Integration of Swarm Intelligence and Artificial Neural Network

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Publisher : World Scientific
ISBN 13 : 9814280143
Total Pages : 352 pages
Book Rating : 4.8/5 (142 download)

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Book Synopsis Integration of Swarm Intelligence and Artificial Neural Network by : Satchidananda Dehuri

Download or read book Integration of Swarm Intelligence and Artificial Neural Network written by Satchidananda Dehuri and published by World Scientific. This book was released on 2011 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a new forum for the dissemination of knowledge in both theoretical and applied research on swarm intelligence (SI) and artificial neural network (ANN). It accelerates interaction between the two bodies of knowledge and fosters a unified development in the next generation of computational model for machine learning. To the best of our knowledge, the integration of SI and ANN is the first attempt to integrate various aspects of both the independent research area into a single volume.

Integration Of Swarm Intelligence And Artificial Neural Network

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Author :
Publisher : World Scientific
ISBN 13 : 9814467316
Total Pages : 352 pages
Book Rating : 4.8/5 (144 download)

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Book Synopsis Integration Of Swarm Intelligence And Artificial Neural Network by : Satchidananda Dehuri

Download or read book Integration Of Swarm Intelligence And Artificial Neural Network written by Satchidananda Dehuri and published by World Scientific. This book was released on 2011-06-08 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a new forum for the dissemination of knowledge in both theoretical and applied research on swarm intelligence (SI) and artificial neural network (ANN). It accelerates interaction between the two bodies of knowledge and fosters a unified development in the next generation of computational model for machine learning.To the best of our knowledge, the integration of SI and ANN is the first attempt to integrate various aspects of both the independent research area into a single volume.

Integration of Swarm Intelligence and Artificial Neural Network

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Author :
Publisher : World Scientific
ISBN 13 : 9814280151
Total Pages : 352 pages
Book Rating : 4.8/5 (142 download)

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Book Synopsis Integration of Swarm Intelligence and Artificial Neural Network by : Satchidananda Dehuri

Download or read book Integration of Swarm Intelligence and Artificial Neural Network written by Satchidananda Dehuri and published by World Scientific. This book was released on 2011 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a new forum for the dissemination of knowledge in both theoretical and applied research on swarm intelligence (SI) and artificial neural network (ANN). It accelerates interaction between the two bodies of knowledge and fosters a unified development in the next generation of computational model for machine learning. To the best of our knowledge, the integration of SI and ANN is the first attempt to integrate various aspects of both the independent research area into a single volume.

Swarm Intelligence and Deep Evolution

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Author :
Publisher : CRC Press
ISBN 13 : 1000579905
Total Pages : 288 pages
Book Rating : 4.0/5 (5 download)

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Book Synopsis Swarm Intelligence and Deep Evolution by : Hitoshi Iba

Download or read book Swarm Intelligence and Deep Evolution written by Hitoshi Iba and published by CRC Press. This book was released on 2022-04-14 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book provides theoretical and practical knowledge about swarm intelligence and evolutionary computation. It describes the emerging trends in deep learning that involve the integration of swarm intelligence and evolutionary computation with deep learning, i.e., deep neuroevolution and deep swarms. The study reviews the research on network structures and hyperparameters in deep learning, and attracting attention as a new trend in AI. A part of the coverage of the book is based on the results of practical examples as well as various real-world applications. The future of AI, based on the ideas of swarm intelligence and evolution is also covered. The book is an introductory work for researchers. Approaches to the realization of AI and the emergence of intelligence are explained, with emphasis on evolution and learning. It is designed for beginners who do not have any knowledge of algorithms or biology, and explains the basics of neural networks and deep learning in an easy-to-understand manner. As a practical exercise in neuroevolution, the book shows how to learn to drive a racing car and a helicopter using MindRender. MindRender is an AI educational software that allows the readers to create and play with VR programs, and provides a variety of examples so that the readers will be able to create and understand AI.

