LEADER 07266nam 22004813 450 001 9910760268403321 005 20231104060223.0 010 $a3-031-46221-1 035 $a(MiAaPQ)EBC30853365 035 $a(Au-PeEL)EBL30853365 035 $a(EXLCZ)9928652798600041 100 $a20231104d2023 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aComputational Intelligence 205 $a1st ed. 210 1$aCham :$cSpringer International Publishing AG,$d2023. 210 4$d©2023. 215 $a1 online resource (263 pages) 225 1 $aStudies in Computational Intelligence Series ;$vv.1119 311 08$aPrint version: Garibaldi, Jonathan Computational Intelligence Cham : Springer International Publishing AG,c2023 9783031462207 327 $aIntro -- Preface -- Organization -- Contents -- Evolutionary Optimization of Roles for Access Control in Enterprise Resource Planning Systems -- 1 Introduction -- 2 Problem Description -- 3 Related Work -- 4 The AddRole-EA -- 4.1 Presentation of the AddRole-EA -- 4.2 Evaluation -- 5 New Mutation Methods for the AddRole-EA -- 5.1 (M1): Intersection of Permission Sets -- 5.2 (M2): Permission Set Setminus Union of Permissions of Roles -- 5.3 (M3): Splitting of Roles -- 5.4 (M4): Permission Set of a User -- 5.5 (M5): Merging of Roles -- 6 Evaluation -- 7 Conclusion and Future Works -- References -- Behavioural Modelling of Digital Circuits in SystemVerilog Using Grammatical Evolution -- 1 Introduction -- 2 Background -- 2.1 Related Work -- 2.2 Grammatical Evolution -- 3 Experimental Design -- 3.1 Benchmark Problems -- 4 Results and Discussions -- 4.1 Success Rate -- 4.2 Grammar Design -- 4.3 Higher Abstraction Levels -- 4.4 Impact of Initialization Schemes on Circuit Design Benchmark Problems -- 5 Conclusion and Future Work -- References -- Crossover in Cartesian Genetic Programming: Evaluation of Two Phenotypic Methods -- 1 Introduction -- 2 Preliminaries -- 2.1 Cartesian Genetic Programming -- 2.2 Advanced Crossover Operators for CGP -- 3 Review and Motivation -- 3.1 Previous Work on Crossover in CGP -- 3.2 Motivation for a New Evaluation -- 3.3 Formulation of Hypotheses -- 4 Evaluation -- 4.1 Experimental Setup -- 4.2 Benchmarks -- 4.3 Meta-optimization -- 4.4 Experiments -- 5 Discussion and Analysis -- 5.1 Analysis of Hypotheses -- 6 Conclusion and Future Work -- References -- An Information Granulation Approach Through m-Grams for Text Classification -- 1 Introduction -- 2 The Text Categorization System -- 2.1 Background and Conceptual Framework -- 2.2 Overview of the Text Categorization System -- 3 Enhancing the System Performance. 327 $a3.1 Performance Exploration Strategy -- 4 Simulation Settings and Results -- 4.1 Experimental Setup -- 4.2 Performance Evaluation -- 4.3 Experimental Results -- 5 Conclusions -- References -- Recent Research Topics in Evolutionary Multiobjective Optimization: A Personal Perspective -- 1 Introduction -- 2 Basic Concepts -- 3 Recent Research Topics -- 3.1 Algorithms -- 3.2 Scalability -- 3.3 Computationally Expensive MOPs -- 3.4 Hyper-Heuristics -- 4 Challenges -- 5 Conclusions -- References -- A Multi-objective Optimization Approach for the Capacitated Vehicle Routing Problem with Time Windows (CVRPTW) -- 1 Introduction -- 2 Formal Model -- 3 Various Approaches to the Problem -- 4 Our Approach -- 4.1 Setting the Input Parameters -- 4.2 Building the Initial Population Using a Greedy Approach -- 4.3 Tweak Operator -- 4.4 Recombination Operator -- 4.5 Fuse Operator: Naïve Merge -- 4.6 Tuning Operator -- 4.7 SPEA2 Fitness