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Advanced Computational Methods for Knowledge Engineering

Proceedings of the 6th International Conference on Computer Science, Applied Mathematics and Applications, ICCSAMA 2019

  • Conference proceedings
  • © 2020

Overview

Editors:
  1. Hoai An Le Thi

    1. Computer Science and Applications Department LGIPM, University of Lorraine, Metz Cedex 03, France

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  2. Hoai Minh Le

    1. Computer Science and Applications Department LGIPM, University of Lorraine, Metz Cedex 03, France

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  3. Tao Pham Dinh

    1. Laboratory of Mathematics, National Institute for Applied Sciences, Saint-Étienne-du-Rouvray Cedex, France

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  4. Ngoc Thanh Nguyen

    1. Department of Information Systems, Wroclaw University of Science and Technology, Wrocław, Poland

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  • Presents recent advances in Computational Methods for Knowledge Engineering
  • Gathers the proceedings of the 6th International Conference on Computer Science, Applied Mathematics and Applications, ICCSAMA 2019, held on Dec 19–20, 2019, in Hanoi, Vietnam
  • Explores the links between Computer Science and Applied Mathematics and presents solutions to real-world problems

Part of the book series: Advances in Intelligent Systems and Computing (AISC, volume 1121)

Included in the following conference series:

Conference proceedings info: ICCSAMA 2019.

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Table of contents (37 papers)

  1. Front Matter

    Pages i-xiv
    Download chapter PDF

  2. Nonconvex Optimization, DC Programming and DCA, and Applications

    1. Front Matter

      Pages 1-1
      Download chapter PDF

    2. A New Efficient Algorithm for Maximizing the Profit and the Compactness in Land Use Planing Problem

      • Tran Duc Quynh
      Pages 3-13

    3. A New Solution Method for a Mean-Risk Mixed Integer Nonlinear Program in Transportation Network Protection

      • Luong Vuong Le, Quang Thuan Nguyen, Duc Quynh Tran
      Pages 14-26

    4. A Novel Approach for Travel Time Optimization in Single-Track Railway Networks

      • Nguyen Quang Thuan, Nguyen Duc Anh
      Pages 27-38

    5. DCA with Successive DC Decomposition for Convex Piecewise-Linear Fitting

      • Vinh Thanh Ho, Hoai An Le Thi, Tao Pham Dinh
      Pages 39-51

    6. Solving Efficient Target-Oriented Scheduling in Directional Sensor Networks by DCA

      • Anh Son Ta, Hoai An Le Thi, Tao Pham Dinh
      Pages 52-63

    7. A Combination of CMAES-APOP Algorithm and Quasi-Newton Method

      • Duc Manh Nguyen
      Pages 64-74

    8. A Triple Stabilized Bundle Method for Constrained Nonconvex Nonsmooth Optimization

      • André Dembélé, Babacar M. Ndiaye, Adam Ouorou, Guy Degla
      Pages 75-87

    9. An Adapted Derivative-Free Optimization Method for an Optimal Design Application with Mixed Binary and Continuous Variables

      • Thi-Thoi Tran, Delphine Sinoquet, Sébastien Da Veiga, Marcel Mongeau
      Pages 88-98

    10. Numerical Technologies for Investigating Optimal Control Problems with Free Right-Hand End of Trajectories

      • Tatiana Zarodnyuk, Alexander Gornov, Anton Anikin, Pavel Sorokovikov
      Pages 99-105

    11. A Genetic Algorithm Approach for Scheduling Trains Maintenance Under Uncertainty

      • Hanyu Gu, Hue Chi Lam
      Pages 106-118

  3. Data Mining and Data Processing

    1. Front Matter

      Pages 119-119
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    2. eDTWBI: Effective Imputation Method for Univariate Time Series

      • Thi-Thu-Hong Phan, Émilie Poisson Caillault, André Bigand
      Pages 121-132

    3. Reweighted \(\ell _1\) Algorithm for Robust Principal Component Analysis

      • Hoai Minh Le, Vo Xuanthanh
      Pages 133-142

    4. A Probability-Based Close Domain Metric in Lifelong Learning for Multi-label Classification

      • Thi-Ngan Pham, Quang-Thuy Ha, Minh-Chau Nguyen, Tri-Thanh Nguyen
      Pages 143-149

    5. Applying MASI Algorithm to Improve the Classification Performance of Imbalanced Data in Fraud Detection

      • Thi-Lich Nghiem, Thi-Toan Nghiem
      Pages 150-162

    6. Learning Rough Set Based Classifiers Using Boolean Kernels

      • Hung Son Nguyen, Sinh Hoa Nguyen
      Pages 163-173

    7. Using Support Vector Machine to Monitor Behavior of an Object Based WSN System

      • Nga Ly-Tu, Qui Vo-Phu, Thuong Le-Tien
      Pages 174-185

    8. Stacking of SVMs for Classifying Intangible Cultural Heritage Images

      • Thanh-Nghi Do, The-Phi Pham, Nguyen-Khang Pham, Huu-Hoa Nguyen, Karim Tabia, Salem Benferhat
      Pages 186-196
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  1. Advanced Computational Methods for Knowledge Engineering

Keywords

About this book

This proceedings book contains 37 papers selected from the submissions to the 6th International Conference on Computer Science, Applied Mathematics and Applications (ICCSAMA 2019), which was held on 19–20 December, 2019, in Hanoi, Vietnam. The book covers theoretical and algorithmic as well as practical issues connected with several domains of Applied Mathematics and Computer Science, especially Optimization and Data Science. The content is divided into four major sections: Nonconvex Optimization, DC Programming & DCA, and Applications; Data Mining and Data Processing; Machine Learning Methods and Applications; and Knowledge Information and Engineering Systems. Researchers and practitioners in related areas will find a wealth of inspiring ideas and useful tools & techniques for their own work. 

Editors and Affiliations

  • Computer Science and Applications Department LGIPM, University of Lorraine, Metz Cedex 03, France

    Hoai An Le Thi, Hoai Minh Le

  • Laboratory of Mathematics, National Institute for Applied Sciences, Saint-Étienne-du-Rouvray Cedex, France

    Tao Pham Dinh

  • Department of Information Systems, Wroclaw University of Science and Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

Bibliographic Information

  • Book Title: Advanced Computational Methods for Knowledge Engineering

  • Book Subtitle: Proceedings of the 6th International Conference on Computer Science, Applied Mathematics and Applications, ICCSAMA 2019

  • Editors: Hoai An Le Thi, Hoai Minh Le, Tao Pham Dinh, Ngoc Thanh Nguyen

  • Series Title: Advances in Intelligent Systems and Computing

  • DOI: https://doi.org/10.1007/978-3-030-38364-0

  • Publisher: Springer Cham

  • eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)

  • Copyright Information: Springer Nature Switzerland AG 2020

  • Softcover ISBN: 978-3-030-38363-3Published: 20 December 2019

  • eBook ISBN: 978-3-030-38364-0Published: 19 December 2019

  • Series ISSN: 2194-5357

  • Series E-ISSN: 2194-5365

  • Edition Number: 1

  • Number of Pages: XIV, 426

  • Number of Illustrations: 42 b/w illustrations, 105 illustrations in colour

  • Topics: Computational Intelligence, Artificial Intelligence

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