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Intelligent systems : 9th Brazilian Conference, BRACIS 2020, Rio Grande, Brazil, October 20-23, 2020, Proceedings. Part I / Ricardo Cerri, Ronaldo C. Prati (eds.).

By: Contributor(s): Material type: TextTextSeries: Lecture notes in computer science ; 12319. | LNCS sublibrary. SL 7, Artificial intelligence.Publication details: Cham : Springer, 2020.Description: 1 online resource (684 pages)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783030613778
  • 3030613771
Other title:
  • BRACIS 2020
Subject(s): Genre/Form: Additional physical formats: Print version:: Intelligent Systems : 9th Brazilian Conference, BRACIS 2020, Rio Grande, Brazil, October 20-23, 2020, Proceedings, Part I.DDC classification:
  • 006.3 23
  • 006.3
LOC classification:
  • Q334
Online resources:
Contents:
Intro -- Preface -- Organization -- Contents -- Part I -- Contents -- Part II -- Evolutionary Computation, Metaheuristics, Constrains and Search, Combinatorial and Numerical Optimization -- A New Hybridization of Evolutionary Algorithms, GRASP and Set-Partitioning Formulation for the Capacitated Vehicle Routing Problem -- 1 Introduction -- 2 Mathematical Model for the Capacitated Vehicle Routing Problem -- 3 The Proposed G-DE-SPP Method -- 3.1 Overview -- 3.2 Split and Cost Functions -- 3.3 Differential Evolution (DE) -- 3.4 Evolutionary Local Search (ELS)
3.5 Greedy Randomized Adaptive Search Procedure (GRASP) -- 3.6 Set-Partitioning Problem (SPP) -- 3.7 G-DE-SPP Method -- 4 Experiments, Analysis and Results -- 5 Conclusion and Future Works -- References -- An Evolutionary Algorithm for Learning Interpretable Ensembles of Classifiers -- 1 Introduction -- 2 The Proposed Estimation of Distribution Algorithm (EDA) for Evolving Ensembles -- 2.1 Individuals (Candidate Solutions) -- 2.2 Fitness Evaluation -- 2.3 PBIL's Probabilistic Graphical Model -- 2.4 Early Stop and Termination -- 2.5 Complexity Analysis -- 3 Experimental Setup
3.1 PBIL's Hyper-parameter Optimization -- 3.2 Baseline Algorithms -- 3.3 Datasets -- 4 Experimental Results -- 5 Related Work -- 6 Conclusion and Future Work -- References -- An Evolutionary Analytic Center Classifier -- 1 Introduction -- 2 Binary Classification and Related Concepts -- 2.1 Binary Classification Problem -- 2.2 Version Space -- 2.3 Potential Function -- 2.4 Anaytic Center and Others Approximations -- 2.5 Hyperspherical Coordinates -- 3 Classifiers -- 3.1 Perceptron Model -- 3.2 Analytic Center Problem -- 3.3 KKT Conditions -- 4 Evolutionary Algorithm -- 4.1 Initial Population
4.2 Fitness Measure -- 4.3 Recombination Operator -- 4.4 Mutation Operator -- 4.5 Bias Optimization -- 5 Experiments and Results -- 6 Conclusions and Future Work -- References -- Applying Dynamic Evolutionary Optimization to the Multiobjective Knapsack Problem -- 1 Introduction -- 2 Problem Formulation -- 3 Dynamic Multiobjective Evolutionary Algorithms -- 4 Major Experiments -- 4.1 DMKP Instances with Just One Environment Change (EC = 1) -- 4.2 DMKP Instances with Two Environment Changes (EC=2) -- 5 Additional Experiments: DNSGA-II and DNSGA-II* -- 6 Conclusion -- References
Backtracking Group Search Optimization: A Hybrid Approach for Automatic Data Clustering -- 1 Introduction -- 2 Group Search Optimization -- 3 Backtracking Search Optimization -- 4 Proposed Approach: Backtracking Group Search Optimization -- 5 Experimental Analysis -- 6 Conclusions -- References -- Dynamic Software Project Scheduling Problem with PSO and Dynamic Strategies Based on Memory -- 1 Introduction -- 2 Related Works -- 3 Dynamic Software Project Scheduling Problem -- 3.1 Employees -- 3.2 Tasks -- 3.3 Solution Representation -- 3.4 Dynamic Events -- 3.5 Objective Functions
Summary: The two-volume set LNAI 12319 and 12320 constitutes the proceedings of the 9th Brazilian Conference on Intelligent Systems, BRACIS 2020, held in Rio Grande, Brazil, in October 2020. The total of 90 papers presented in these two volumes was carefully reviewed and selected from 228 submissions. The contributions are organized in the following topical section: Part I: Evolutionary computation, metaheuristics, constrains and search, combinatorial and numerical optimization; neural networks, deep learning and computer vision; and text mining and natural language processing. Part II: Agent and multi-agent systems, planning and reinforcement learning; knowledge representation, logic and fuzzy systems; machine learning and data mining; and multidisciplinary artificial and computational intelligence and applications. Due to the Corona pandemic BRACIS 2020 was held as a virtual event.
Holdings
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International conference proceedings.

