Artificial Intelligence and Computational Intelligence, Part I

Cover......Page 1
Lecture Notes in Artificial Intelligence 6319......Page 2
Artificial Intelligence
and Computational
Intelligence......Page 3
ISBN-13 9783642165290......Page 4
Preface......Page 6
Organization......Page 8
Table of Contents – Part I......Page 12
Table of Contents – Part II......Page 18
Introduction......Page 24
RBF Neural Network......Page 25
Load Forecasting Using RBF Neural Network......Page 28
Analysis......Page 30
References......Page 31
Introduction......Page 33
The System Framework......Page 35
The Zoom In/Out Operation......Page 36
The Scroll Left/Right Operation......Page 37
Experimental Results......Page 38
Conclusions......Page 39
References......Page 40
Introduction......Page 41
Introducing Ontology in the KRA Model......Page 42
Hierarchical Modeling of Physical World Based-on Ontology Classes......Page 44
References......Page 46
Introduction......Page 48
Satisfiability Degree for Transition System......Page 49
Applications......Page 53
References......Page 55
Introduction......Page 56
Control Equations......Page 57
Solution Conditions......Page 58
Optimization Process......Page 59
Results Analysis......Page 60
Conclusions......Page 62
References......Page 63
Introduction......Page 64
Preliminarily......Page 65
Semantics......Page 66
Time-Bounded Reachability......Page 67
Long-Run Average Fraction of Time......Page 69
References......Page 71
Introduction......Page 72
Model Description and Main Results......Page 73
The Stability of the Equilibrium Solution and the Periodical Solution......Page 75
References......Page 78
Introduction......Page 80
Model Description and Main Result......Page 81
The Synchronization of the Drive and Response Neural Networks......Page 83
References......Page 85
Introduction......Page 87
The Traditional Method of Magnetic Field Extrapolation......Page 88
The Classical BP Neural Network......Page 89
Experimental Design......Page 90
Train and Evaluate the Network......Page 91
References......Page 92
Introduction......Page 94
Restricted Boltzman Machine......Page 95
Sparse RBM with Gaussian Visible Units......Page 96
Differentiable Sparse Coding......Page 97
Learning the Sparse Feature from Handwritten Digits......Page 98
Learning the Sparse Deep Belief Net......Page 99
Conclusion......Page 100
References......Page 101
Introduction......Page 102
Structure of PCNN in Image Fusion......Page 103
Mathematical Model of PCNN......Page 104
Experimental Results......Page 105
References......Page 109
Introduction......Page 111
Overview of Real-Time Reliability Estimation Based on Time Series......Page 112
Principle of Dynamic Probability Model......Page 114
Dynamic Adjustable Model for Probability Distribution......Page 115
Real-Time Reliability Assessments......Page 116
Case Study......Page 117
Conclusion......Page 118
References......Page 119
Introduction......Page 120
Related Work......Page 121
Background......Page 122
Data Mining Operators......Page 123
Data Mining Execution Process Plan......Page 124
The Complexity of Data Mining Operators......Page 125
Implementation and Evaluation......Page 126
Conclusions and Future Work......Page 128
References......Page 129
Introduction......Page 130
Notation and Definition......Page 131
Enumerating Personal Centre Networks......Page 132
Mining Subgraphs(Whose Diameter Is 2)......Page 133
General Algorithm of Subgraph Mining......Page 134
Experiments......Page 136
Conclusions......Page 137
References......Page 138
Introduction......Page 139
Similarity Function......Page 141
Data Description......Page 142
Results......Page 144
Conclusion......Page 145
References......Page 146
Introduction......Page 147
Uncertain Data......Page 148
The Distance Function......Page 149
Performance Study......Page 151
Experimental Results......Page 152
Conclusions......Page 153
References......Page 154
Introduction......Page 155
Role Model......Page 156
Relation-Web Model......Page 158
Relation-Web Model Based Collaboration......Page 161
Experiment Design and Analysis......Page 163
Conclusions and Future Work......Page 166
References......Page 167
Introduction......Page 168
Agent Communication State......Page 169
MAS Asynchronous Communication Mechanism......Page 170
Agent Cooperating Principle......Page 171
Automatic Negotiation in Agent Protocol......Page 172
Conclusions......Page 174
References......Page 175
Introduction......Page 176
Reviewing and Analyzing the Principle of Infrared Automobile Exhaust Gas Analyzer......Page 177
Temperature Compensation Scheme Based on Fuzzy Inference System......Page 179
References......Page 182
Introduction......Page 184
Data Envelopment Analysis Model......Page 185
Analysis of Treatment Results......Page 187
References......Page 191
Introduction......Page 192
Description of the Algorithm about the Open-Loop IBM......Page 193
Using Differential Evolution Algorithm to Solve Fuzzy Nonlinear Programming Problems in Local Decision Units......Page 195
