Artificial Intelligence and Computational Intelligence : International Conference, AICI 2010, Sanya, China, October 23-24, 2010, Proceedings, Part I

The 2010 International Conference on Artificial Intelligence and Computational Intelligence (AICI 2010) was held October 23–24, 2010 in Sanya, China. The AICI 2010 received 1,216 submissions from 20 countries and regions. After rigorous reviews, 105 high-quality papers were selected for publication in the AICI 2010 proceedings. The acceptance rate was 8%. The aim of AICI 2010 was to bring together researchers working in many different areas of artificial intelligence and computational intelligence to foster the exchange of new ideas and promote international collaborations. In addition to the large number of submitted papers and invited sessions, there were several internationally well-known keynote speakers. On behalf of the Organizing Committee, we thank Hainan Province Institute of Computer and Qiongzhou University for its sponsorship and logistics support. We also thank the members of the Organizing Committee and the Program Committee for their hard work. We are very grateful to the keynote speakers, invited session organizers, session chairs, reviewers, and student helpers. Last but not least, we thank all the authors and participants for their great contributions that made this conference possible. 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 Annotation This two-volume proceedings contains revised selected papers from the International Conference on Artificial Intelligence and Computational Intelligence, AICI 2010, held in Sanya, China, in October 2010. The total of 105 high-quality papers presented were carefully reviewed and selected from 1216 submissions. The topics covered are: applications of artificial intelligence; automated problem solving; automatic programming; data mining and knowledge discovering; distributed AI and agents; expert and decision support systems; fuzzy logic and soft computing; intelligent information fusion; intelligent scheduling; intelligent signal processing; machine learning; machine vision; multi-agent systems; natural language processing; neural networks; pattern recognition; robotics; applications of computational intelligence; biomedical informatics and computation; fuzzy computation; genetic algorithms; immune computation; information security; intelligent agents and systems; nature computation; particle swarm optimization; and probabilistic reasoning