Computational Intelligence

• Record Nr.: UNINA9910760268403321
• Autore: Garibaldi Jonathan
• Pubbl/distr/stampa: Cham : , : Springer International Publishing AG, , 2023; ©2023
• ISBN: 3-031-46221-1
• Edizione: [1st ed.]
• Descrizione fisica: 1 online resource (263 pages)
• Collana: Studies in Computational Intelligence Series ; ; v.1119
• Altri autori (Persone): WagnerChristian; BäckThomas; LamHak-Keung; CottrellMarie; MadaniKurosh; WarwickKevin
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di contenuto: Intro -- 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.; 3.1 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.; 5.2 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&amp -- 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.; 4.3 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.