Applied Genetic Algorithm and Its Variants

by Nilanjan Dey
Applied Genetic Algorithm and Its Variants
Author: Nilanjan Dey
Publisher: Springer Nature
Total Pages: 254
Release: 2023-07-01
Genre: Technology & Engineering
ISBN: 9819934281
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This book provides fundamental concepts related to various types of genetic algorithms and practical applications in various domains such as medical imaging, manufacturing, and engineering design. The book discusses genetic algorithms which are used to solve a variety of optimization problems. The genetic algorithms are demonstrated to offer reliable search in complex spaces. The book presents high-quality research work by academics and researchers which is useful for young researchers and students.

Genetic Algorithm Essentials

by Oliver Kramer
Genetic Algorithm Essentials
Author: Oliver Kramer
Publisher: Springer
Total Pages: 94
Release: 2017-01-07
Genre: Technology & Engineering
ISBN: 331952156X
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This book introduces readers to genetic algorithms (GAs) with an emphasis on making the concepts, algorithms, and applications discussed as easy to understand as possible. Further, it avoids a great deal of formalisms and thus opens the subject to a broader audience in comparison to manuscripts overloaded by notations and equations. The book is divided into three parts, the first of which provides an introduction to GAs, starting with basic concepts like evolutionary operators and continuing with an overview of strategies for tuning and controlling parameters. In turn, the second part focuses on solution space variants like multimodal, constrained, and multi-objective solution spaces. Lastly, the third part briefly introduces theoretical tools for GAs, the intersections and hybridizations with machine learning, and highlights selected promising applications.

Applied Genetic Algorithm and Its Variants

by Nilanjan Dey
Applied Genetic Algorithm and Its Variants
Author: Nilanjan Dey
Publisher:
Total Pages: 0
Release: 2023
Genre:
ISBN: 9789819934294
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This book provides fundamental concepts related to various types of genetic algorithms and practical applications in various domains such as medical imaging, manufacturing, and engineering design. The book discusses genetic algorithms which are used to solve a variety of optimization problems. The genetic algorithms are demonstrated to offer reliable search in complex spaces. The book presents high-quality research work by academics and researchers which is useful for young researchers and students.

Applications of Flower Pollination Algorithm and its Variants

by Nilanjan Dey
Applications of Flower Pollination Algorithm and its Variants
Author: Nilanjan Dey
Publisher: Springer Nature
Total Pages: 239
Release: 2021-03-17
Genre: Technology & Engineering
ISBN: 9813361042
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This book presents essential concepts of traditional Flower Pollination Algorithm (FPA) and its recent variants and also its application to find optimal solution for a variety of real-world engineering and medical problems. Swarm intelligence-based meta-heuristic algorithms are extensively implemented to solve a variety of real-world optimization problems due to its adaptability and robustness. FPA is one of the most successful swarm intelligence procedures developed in 2012 and extensively used in various optimization tasks for more than a decade. The mathematical model of FPA is quite straightforward and easy to understand and enhance, compared to other swarm approaches. Hence, FPA has attracted attention of researchers, who are working to find the optimal solutions in variety of domains, such as N-dimensional numerical optimization, constrained/unconstrained optimization, and linear/nonlinear optimization problems. Along with the traditional bat algorithm, the enhanced versions of FPA are also considered to solve a variety of optimization problems in science, engineering, and medical applications.

Applications of Cuckoo Search Algorithm and its Variants

by Nilanjan Dey
Applications of Cuckoo Search Algorithm and its Variants
Author: Nilanjan Dey
Publisher: Springer Nature
Total Pages: 328
Release: 2020-06-23
Genre: Technology & Engineering
ISBN: 9811551634
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This book highlights the basic concepts of the CS algorithm and its variants, and their use in solving diverse optimization problems in medical and engineering applications. Evolutionary-based meta-heuristic approaches are increasingly being applied to solve complicated optimization problems in several real-world applications. One of the most successful optimization algorithms is the Cuckoo search (CS), which has become an active research area to solve N-dimensional and linear/nonlinear optimization problems using simple mathematical processes. CS has attracted the attention of various researchers, resulting in the emergence of numerous variants of the basic CS with enhanced performance since 2019.

Advances in Computational Intelligence. MICAI 2023 International Workshops

by Hiram Calvo
Advances in Computational Intelligence. MICAI 2023 International Workshops
Author: Hiram Calvo
Publisher: Springer Nature
Total Pages: 476
Release: 2024-01-19
Genre: Computers
ISBN: 303151940X
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This conference LNAI 14502 volume constitutes the workshop proceedings of 22nd Mexican International Conference on Artificial Intelligence, held in November 2023 in Mérida, Yucatán, México. The total of 34 papers presented in this volume was carefully reviewed and selected from 54 submissions. The proceedings of MICAI 2023 workshops are structured into three sections: – WILE 2023: 16th Workshop on Intelligent Learning Environments – HIS 2023: 16th Workshop of Hybrid Intelligent Systems – CIAPP 2023: 5th Workshop on New Trends in Computational Intelligence and Applications

Feature Engineering and Selection

by Max Kuhn
Feature Engineering and Selection
Author: Max Kuhn
Publisher: CRC Press
Total Pages: 266
Release: 2019-07-25
Genre: Business & Economics
ISBN: 1351609467
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The process of developing predictive models includes many stages. Most resources focus on the modeling algorithms but neglect other critical aspects of the modeling process. This book describes techniques for finding the best representations of predictors for modeling and for nding the best subset of predictors for improving model performance. A variety of example data sets are used to illustrate the techniques along with R programs for reproducing the results.