Description of the Algorithm about the Global Feedback IBM......Page 197
Conclusion......Page 198
References......Page 199
Introduction......Page 200
PCM Selection......Page 201
The Establishment of Membership Functions and Fuzzy Control Rules......Page 202
Different Setpoint of Fresh Air Temperature Control......Page 205
Conclusion......Page 206
References......Page 207
Introduction......Page 208
ROIs Detection Based on Variance Weighted Information Entropy......Page 209
MAP-MRF Segmentation Framework......Page 210
MRF-Based Accurate Target Extraction......Page 211
Experiments and Results......Page 213
Conclusions......Page 214
References......Page 215
Introduction......Page 216
Problems in the Conventional EKF......Page 217
Coordinate Frames......Page 218
Attitude Error Model......Page 219
Attitude Correction......Page 220
Experimentation......Page 221
References......Page 222
Introduction......Page 224
Modified Cramer-Rao Inequality......Page 225
Adaptive Input Design Algorithm......Page 227
Simulation Results......Page 229
References......Page 230
Introduction......Page 232
Probabilistic Temporal Logic of Knowledge......Page 233
Abstract Probabilistic Kripke Structure......Page 235
Property Preservation Theorem......Page 238
Model Checking for PTLK......Page 239
Dining Cryptographers Protocol......Page 241
References......Page 243
Introduction......Page 245
Coding and Active Decoding......Page 246
Crossover and Mutation Operators......Page 247
Sorting Strategy and Selection Operator on Pareto Index......Page 248
Knowledge Inherited Based on Pheromone......Page 249
Evaluate Criteria on Pareto-Optimal Solution......Page 250
Conclusion......Page 251
References......Page 252
Introduction......Page 253
Knowledge Base MDA Principles......Page 254
Application of Knowledge Base Engineering Principles to MDA......Page 255
Mappings among the Internal Models of PIM and Enterprise Meta-model......Page 256
The Main Steps of Knowledge Base MDA Approach......Page 258
References......Page 260
Introduction......Page 262
Set Up a Testing Device and Analysis of Obtained Original Electric Signals of Plants......Page 263
Autoregressive Integrated Moving Average Model......Page 264
The Time Domain Waveform of Electric Wave Signal......Page 265
The Information Fusion Forecast of Electric Signals......Page 266
References......Page 269
Introduction......Page 271
Energy Detector......Page 272
Noise Uncertainty Model......Page 273
Single Detection......Page 274
Cooperative Detection......Page 275
References......Page 277
Introduction......Page 279
Ensemble System with ``Rehearsal''......Page 280
Specification of the Rehearsal Program......Page 281
Specification of the Performance Program......Page 282
Experiments for Expressive Performance......Page 284
Related Works......Page 286
Conclusion......Page 287
References......Page 288
Introduction......Page 289
New Linear Smooth SVM......Page 290
New Kernel Smooth SVM......Page 291
NSSVM Implementation......Page 292
Numerical Experiments......Page 293
References......Page 295
Introduction......Page 296
Condition of Convergence for Generalized Consistency Method......Page 297
Experiments......Page 299
References......Page 304
Introduction......Page 305
Multi-label Support Vector Machine......Page 307
Multi-label Kernel Machine with Two-Objective Optimization......Page 308
Fast and Elitist Multi-objective Genetic Algorithm: NSGA-II......Page 309
Experiments......Page 310
References......Page 313
Introduction......Page 315
Hierarchy of the Scene Graph for Robot Workcell......Page 316
Hierarchy of AABBs for Robot Workcell......Page 317
Implementation of the Collision Detection Algorithm......Page 318
Groups Filter Manager......Page 319
Faces and Objects Intersection Manager......Page 320
Solution and Graphical Simulation Application Instance......Page 321
References......Page 322
Introduction......Page 324
Mathematical Preliminaries......Page 325
Image Moments......Page 326
The Relationship between Zero-Order Image Geometric Moment and Object Depth......Page 327
The Relationship between 2nd-Order Image Central Moments and Object Orientation......Page 328
Image Feature Selection......Page 329
Control Structure of Visual Servoing System......Page 330
Simulation Results......Page 331
References......Page 333
Introduction......Page 334
Related Works......Page 335
Large FOV Camera Model......Page 336
Setting Virtual Planes......Page 337
Computing Projection Points......Page 338
Detecting Moving Points......Page 339
Planar Scenes......Page 340
References......Page 342
Introduction......Page 344
Sparse Representation of Signals......Page 347
Visual Dictionary Learning via K-SVD......Page 348
Experiments and Results......Page 349
Future Works......Page 351
References......Page 352
Introduction......Page 354
Review of LMNND......Page 355
Modification of LMNND......Page 356
