Proceedings of the First International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’16) (eBook)

Preface 6
Organization 8
Conference Chairs 8
Conference Vice-Chair 8
International Program Committee 8
Organizing Committee Chair 9
Local Organizing Committee 9
Sponsoring Institutions 10
Contents 11
Part IInvited Papers 16
Cognitive Reasoning Framework: Possibilities, Problems, Prospects 17
1 Introduction 17
2 Cognizing Agent: General Scheme 18
3 Modification Calculi and Modification Theories 21
3.1 Syntax 21
3.2 Semantics 22
3.3 Calculus 23
3.4 Modification Calculus 24
4 Open Problems and Promising Areas of Research 26
References 27
A Survey of Current Challenges in Manufacturing Industry and Preparation for Industry 4.0 28
1 Introduction 28
2 Industry 4.0 and Future Manufacturing 30
3 Research Methodology 31
4 Current Challenges 31
4.1 Data Integration 32
4.2 Process Flexibility 32
4.3 Security 33
5 Future Scenarios and Initial Results 34
5.1 Process Integration Within and Across Enterprise Boundaries 34
5.2 Real-Time Information Access on Hand-Held Devices 35
5.3 Predictive Maintenance 35
6 Discussion and Suggestions 36
7 Summary and Outlook 37
References 38
A Comparison of Stochastic and Fuzzy Orderings 40
1 Introduction 40
2 Stochastic and Fuzzy Orderings 41
2.1 Stochastic Orderings 42
2.2 Fuzzy Orderings 43
3 A Comparison of Histograms by the Method of the Minimum Transformations 46
4 Summary and Conclusion 48
References 49
Part IIData Mining and Knowledge Discovery in Intelligent Information and Control Systems 51
4 Time Series Forecasting Using Combination of Exponential Models and Fuzzy Techniques 52
Abstract 52
1 Introduction 52
2 Overview of Time Series Modeling Methods 53
2.1 Exponential Smoothing 54
2.2 Integration of Fuzzy Modeling and Exponential Smoothing 55
2.3 Reinhard Viertl Fuzzy Modeling 55
2.4 Fuzzy Models Implementation (DSA) 56
2.5 Combinations and Collectives of Models 56
3 Classification of Models 57
4 Experiment Results 59
5 Conclusion 60
References 60
5 Time Series Knowledge Mining Based on Temporal Network Model 62
Abstract 62
1 Introduction 63
2 Problem Statement 63
3 Temporal Network Model 65
4 Example of Temporal Network 67
5 Temporal Network Optimization 68
6 Fuzzy Interpretation of Temporal Network 70
7 Conclusions and Future Work 71
References 71
6 Methods and Algorithms of Anomaly Searching in Collections of Time Series 73
Abstract 73
1 Introduction 73
2 The Problems of Processing Time Series 74
3 Anomaly Detection Problem 75
3.1 Problem Statement 75
3.2 The Representation of Time Series 77
3.3 The Algorithm of Anomaly Detection in Sets of Time Series 78
4 Experimental Results for Anomaly Detection in Time Series 80
5 Conclusion 82
References 82
7 Web-Based System for Enterprise Performance Analysis on the Basis of Time Series Data Mining 84
Abstract 84
1 Introduction 85
2 Enterprise Performance Assessment 86
3 Time Series Analysis by the F-Transform 87
4 Time Series Decomposition 89
5 Fuzzy Tendencies Forecasting 90
6 Structure of Internet Service for Enterprise Performance Assessment 92
7 Conclusion 94
References 94
8 Feature Selection Using Semi Discrete Decomposition and Singular Value Decompositions 96
Abstract 96
1 Introduction 96
2 Dimensionality Reduction Techniques 98
2.1 Dimensionality Reduction and Feature Selection 98
2.2 Singular Value Decomposition 99
2.3 Semi-discrete Decomposition 99
3 Related Work 100
4 Features Selection Strategy 101