Computation and Archive Construction -- 4.8 SPEA2 Algorithm -- 4.9 Evolve Operator -- 5 Summary of Our Experimental Results -- 5.1 Hyperparameters Tuning -- 5.2 Results Analysis -- 6 Conclusions -- References -- Risk Assessment Modeling Based on a Graded Fuzzy Concept Lattice -- 1 Introduction -- 2 Background -- 2.1 Lattices and Quantales -- 2.2 Fuzzy Sets -- 2.3 Fuzzy Relations -- 3 Concept Lattices Vs. Preconcept Lattices -- 3.1 Preconcepts and Preconcept Lattices -- 3.2 Operators R "3222378 and R "3223379 on [SPSDOLLAR4DOLLARSPS]-Powersets and Fuzzy Concept Lattices -- 3.3 Concepts and Concept Lattices -- 4 Graded Concept Lattices -- 4.1 Measure of Inclusion of L-Fuzzy Sets -- 4.2 Conceptuality Degree of a Fuzzy Preconcept -- 4.3 Examples of Evaluation of Conceptuality Degree for Fuzzy Preconcepts -- 4.4 Graded Preconcept Lattices -- 5 Risk Assessment and Fuzzy Preconcept Lattices -- 5.1 Risk Assessment Model. 327 $a5.2 Assessment of Possible Covid-19 Impact on the Healthcare System in Latvia -- 6 Conclusions -- References -- Improving Simulation Realism in Developing a Fuzzy Modular Autonomous Driving System for Electric Boats -- 1 Introduction -- 2 Proposed Autonomous Driving System Architecture -- 2.1 LLC Design: Motion Control -- 2.2 Navigation Pipeline -- 2.3 Boat Avoidance Pipeline -- 2.4 Docks Avoidance Pipeline -- 2.5 High Level of Control: Pipeline Selection -- 3 Evaluation Metrics -- 3.1 Fish Schooling Behavior Inspired Reward Function -- 3.2 Stall, Collision and Success Probabilities -- 4 Simulation Results -- 4.1 Phase 1 -- 4.2 Phase 2 -- 4.3 Phase 3 -- 5 Conclusions -- References -- Facing Graph Classification Problems by a Multi-agent Information Granulation Approach -- 1 Introduction -- 2 Related Works -- 3 Complex and Multi-agent Systems -- 4 Graph E-ABC -- 5 Graph Neural Network -- 6 Experimental Results -- 7 Discussions and Conclusions -- References -- One-Shot Identification with Different Neural Network Approaches -- 1 Introduction -- 1.1 Related Work -- 2 Approach -- 2.1 Classic Convolutional Neural Network with Merged Images -- 2.2 Siamese Networks -- 2.3 Siamese Network with Capsules -- 3 Experimental Results -- 3.1 Industrial Application -- 3.2 Results on SmallNORB Dataset -- 3.3 Results on AT& -- T Database of Faces -- 4 Conclusion and Future Prospects -- References -- Evaluation of Gated Recurrent Neural Networks for Embedded Systems Applications -- 1 Introduction -- 2 State of the Art -- 2.1 Emergence of RNNs -- 2.2 Training with Back-Propagation -- 2.3 Applications of RNNs in Embedded Systems (ESs) -- 3 Basic RNN Cells Description -- 3.1 LSTM Cell -- 3.2 GRU Cell -- 3.3 MGU Cell -- 3.4 STAR Cell -- 4 Building Deep RNN Structures -- 4.1 Discussion on Basic Cells Complexity -- 4.2 Bi-Directional Variants. 327 $a4.3 Stacking Recurrent Cells -- 5 Experiments and Results -- 5.1 Test Cases Overview -- 5.2 Pytorch Implementation -- 5.3 Our Implementation -- 5.4 Performance Results -- 6 Conclusions and Perspectives -- References -- Author Index. 410 0$aStudies in Computational Intelligence Series 700 $aGaribaldi$b Jonathan$01438298 701 $aWagner$b Christian$0880834 701 $aBäck$b Thomas$0351375 701 $aLam$b Hak-Keung$0762991 701 $aCottrell$b Marie$0105006 701 $aMadani$b Kurosh$0929700 701 $aWarwick$b Kevin$01438299 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910760268403321 996 $aComputational Intelligence$93599591 997 $aUNINA