Semi-supervosed Extension of Modified LMNND......Page 357
The Algorithm......Page 358
Experiments on the AR Database......Page 359
Conclusions......Page 360
References......Page 361
Introduction......Page 362
Problem Definition......Page 363
Control Law for Agents with Different DOFs......Page 365
Control Law for the 1-DOF Agents......Page 366
Control Law for the 2-DOF Agents......Page 367
Control Law for the 3-DOF Agents......Page 368
Conclusion......Page 369
References......Page 370
Introduction......Page 372
Cooperative Design Model for Based on Multi-Agent system......Page 373
Basic Structure of Agent......Page 374
Application Agent......Page 375
Digital Certificate Management Agent......Page 376
Digital Certificate......Page 377
References......Page 379
Introduction......Page 380
FISC......Page 381
Classification......Page 382
Laplace Estimate and M-estimate......Page 383
Experimental Setting and Results......Page 384
References......Page 386
Introduction......Page 388
The Feature Selection Measure......Page 389
The Local Feature Selection and Weighing......Page 390
Experimental Setting......Page 391
Performance Measure......Page 392
The Experimental Results and Analyses......Page 393
References......Page 395
Introduction......Page 396
Computing the Gaussian Curvature......Page 397
Construction of Gaussian Curvature Co-occurrence Matrix......Page 398
Normalization and Invariants......Page 399
Experimentation Results......Page 400
References......Page 402
Introduction......Page 404
Basic Theory of ANFIS......Page 405
Bicycle Robot Modeling and ARX Model......Page 407
ANFIS Model of Bicycle Robot......Page 409
References......Page 410
Introduction......Page 412
Preliminary Estimation Using Dark Channel Prior......Page 414
Smoke Detection Based on Transmission......Page 416
Experimental Results......Page 417
Conclusion......Page 418
References......Page 419
Introduction......Page 420
Our Proposed Method: GLCM-Based Texture Histogram (HOT)......Page 422
Data Set and Training Samples......Page 424
Experiment: Based on Flicrk Cat Database......Page 425
References......Page 427
Introduction......Page 429
Time Serial Model of Rock Burst Based on Evolutionary Neural Network......Page 430
Immunized Evolutionary Programming......Page 431
New Evolutionary Neural Network......Page 433
Engineering Example......Page 434
Conclusions......Page 435
References......Page 436
Introduction......Page 437
Multilayer Perceptron Networks......Page 438
Activation Function......Page 439
Modified Activation Function......Page 440
Multilayer Perceptron Network Training......Page 441
Results......Page 442
References......Page 444
Introduction......Page 445
Kernel Methods and Kernel Trick......Page 446
Linear Mixture Model and OBSP......Page 447
OBSP in Feature Space and Its Kernel Version......Page 449
Experiment Using Synthetic Hyperspectral Data......Page 450
Experiment for Real Image......Page 452
References......Page 453
Introduction......Page 455
Mapping Function......Page 456
Training of EV-GMM Based on Principal Component Analysis......Page 457
Training of the Proposed KEV-GMM Based on Kernel Principal Component Analysis......Page 458
Unsupervised Adaptation of Trained KEV-GMM and Conversion......Page 459
Experimental Results and Discussion......Page 460
Conclusions and Future Works......Page 461
References......Page 462
Introduction......Page 463
KSVD......Page 464
Feature Extraction Based on KSVD and PCA......Page 466
Experimental Results and Analysis......Page 467
References......Page 469
Introduction......Page 471
Basic Framework......Page 472
Experimental Results......Page 474
Conclusions......Page 476
References......Page 477
Introduction......Page 478
Self-Organizing Feature Map......Page 479
Operational Summary of the SOM Algorithm......Page 480
Methods......Page 481
Results......Page 482
References......Page 483
Introduction......Page 484
Theoretical Results for NCP......Page 485
Merit Functions Methods......Page 487
Nonsmooth Newton Methods......Page 488
Interior Point Methods......Page 489
Applications and Current Trends of NCP......Page 490
References......Page 491
Introduction......Page 493
Calculation of Attractive and Repulsive Forces......Page 494
Method of Accessibility......Page 495
Experiment of Accessibility......Page 498
Simulation of Path Planning......Page 499
References......Page 500
Introduction......Page 502
Background Modeling......Page 503
The Detection and Extraction of Moving Object......Page 504
Wavelet Velocity Moments......Page 505
Standard Motion Sequence......Page 506
Evaluation and Experimental Results......Page 507
References......Page 509
Introduction......Page 511
The Triangulation Problem......Page 512
Linear Solution......Page 513
The L∞ Minimization......Page 514
Experiments......Page 515
References......Page 516
Erratum......Page 17
Erratum to: An Efficient Method for Target Extraction
of Infrared Images......Page 518
Author Index......Page 519