4.1 Updated Singular Value Decomposition 101
4.2 Semi-discrete Decomposition 102
5 Experimental Results 103
5.1 Dataset and Preprocessing 103
5.2 Applying Semi-discrete Decomposition 103
5.3 Applying Singular Value Decomposition 103
6 Discussion 104
7 Conclusion 105
Acknowledgement 105
References 105
Feature Selection by Principle Component Analysis for Mining Frequent Association Rules 107
1 Introduction 107
2 Background 108
2.1 Frequent Pattern Mining 108
2.2 Association Rules Mining 109
2.3 Singular Value Decomposition (SVD) 110
2.4 Principle Component Analysis (PCA) 110
3 Related Work 111
4 Methodology 112
4.1 Data Collections 112
4.2 Data Conversion 112
4.3 Dimension Reduction and Feature Selection by the PCA 112
4.4 Proposed Algorithm 113
4.5 Experiment 114
5 Results 114
6 Conclusion 115
References 116
10 Time Series Forecasting Based on Hybrid Neural Networks and Multiple Regression 118
Abstract 118
1 Introduction 119
2 Latest Researches in Hybrid Time Series Prediction 120
3 Neural Networks Versus Multiple Regression 121
4 Hybrid Time Series Forecasting with Using ANFIS 124
5 Conclusions and Future Work 126
References 127
11 Power Load Daily-Similarity and Time-Series Prediction Using the Selective Differential Polynomial Network 129
Abstract 129
1 Introduction 130
2 Forecasting Electrical Energy Demands 131
3 General Differential Equation Substitution 132
4 Backward Selective Differential Polynomial Neural Network 134
5 Power Demand Forecast Model Experiments 137
6 Conclusions 139
Acknowledgements 139
References 140
An EEG Classification Approach Based on Intrinsic Signal Properties and Wavelets 141
1 Introduction 141
2 Dataset 142
3 Continuous Wavelet Transform 143
4 Wavelet Marker 144
4.1 EEG Data Preprocessing 144
5 Classifiers Being Evaluated 146
6 Experiments and Results 147
6.1 Tasks 148
6.2 Experimental Settings 148
6.3 Results 148
7 Conclusion 150
References 150
13 Fuzzy c-Means Algorithm in Automatic Classification of EEG 152
Abstract 152
1 Introduction 153
2 Materials 153
3 Methods 154
3.1 Adaptive Segmentation 154
3.2 Feature Extraction 155
3.3 Fuzzy Clustering 156
4 Results 159
5 Conclusion 160
Acknowledgments 160
References 160
Part IIILogical-Algebraic Methods and Reasoning Models for Intelligent Systems: Theory and Applications 162
14 Implementation of the Argumentation System Based on Defeasible Reasoning Theory 163
Abstract 163
1 Introduction 163
2 Argumentation Theory 164
2.1 Justification Degrees in Defeasible Reasoning 167
2.2 An Algorithm for Calculating the Degrees of Justification 168
3 Implementation 169
4 Example 172
5 Conclusions 173
Acknowledgments 173
References 173
15 Paraconsistency of Argumentation Semantics for Stepping Theories of Active Logic 175
Abstract 175
1 Introduction 175
2 Logical Paraconsistency 176
3 Explosive Semantics for Theories of Stepping Active Logic 177
4 Paraconsistent Argumentation Semantics for Stepping Theories of Active Logic 180
5 Conclusions 183
References 184
16 Query Answering Over Ontologies in the Extended Allen’s Interval Logic 185
Abstract 185
1 Introduction. Main Definitions 185
2 Inference Rules and Deduction in the Logics LA+ and ?LA+ 188
3 Query Answering Over Ontologies in LA+ and ?LA+ 191
4 Conclusion 192
Acknowledgment 193
References 193
17 Logical-Algebraic Methods in Constructing Cognitive Sensors for Railway Infrastructure Intelligent Monitoring System 194
Abstract 194
1 Introduction 195
