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Metaheuristic Procedures for Training Neural Networks

2006-08-25 Business & Economics
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Release : 2006-08-25
Genre : Business & Economics
Kind : eBook
Book Rating : 165/5 ( reviews)

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Book Synopsis Metaheuristic Procedures for Training Neural Networks by : Enrique Alba

Download or read book Metaheuristic Procedures for Training Neural Networks written by Enrique Alba. This book was released on 2006-08-25. Available in PDF, EPUB and Kindle. Book excerpt: This book provides successful implementations of metaheuristic methods for neural network training. It is the first book to achieve this objective. Moreover, the basic principles and fundamental ideas given in the book will allow the readers to create successful training methods on their own. Overall, the book's aim is to provide a broad coverage of the concepts, methods, and tools of the important area of ANNs within the realm of continuous optimization.

Metaheuristics in Machine Learning: Theory and Applications

2021
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Release : 2021
Genre :
Kind : eBook
Book Rating : 435/5 ( reviews)

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Book Synopsis Metaheuristics in Machine Learning: Theory and Applications by : Diego Oliva

Download or read book Metaheuristics in Machine Learning: Theory and Applications written by Diego Oliva. This book was released on 2021. Available in PDF, EPUB and Kindle. Book excerpt: This book is a collection of the most recent approaches that combine metaheuristics and machine learning. Some of the methods considered in this book are evolutionary, swarm, machine learning, and deep learning. The chapters were classified based on the content; then, the sections are thematic. Different applications and implementations are included; in this sense, the book provides theory and practical content with novel machine learning and metaheuristic algorithms. The chapters were compiled using a scientific perspective. Accordingly, the book is primarily intended for undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics and is useful in courses on Artificial Intelligence, Advanced Machine Learning, among others. Likewise, the book is useful for research from the evolutionary computation, artificial intelligence, and image processing communities.

Advancements in Applied Metaheuristic Computing

2017-11-30 Computers
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Release : 2017-11-30
Genre : Computers
Kind : eBook
Book Rating : 527/5 ( reviews)

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Book Synopsis Advancements in Applied Metaheuristic Computing by : Dey, Nilanjan

Download or read book Advancements in Applied Metaheuristic Computing written by Dey, Nilanjan. This book was released on 2017-11-30. Available in PDF, EPUB and Kindle. Book excerpt: Metaheuristic algorithms are present in various applications for different domains. Recently, researchers have conducted studies on the effectiveness of these algorithms in providing optimal solutions to complicated problems. Advancements in Applied Metaheuristic Computing is a crucial reference source for the latest empirical research on methods and approaches that include metaheuristics for further system improvements, and it offers outcomes of employing optimization algorithms. Featuring coverage on a broad range of topics such as manufacturing, genetic programming, and medical imaging, this publication is ideal for researchers, academicians, advanced-level students, and technology developers seeking current research on the use of optimization algorithms in several applications.

Research Anthology on Artificial Neural Network Applications

2021-07-16 Computers
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Release : 2021-07-16
Genre : Computers
Kind : eBook
Book Rating : 096/5 ( reviews)

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Book Synopsis Research Anthology on Artificial Neural Network Applications by : Management Association, Information Resources

Download or read book Research Anthology on Artificial Neural Network Applications written by Management Association, Information Resources. This book was released on 2021-07-16. Available in PDF, EPUB and Kindle. Book excerpt: Artificial neural networks (ANNs) present many benefits in analyzing complex data in a proficient manner. As an effective and efficient problem-solving method, ANNs are incredibly useful in many different fields. From education to medicine and banking to engineering, artificial neural networks are a growing phenomenon as more realize the plethora of uses and benefits they provide. Due to their complexity, it is vital for researchers to understand ANN capabilities in various fields. The Research Anthology on Artificial Neural Network Applications covers critical topics related to artificial neural networks and their multitude of applications in a number of diverse areas including medicine, finance, operations research, business, social media, security, and more. Covering everything from the applications and uses of artificial neural networks to deep learning and non-linear problems, this book is ideal for computer scientists, IT specialists, data scientists, technologists, business owners, engineers, government agencies, researchers, academicians, and students, as well as anyone who is interested in learning more about how artificial neural networks can be used across a wide range of fields.

Survey of Meta-Heuristic Algorithms for Deep Learning Training

2016 Mathematics
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Release : 2016
Genre : Mathematics
Kind : eBook
Book Rating : /5 ( reviews)

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Book Synopsis Survey of Meta-Heuristic Algorithms for Deep Learning Training by : Zhonghuan Tian

Download or read book Survey of Meta-Heuristic Algorithms for Deep Learning Training written by Zhonghuan Tian. This book was released on 2016. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning (DL) is a type of machine learning that mimics the thinking patterns of a human brain to learn the new abstract features automatically by deep and hierarchical layers. DL is implemented by deep neural network (DNN) which has multi-hidden layers. DNN is developed from traditional artificial neural network (ANN). However, in the training process of DL, it has certain inefficiency due to very long training time required. Meta-heuristic aims to find good or near-optimal solutions at a reasonable computational cost. In this article, meta-heuristic algorithms are reviewed, such as genetic algorithm (GA) and particle swarm optimization (PSO), for traditional neural network's training and parameter optimization. Thereafter the possibilities of applying meta-heuristic algorithms on DL training and parameter optimization are discussed.

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