscillaing F = m & = ge rearrange: F =
More informationChapter 7 Response of First-order RL and RC Circuits
Chaper 7 Response of Firs-order RL and RC Circuis 7.- The Naural Response of RL and RC Circuis 7.3 The Sep Response of RL and RC Circuis 7.4 A General Soluion for Sep and Naural Responses 7.5 Sequenial
More informationLecture 9: September 25
0-725: Opimizaion Fall 202 Lecure 9: Sepember 25 Lecurer: Geoff Gordon/Ryan Tibshirani Scribes: Xuezhi Wang, Subhodeep Moira, Abhimanu Kumar Noe: LaTeX emplae couresy of UC Berkeley EECS dep. Disclaimer:
More informationBi-Objective Task Scheduling in Cloud Computing using Chaotic Bat Algorithm
Bi-Objecive Task Scheduling in Cloud Compuing using Chaoic Ba Algorihm Feresheh Ershad Farkar Deparmen of Compuer Engineering, Tabriz Branch, Islamic Azad Universiy, Tabriz, Iran Ali Asghar Pourhaji Kazem*
More informationGeorey E. Hinton. University oftoronto. Technical Report CRG-TR February 22, Abstract
Parameer Esimaion for Linear Dynamical Sysems Zoubin Ghahramani Georey E. Hinon Deparmen of Compuer Science Universiy oftorono 6 King's College Road Torono, Canada M5S A4 Email: zoubin@cs.orono.edu Technical
More informationHall effect. Formulae :- 1) Hall coefficient RH = cm / Coulumb. 2) Magnetic induction BY 2
Page of 6 all effec Aim :- ) To deermine he all coefficien (R ) ) To measure he unknown magneic field (B ) and o compare i wih ha measured by he Gaussmeer (B ). Apparaus :- ) Gauss meer wih probe ) Elecromagne
More informationThe Production-Distribution Problem in the Supply Chain Network using Genetic Algorithm
Inernaional Journal o Applied Engineering Research ISSN 0973-4562 Volume 12, Number 23 (2017) pp. 13570-13581 Research India Publicaions. hp://www.ripublicaion.com The Producion-Disribuion Problem in he
More informationApplication of Shuffled Frog Leaping Algorithm to Long Term Generation Expansion Planning
Inernaional Journal of Compuer and Elecrical Engineering, Vol.4, o.2, April 2012 Applicaion of Shuffled Frog Leaping Algorihm o Long Term Generaion Expansion Planning M. Jadidoleslam, E. Biami,. Amiri,
More informationWATER LEVEL TRACKING WITH CONDENSATION ALGORITHM
WATER LEVEL TRACKING WITH CONDENSATION ALGORITHM Shinsuke KOBAYASHI, Shogo MURAMATSU, Hisakazu KIKUCHI, Masahiro IWAHASHI Dep. of Elecrical and Elecronic Eng., Niigaa Universiy, 8050 2-no-cho Igarashi,
More informationMulti-scale 2D acoustic full waveform inversion with high frequency impulsive source
Muli-scale D acousic full waveform inversion wih high frequency impulsive source Vladimir N Zubov*, Universiy of Calgary, Calgary AB vzubov@ucalgaryca and Michael P Lamoureux, Universiy of Calgary, Calgary
More information20. Applications of the Genetic-Drift Model
0. Applicaions of he Geneic-Drif Model 1) Deermining he probabiliy of forming any paricular combinaion of genoypes in he nex generaion: Example: If he parenal allele frequencies are p 0 = 0.35 and q 0
More informationSPH3U: Projectiles. Recorder: Manager: Speaker:
SPH3U: Projeciles Now i s ime o use our new skills o analyze he moion of a golf ball ha was ossed hrough he air. Le s find ou wha is special abou he moion of a projecile. Recorder: Manager: Speaker: 0
More informationPolicy regimes Theory
Advanced Moneary Theory and Policy EPOS 2012/13 Policy regimes Theory Giovanni Di Barolomeo giovanni.dibarolomeo@uniroma1.i The moneary policy regime The simple model: x = - s (i - p e ) + x e + e D p
More informationModeling the Dynamics of an Ice Tank Carriage
Modeling he Dynamics of an Ice Tank Carriage The challenge: To model he dynamics of an Ice Tank Carriage and idenify a mechanism o alleviae he backlash inheren in he design of he gearbox. Maplesof, a division
More informationPosition, Velocity, and Acceleration
rev 06/2017 Posiion, Velociy, and Acceleraion Equipmen Qy Equipmen Par Number 1 Dynamic Track ME-9493 1 Car ME-9454 1 Fan Accessory ME-9491 1 Moion Sensor II CI-6742A 1 Track Barrier Purpose The purpose