2 Monitoring Railway Infrastructure 196
3 Ambient Intelligence Architecture for Intelligent Monitoring Systems 196
4 Problem Formulation: How to Perform Cognitive Measurement by Cognitive Sensors? 198
4.1 Cognitive Measurements and Pragmatic Information Granulation 198
4.2 Cognitive Sensors and Understanding Models 201
4.3 Specification of Logical World as the Core of Cognitive Sensor 202
4.4 Pragmatic Interpretation of Logical Values for Cognitive Sensors 204
5 Interpretation of Multi-sensor Data: Bilattice Pragmatics 205
6 Algorithm of Logical-Algebraic Synthesis for Cognitive Sensors 208
References 208
18 Case-Based Reasoning Module for Intelligent Decision Support Systems 210
Abstract 210
1 Introduction 210
2 Case-Based Reasoning 211
2.1 CBR Cycle 211
2.2 Methods of Case Representation 212
2.3 Advantages and Disadvantages of CBR Methods 213
3 Method of Case Retrieval 213
3.1 Well-Known Methods for Case Retrieval 213
3.2 Structure-Mapping Theory 213
3.3 Hybrid Method for Case Retrieval 214
4 Implementation of CBR Module for IDSS 216
5 Conclusions 218
References 219
19 Automatic Document Classification Based on J.S. Mill’s Ideas 220
Abstract 220
1 Introduction 220
2 Automatic Text Classification Method Based on J.S. Mill’s Ideas 221
2.1 Notation 222
2.2 Induction 222
2.3 Analogy 224
3 Experiments 226
4 Conclusions 227
References 228
20 The Analysis of Diagrammatic Models of Workflows in Design of the Complex Automated Systems 229
Abstract 229
1 Introduction 229
2 Metamodel 231
3 Grammars 232
4 A Temporal Grammar 233
5 Checking Diagrams 236
6 Conclusions 237
References 237
Part IVOntological Engineering and Semantic Technologies 239
21 Integration and Processing of Problem-Oriented Knowledge Based on Evolutionary Procedures 240
Abstract 240
1 Introduction 241
2 Integration Problems of Knowledge in IIS Ontologies 241
3 Modified Approach to the Integration Problem 242
4 Evolutionary Approach to the Problem of Knowledge Integration 243
5 GA of Weighting Coefficients Search 245
6 Experimental Results 247
7 Conclusion 248
Acknowledgment 249
References 249
22 Design Intelligent Lifecycle Management Systems Based on Applying of Semantic Technologies 251
Abstract 251
1 Introduction 252
2 Methods of Component Design OSTIS 252
3 The Structure of the Lifecycle Management System of Complex Technical System 254
4 Conclusion 259
References 259
23 Application of Swarm Intelligence for Domain Ontology Alignment 261
Abstract 261
1 Introduction 261
2 Combined Ontology Alignment Based on Swarm Intelligence 263
3 Implementation of Ontology Alignment for the Transport System Domain 267
4 Conclusion 269
Acknowledgement 270
References 270
24 Mathematical Models of Learning Materials Estimation Based on Subject Ontology 271
Abstract 271
1 Introduction 271
2 The Subject Ontology Model 272
3 Model of Cognitive Map Learning (CML) 273
4 Testing Technique Based on Metasubject Ontology 273
4.1 Methods to Construct the CML 274
4.2 Evaluation Metrics of Students’ Metaconcept Knowledge 275
5 Conclusion 275
References 276
25 Hybridization of Fuzzy Inference and Self-learning Fuzzy Ontology-Based Semantic Data Analysis 277
Abstract 277
1 Introduction 277
2 Models and Algorithms of Ontologically-Based Data Analysis 279
2.1 Semantic Metrics for Evaluating Termhood 279
2.2 Fuzzy Ontology Model and Inference Algorithm 280
3 Implementation of Ontology Oriented Data Mining Algorithms 281
3.1 Ontology Oriented System for Extracting Terminology 281