Intro -- Preface -- Organization -- Contents -- Part I -- Contents -- Part II -- Evolutionary Computation, Metaheuristics, Constrains and Search, Combinatorial and Numerical Optimization -- A New Hybridization of Evolutionary Algorithms, GRASP and Set-Partitioning Formulation for the Capacitated Vehicle Routing Problem -- 1 Introduction -- 2 Mathematical Model for the Capacitated Vehicle Routing Problem -- 3 The Proposed G-DE-SPP Method -- 3.1 Overview -- 3.2 Split and Cost Functions -- 3.3 Differential Evolution (DE) -- 3.4 Evolutionary Local Search (ELS)

3.5 Greedy Randomized Adaptive Search Procedure (GRASP) -- 3.6 Set-Partitioning Problem (SPP) -- 3.7 G-DE-SPP Method -- 4 Experiments, Analysis and Results -- 5 Conclusion and Future Works -- References -- An Evolutionary Algorithm for Learning Interpretable Ensembles of Classifiers -- 1 Introduction -- 2 The Proposed Estimation of Distribution Algorithm (EDA) for Evolving Ensembles -- 2.1 Individuals (Candidate Solutions) -- 2.2 Fitness Evaluation -- 2.3 PBIL's Probabilistic Graphical Model -- 2.4 Early Stop and Termination -- 2.5 Complexity Analysis -- 3 Experimental Setup

3.1 PBIL's Hyper-parameter Optimization -- 3.2 Baseline Algorithms -- 3.3 Datasets -- 4 Experimental Results -- 5 Related Work -- 6 Conclusion and Future Work -- References -- An Evolutionary Analytic Center Classifier -- 1 Introduction -- 2 Binary Classification and Related Concepts -- 2.1 Binary Classification Problem -- 2.2 Version Space -- 2.3 Potential Function -- 2.4 Anaytic Center and Others Approximations -- 2.5 Hyperspherical Coordinates -- 3 Classifiers -- 3.1 Perceptron Model -- 3.2 Analytic Center Problem -- 3.3 KKT Conditions -- 4 Evolutionary Algorithm -- 4.1 Initial Population

4.2 Fitness Measure -- 4.3 Recombination Operator -- 4.4 Mutation Operator -- 4.5 Bias Optimization -- 5 Experiments and Results -- 6 Conclusions and Future Work -- References -- Applying Dynamic Evolutionary Optimization to the Multiobjective Knapsack Problem -- 1 Introduction -- 2 Problem Formulation -- 3 Dynamic Multiobjective Evolutionary Algorithms -- 4 Major Experiments -- 4.1 DMKP Instances with Just One Environment Change (EC = 1) -- 4.2 DMKP Instances with Two Environment Changes (EC=2) -- 5 Additional Experiments: DNSGA-II and DNSGA-II* -- 6 Conclusion -- References

Backtracking Group Search Optimization: A Hybrid Approach for Automatic Data Clustering -- 1 Introduction -- 2 Group Search Optimization -- 3 Backtracking Search Optimization -- 4 Proposed Approach: Backtracking Group Search Optimization -- 5 Experimental Analysis -- 6 Conclusions -- References -- Dynamic Software Project Scheduling Problem with PSO and Dynamic Strategies Based on Memory -- 1 Introduction -- 2 Related Works -- 3 Dynamic Software Project Scheduling Problem -- 3.1 Employees -- 3.2 Tasks -- 3.3 Solution Representation -- 3.4 Dynamic Events -- 3.5 Objective Functions

The two-volume set LNAI 12319 and 12320 constitutes the proceedings of the 9th Brazilian Conference on Intelligent Systems, BRACIS 2020, held in Rio Grande, Brazil, in October 2020. The total of 90 papers presented in these two volumes was carefully reviewed and selected from 228 submissions. The contributions are organized in the following topical section: Part I: Evolutionary computation, metaheuristics, constrains and search, combinatorial and numerical optimization; neural networks, deep learning and computer vision; and text mining and natural language processing. Part II: Agent and multi-agent systems, planning and reinforcement learning; knowledge representation, logic and fuzzy systems; machine learning and data mining; and multidisciplinary artificial and computational intelligence and applications. Due to the Corona pandemic BRACIS 2020 was held as a virtual event.

Online resource; title from PDF title page (SpringerLink, viewed December 23, 2020).

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