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Mohammadian M., Sarker R.A., Yao X. — Computational intelligence in control
Mohammadian M., Sarker R.A., Yao X. — Computational intelligence in control



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Название: Computational intelligence in control

Авторы: Mohammadian M., Sarker R.A., Yao X.

Аннотация:

The problem of controlling uncertain dynamic systems, which are subject to external disturbances, uncertainty and sheer complexity is of considerable interest in computer science, Operations Research and Business domains. The application of intelligent systems has been found useful in problems when the process is either difficult to model or difficult to solve by conventional methods. Intelligent systems have attracted increasing attention in recent years for solving many complex problems. Computational Intelligence in Control will be a repository for the theory and applications of intelligent systems techniques in modelling control and automation.


Язык: en

Рубрика: Computer science/AI, knowledge/

Статус предметного указателя: Готов указатель с номерами страниц

ed2k: ed2k stats

Год издания: 2003

Количество страниц: 336

Добавлена в каталог: 20.11.2005

Операции: Положить на полку | Скопировать ссылку для форума | Скопировать ID
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Предметный указатель
Adaptive landscapes      288
Adaptive learning      130
Agent      169
Agricultural production      184
AIDA      149
Aircraft cockpit      149
Airplane system technology      150
Ambient vibration testing      307
Ant colony      171
Approach by Localization (AL)      241
artificial intelligence      170
Artificial Life modeling approach      185
Artificial neural networks (ANN)      197
Attainment surfaces      222
ATTAS      149
Autonomous agents      168 170
Bactrocera oleae      184
Bayesian agencies      168
Bayesian agents      168
Bayesian networks      168 169
Behavior networks      170
Binary alphabet      238
Binary string      142
Box-pushing controller      107
BTGP      280
Cartesian workspace      71
Chaos theory      215
Civil engineering structures      304
Classic coding      238
Classical Evolution Strategies (CES)      264
Classification      200
Climatic data      184
Clustering      200
Clusters      175
Complex control systems      122
Complex interaction protocols      170
Computational Intelligence      169
Computer simulation      268
Control vector      44
Controlled Evolutionary Approach (CEA)      233 243
Conventional control difficult      43
Coverage metrics      222
Critical machine      234
Cross-Spectral Density (CSD)      302 313
Crossover      287
Cycle-cutset conditioning      175
Cycle-cutsets      175
Damage detection      137
Design wind load      302
Differential Evolution (DE)      219 222
Discrete Fourier transform (DFT)      312
Doping      118
Ecological system analysis      185
Ensemble learning system      2
Epistasis variance      286
Epoch      7
Error ratio      222
Evolution Strategies (ES)      263
Evolution strategies algorithms      264
Evolutionary Algorithm (EAs)      88 104 110 116 218 219 280
Evolutionary biology      280
Evolutionary computation context      280
Evolutionary programming (EP)      263
Existence of variation      281
Fast Evolution Strategies (FES)      265
Fast Fourier transform (FFT)      302 312
Finite Element (FE)      136
Fitter mutants      286
Flight simulation      150
Flight Training Devices (FTDs)      149
Forced vibration methods      302
Forced vibration testing      306
Fourier transform      311
Frequency Response Function (FRF)      302
Fuzzy amalgamation      89
Fuzzy logic      122
Fuzzy logic application      88
Fuzzy logic controllers      89
Fuzzy logic systems      122
Fuzzy pilot      151
Fuzzy rule-based systems      197
General regression      43
General Regression Network (GRNN)      43
Generational distance      222
Generic neural network      25
Genetic algorithm (GA)      123 137 238 263
Genetic diversity      283
Genetic drift      285
Genetic manipulations      246
Genetic Programming System (BTGP)      287
Genetic reinforcement learning      106
Genetically Modified Organisms (GMO)      246
Genotype      138
German Aerospace Center (DLR)      149
Glide slope      154
Global Combined Discrete Recombination      268
Global External (GE)      112
Global Internal (Gl)      112
Global semantics      173
Golden unit      23
Ground based simulators      150
Gust Response Factors (GRF)      304
Heat unit accumulation concept      187
Helicopter control      43
Hidden periodicities      312
Hierarchical Fuzzy Logic Systems      126
Human decision maker      219
ILS tracking task      151
Impact tests      307
Information retrieval      279
Intelligent components      168
Intelligent control systems      43
Interaction      170
Inverse analyses      136
Inverse system identification      137
Job-shop Scheduling Problem (JSP)      233
Join-tree propagation      175
Kheperatype      107
Knowledge base (KB)      88
Knowledge space      23
Lay-up design      143
Learning      2
Local External (LE)      112
Local Internal (LI)      112
Local semantics      173
Lyapunov stability theory      71
Machine learning      199
Main rotor      45
Makespan      234
Malaysian Wind Code      310
Man/Machine Interface (MMI)      148
Mapping Genetic Algorithm (MGA)      280 287
Mixtures-of-Experts(ME)      4
Model      198
Model tree      208
Most Probable Explanation (MPE)      174
Multiobjective Evolutionary Algorithms (MEAs)      218
Multiobjective Optimization Problems (MOPs)      218
Mutation      281
Mutation variance      284
Negative correlation learning      5
Neighboring neurons      73
Neural computation      23
Neural controller configuration      114
Neural network      42 104
Neural network methods      2 70
Neural variables      22
Neutral mutants      286
Next-generation      168
NN-based controllers      44
Noise      263
Nominal data      200
Non-dominated Sorting Genetic Algorithms (NSGA)      221
Non-linear dynamics      215
Non-serial dynamic programming algorithms      175
Nonstationary environment      69
Nonstationary statistics      54
Olive fly’s life cycle      186
Olive trees      184
Operational Research (OR)      219
Output vector      44
Parameter sensitivity      82
Pareto Archived Evolution Strategy (PAES)      222
Pest management      183
Phenotype      138
Phenotypes (decision trees)      287
Phenotypic diversity      284
Pilot model approach      151
Plasmopara viticola      185
Poikilothermic animal      188
Population dynamics analysis methods      184
Power spectral density (PSD)      302 312 315
Pre-imaginary phases      186
probability      28
Pruning      209
Pull back tests      307
push      164
Radial-Basis Function (RBF) neural network      205
Ramped growth      287
Random Sampling Evolutionary Algorithm (RAND)      220
Randomized algorithms      22
Real-time path planning      69
Real-time trajectory      70
Regression tree      208
Robot soccer system      89
Robot’s proximity sensors      107
Robust Evolution Strategies (RES)      265
Robustness index      27
Root locus      47
Scheduling algorithm      242
Schemata generation algorithm      242
Sequential training methods      3
Shaker tests      307
Simple agents      171
Simulation models      198
Single Objective Evolutionary Algorithm (SOEA)      220
Single sampling line      223
Spectrum analysis      312
Splines      205
SPREAD      222
State vector      44
Statistical learning theory      200
Strength Pareto Evolutionary Algorithm (SPEA)      219
Strength-to-weight ratio      143
Support vector machine (SVM)      200
Task instances      111
Thrust increase      164
Thrust reduction      164
Training set      201
Travelling salesman problem      239
Turbulence Intensities (Tl)      302 313
Uncertain environments      176
Variation      281
Vector Evaluated Genetic Algorithm (VEGA)      220
Verification set      201
Vibration testing      305
Wind speed      309
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