More informationA Meta-Heuristics Based Input Variable Selection Technique for Hybrid Electrical Energy Demand Prediction Models
A Mea-Heurisics Based Inpu Variable Selecion Technique for Hybrid Elecrical Energy Demand Predicion Models Badar ul Islam badar.up@gmail.com Perumal allagownden perumal@peronas.com.my Zuhairi Baharudin
More informationNumerical Dispersion
eview of Linear Numerical Sabiliy Numerical Dispersion n he previous lecure, we considered he linear numerical sabiliy of boh advecion and diffusion erms when approimaed wih several spaial and emporal
More informationThe Paradox of Twins Described in a Three-dimensional Space-time Frame
The Paradox of Twins Described in a Three-dimensional Space-ime Frame Tower Chen E_mail: chen@uguam.uog.edu Division of Mahemaical Sciences Universiy of Guam, USA Zeon Chen E_mail: zeon_chen@yahoo.com
More informationSupplement for Stochastic Convex Optimization: Faster Local Growth Implies Faster Global Convergence
Supplemen for Sochasic Convex Opimizaion: Faser Local Growh Implies Faser Global Convergence Yi Xu Qihang Lin ianbao Yang Proof of heorem heorem Suppose Assumpion holds and F (w) obeys he LGC (6) Given
More informationDecentralized Stochastic Control with Partial History Sharing: A Common Information Approach
1 Decenralized Sochasic Conrol wih Parial Hisory Sharing: A Common Informaion Approach Ashuosh Nayyar, Adiya Mahajan and Demoshenis Tenekezis arxiv:1209.1695v1 [cs.sy] 8 Sep 2012 Absrac A general model
More informationL07. KALMAN FILTERING FOR NON-LINEAR SYSTEMS. NA568 Mobile Robotics: Methods & Algorithms
L07. KALMAN FILTERING FOR NON-LINEAR SYSTEMS NA568 Mobile Roboics: Mehods & Algorihms Today s Topic Quick review on (Linear) Kalman Filer Kalman Filering for Non-Linear Sysems Exended Kalman Filer (EKF)
More informationKinematics and kinematic functions
Kinemaics and kinemaic funcions Kinemaics deals wih he sudy of four funcions (called kinemaic funcions or KFs) ha mahemaically ransform join variables ino caresian variables and vice versa Direc Posiion
More informationSlide03 Historical Overview Haykin Chapter 3 (Chap 1, 3, 3rd Ed): Single-Layer Perceptrons Multiple Faces of a Single Neuron Part I: Adaptive Filter
Slide3 Haykin Chaper 3 (Chap, 3, 3rd Ed): Single-Layer Perceprons CPSC 636-6 Insrucor: Yoonsuck Choe Hisorical Overview McCulloch and Pis (943): neural neworks as compuing machines. Hebb (949): posulaed
More informationθ with respect to time is
From MEC '05 Inergraing Prosheics and Medicine, Proceedings of he 005 MyoElecric Conrols/Powered Prosheics Symposium, held in Fredericon, New Brunswick, Canada, Augus 17-19, 005. A MINIMAL JERK PROSTHESIS
More informationEmbedded Systems and Software. A Simple Introduction to Embedded Control Systems (PID Control)
Embedded Sysems and Sofware A Simple Inroducion o Embedded Conrol Sysems (PID Conrol) Embedded Sysems and Sofware, ECE:3360. The Universiy of Iowa, 2016 Slide 1 Acknowledgemens The maerial in his lecure
More information1 Review of Zero-Sum Games
COS 5: heoreical Machine Learning Lecurer: Rob Schapire Lecure #23 Scribe: Eugene Brevdo April 30, 2008 Review of Zero-Sum Games Las ime we inroduced a mahemaical model for wo player zero-sum games. Any
More informationDecimal moved after first digit = 4.6 x Decimal moves five places left SCIENTIFIC > POSITIONAL. a) g) 5.31 x b) 0.
PHYSICS 20 UNIT 1 SCIENCE MATH WORKSHEET NAME: A. Sandard Noaion Very large and very small numbers are easily wrien using scienific (or sandard) noaion, raher han decimal (or posiional) noaion. Sandard
More informationOptimal Path Planning for Flexible Redundant Robot Manipulators
25 WSEAS In. Conf. on DYNAMICAL SYSEMS and CONROL, Venice, Ialy, November 2-4, 25 (pp363-368) Opimal Pah Planning for Flexible Redundan Robo Manipulaors H. HOMAEI, M. KESHMIRI Deparmen of Mechanical Engineering
More information