3.2 Inference System Based on Fuzzy Ontology 282
4 Analysis of Experiments on Extraction of Terms and Inference of New Knowledge 283
4.1 Experiments on Extraction of Terms 283
4.2 Inference Based on Fuzzy Ontology 284
5 Conclusions 284
References 285
26 Models for Supporting of Problem-Oriented Knowledge Search and Processing 286
Abstract 286
1 Introduction 286
2 Agent Model of Knowledge Filter 287
3 Meta-Model of the Knowledge Filter 289
4 Case-Model of the Knowledge Filter 290
5 Experimental Research 291
6 Conclusion 292
Acknowledgments 293
References 293
27 A New Approach for Software Development in Terms of Problem-Oriented Knowledge Search and Processing 295
Abstract 295
1 Introduction 295
2 A New Approach for Problem-Oriented Knowledge Representation 296
3 Principles of Problem-Oriented Knowledge Extraction and Structuring for Object-Oriented Knowledge Database 298
4 The Software Architecture 300
5 The Developed Software 301
6 Conclusion 302
Acknowledgments 303
References 303
28 The Concept of Construction Methodology Notion for Intelligent Systems 305
Abstract 305
1 Introduction 305
2 Problem Statement 306
3 Proposed Approach 308
4 Conclusion 313
Acknowledgements 313
References 313
29 The Model of Subject-Oriented Storage of Concepts Sense for Configurable Information Systems 315
Abstract 315
1 Introduction 315
2 The Object and Subject-Oriented Concepts of Information Systems and Data Warehouses Development 317
3 The Model of Subject-Oriented Storage of Concepts Sense for Configurable Information Systems 320
4 NoSQL Implementation of Subject-Oriented Storage of Concepts Sense for Configurable Information Systems 322
5 Conclusion 323
Acknowledgement 323
References 323
Part VFuzzy Graphs, Fuzzy Networks and Fuzzy Inference for Planning and Cognitive Modelling 326
30 Coloring Method of Fuzzy Temporal Graph with the Greatest Separation Degree 327
Abstract 327
1 Introduction 327
2 Temporal Chromatic Set 328
3 The Method of Finding Temporal Chromatic Set 329
4 Conclusions 333
References 333
Temporal Coloured Petri Nets as a Tool for Modelling of Complex Dynamic Systems 335
1 Introduction 335
2 Real-Time Coloured Petri Nets with Temporal Logic Support 336
2.1 Formal Definitions and Model Example 338
2.2 Model Analysis and Verification 340
3 AL RTCP-net Computer Simulation Tools Developing 342
4 Conclusions 344
References 344
32 Fuzzy Graphs Clustering with Quality Relation Functionals in Cognitive Models 345
Abstract 345
1 Introduction 346
2 Related Work 347
3 Methods 348
4 Results 350
5 Discussion 354
5.1 Evaluation of SCAG Approach 354
6 Conclusion 355
References 355
33 Context-Based Trip Planning in Infomobility System for Public Transport 357
Abstract 357
1 Introduction 358
2 Related Work 359
3 Contextual Information in Infomobility Systems 360
4 Dynamic Multigraph for Public Transport Network 361
5 Dynamic Trip Planning Based on Multigraph and Context Management 362
6 Use Cases 364
7 Conclusions 365
References 366
34 Processing of Qualitative Data 368
Abstract 368
1 Introduction 369
2 Collecting Evidences with Axiomatic Tools 371
2.1 Fuzzy Environment 371
2.2 Ergodicity 372
3 Behavior of Linear Tactics Automaton 373
3.1 Asymptotic Optimality 375
4 Comments on Singletons 375
5 The Possibility to Measure the Level of Fuzziness 376
6 Conclusion 377
References 378
35 An Approach to the Fuzzy Inference in Logical-Type Systems with Many Inputs 379
