Vol. 1 (2022): Hybrid Methods of BIG DATA Analysis and Applications

Hybrid Methods of Big Data Analysis and Applications

This volume includes an authoritative selection of leading international researchers and teams investigating the applicability of not one, but several methods, usually from different classes, for solving interdisciplinary problems of intellectual analysis, control, design and optimization of Big Data. The volume provides an understanding of the theory of algorithms hybridization, and also covers a wide range of applications and practical implementation problems, with due attention to modeling. The volume will be of interest to researchers in neural networks, fuzzy logic, deep learning, Data Mining as well as specialists in computer science and engineering, geoinformatics, electrical engineering, mechanical engineering and energy. The articles are arranged in five thematic topics, I) Strongly coupled (functional) hybrid methods (articles 1-3); II) Loosely coupled (functional) hybrid methods (articles 4-5); III) Transformational hybrid methods (articles 6-7); IV) Integrated methods (articles 8-12) and V) Distributed hybrid intelligent methods (article 13).

DOI: https://doi.org/10.57118/creosar/978-1-915740-01-4
Published: 2022-11-24

Full Issue

  • Preface

    Sergey Gorbachev, Boris Gusev, Victor Kuzin, Shengli Xie, Dong Yue
    ix-xviii
    DOI: https://doi.org/10.57118/creosar/978-1-915740-01-4_0

Articles