Abstract 379
1 Introduction 379
2 The Complexity of the Fuzzy Production with N-Inputs 380
3 Statement 381
4 Calculation of Output for the Block of Rules 386
5 Conclusion 386
References 387
New Fuzzy Truth Value Based Inference Methods for Non-singleton MISO Rule-Based Systems 388
1 Introduction 388
2 Problem Statement 389
3 Zadeh Inference Method 390
4 The Inference Method Based on the Fuzzy Truth Values 391
5 Calculation of Fuzzy Output Value for the Rule Block 394
6 Conclusion 397
References 397
Part VIEvolutionary Modeling, Bionic Algorithms and Computational Intelligence 399
Feature Selection Using a Genetic Algorithm for Solar Power Prediction 400
1 Introduction 400
2 Background 401
2.1 Formalisation of the Forecasting Problem 401
2.2 Genetic Algorithm 402
2.3 Echo State Networks 403
3 Feature Selection for Solar Power Prediction 404
4 Experimental Results 405
4.1 Data Description 405
4.2 Results Analysis 406
5 Conclusions and Future Work 407
References 410
38 Hybrid Intelligent Approach to Solving the Problem of Service Data Queues 411
Abstract 411
1 Introduction 411
2 Problem Definition 413
3 Algorithm Description 414
4 Software Implementation and Experiments 418
5 Conclusion 420
Acknowledgment 420
References 420
39 Artificial Bee Colony Algorithm—A Novel Tool for VLSI Placement 422
Abstract 422
1 Introduction 422
2 VLSI Placement Problem Formulation 423
3 The Artificial Bee Algorithm for VLSI Placement Problem 424
4 Experiments 428
5 Conclusion 428
Acknowledgements 430
References 430
40 Mechanisms of Adaptive Ant Colony Behavior in Placement Problem 432
Abstract 432
1 Introduction 432
2 Fundamentals 433
3 Organizing Search Procedures Based on Ant Colony Adaptive Behavior Modeling 436
4 Experimental Evaluation 438
5 Conclusion 439
Acknowledgments 439
References 439
Multiagent Self-Organizing Interval Bacterial Colony Evolution Optimization Algorithm 440
1 Introduction 440
2 Optimal Control of Continuous Deterministic Systems 441
3 Application of Interval Optimization Technique 443
4 SOIBCEA Strategy 444
5 Applied Problems 446
6 Conclusion 449
References 449
42 Effectiveness Evaluation of Memetics and Biogeography Algorithms Using Benchmark and Trans Computational Tasks of Combinatorial Optimization 451
Abstract 451
1 Introduction 451
2 Statement of the Traveling Salesman Problem 452
3 Theory of Population Metaheuristics 453
4 Memetic Population-Based Algorithm 455
5 Biogeographic Population-Based Algorithm 455
6 Experimental Results 457
7 Conclusion and Future Work 460
Acknowledgment 460
References 460
43 Performance Investigation of Mind Evolutionary Computation Algorithm and Some of Its Modifications 462
Abstract 462
1 Introduction 462
2 Problem Statement and Simple MEC 463
3 Co-Algorithm Based on MEC 464
4 Memetic Modifications of MEC and CoMEC 466
5 Software Implementation and Numeric Experiments 467
5.1 Benchmark Functions 467
5.2 Analysis of the Results 468
5.3 Estimating the Influence of Free Parameters 469
6 Conclusions 471
References 472
Three Types of Differential Evolution Applied to the Facility Location Problem 474
1 Introduction 474
2 Single Source Capacitated Facility Location Problem 475
2.1 Nature-Inspired Metaheuristics for the Facility Location Problem 476
3 Differential Evolution 476
3.1 Self-Adaptive Differential Evolution 477
3.2 Gaussian Bare-Bones Differential Evolution 479
4 Computational Experiments 480
5 Conclusions 485
References 485
Author Index 487