Artificial Intelligence Systems Based on Hybrid Neural Networks

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Author :
Publisher : Springer Nature
ISBN 13 : 303048453X
Total Pages : 527 pages
Book Rating : 4.0/5 (34 download)

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Book Synopsis Artificial Intelligence Systems Based on Hybrid Neural Networks by : Michael Zgurovsky

Download or read book Artificial Intelligence Systems Based on Hybrid Neural Networks written by Michael Zgurovsky and published by Springer Nature. This book was released on 2020-09-03 with total page 527 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is intended for specialists as well as students and graduate students in the field of artificial intelligence, robotics and information technology. It is will also appeal to a wide range of readers interested in expanding the functionality of artificial intelligence systems. One of the pressing problems of modern artificial intelligence systems is the development of integrated hybrid systems based on deep learning. Unfortunately, there is currently no universal methodology for developing topologies of hybrid neural networks (HNN) using deep learning. The development of such systems calls for the expansion of the use of neural networks (NS) for solving recognition, classification and optimization problems. As such, it is necessary to create a unified methodology for constructing HNN with a selection of models of artificial neurons that make up HNN, gradually increasing the complexity of their structure using hybrid learning algorithms.

Advanced Deep Learning Applications in Big Data Analytics

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Author :
Publisher : IGI Global
ISBN 13 : 1799827933
Total Pages : 351 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Advanced Deep Learning Applications in Big Data Analytics by : Bouarara, Hadj Ahmed

Download or read book Advanced Deep Learning Applications in Big Data Analytics written by Bouarara, Hadj Ahmed and published by IGI Global. This book was released on 2020-10-16 with total page 351 pages. Available in PDF, EPUB and Kindle. Book excerpt: Interest in big data has swelled within the scholarly community as has increased attention to the internet of things (IoT). Algorithms are constructed in order to parse and analyze all this data to facilitate the exchange of information. However, big data has suffered from problems in connectivity, scalability, and privacy since its birth. The application of deep learning algorithms has helped process those challenges and remains a major issue in today’s digital world. Advanced Deep Learning Applications in Big Data Analytics is a pivotal reference source that aims to develop new architecture and applications of deep learning algorithms in big data and the IoT. Highlighting a wide range of topics such as artificial intelligence, cloud computing, and neural networks, this book is ideally designed for engineers, data analysts, data scientists, IT specialists, programmers, marketers, entrepreneurs, researchers, academicians, and students.

Advances in Swarm Intelligence, Part II

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Author :
Publisher : Springer
ISBN 13 : 3642215246
Total Pages : 611 pages
Book Rating : 4.6/5 (422 download)

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Book Synopsis Advances in Swarm Intelligence, Part II by : Ying Tan

Download or read book Advances in Swarm Intelligence, Part II written by Ying Tan and published by Springer. This book was released on 2011-06-06 with total page 611 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set (LNCS 6728 and 6729) constitutes the refereed proceedings of the International Conference on Swarm Intelligence, ICSI 2011, held in Chongqing, China, in June 2011. The 143 revised full papers presented were carefully reviewed and selected from 298 submissions. The papers are organized in topical sections on theoretical analysis of swarm intelligence algorithms, particle swarm optimization, applications of pso algorithms, ant colony optimization algorithms, bee colony algorithms, novel swarm-based optimization algorithms, artificial immune system, differential evolution, neural networks, genetic algorithms, evolutionary computation, fuzzy methods, and hybrid algorithms - for part I. Topics addressed in part II are such as multi-objective optimization algorithms, multi-robot, swarm-robot, and multi-agent systems, data mining methods, machine learning methods, feature selection algorithms, pattern recognition methods, intelligent control, other optimization algorithms and applications, data fusion and swarm intelligence, as well as fish school search - foundations and applications.

Swarm-based Algorithms for Neural Network Training

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Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (124 download)

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Book Synopsis Swarm-based Algorithms for Neural Network Training by : Reginald McLean

Download or read book Swarm-based Algorithms for Neural Network Training written by Reginald McLean and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The main focus of this thesis is to compare the ability of various swarm intelligence algorithms when applied to the training of artificial neural networks. In order to compare the performance of the selected swarm intelligence algorithms both classification and regression datasets were chosen from the UCI Machine Learning repository. Swarm intelligence algorithms are compared in terms of training loss, training accuracy, testing loss, testing accuracy, hidden unit saturation, and overfitting. Our observations showed that Particle Swarm Optimization (PSO) was the best performing algorithm in terms of Training loss and Training accuracy. However, it was also found that the performance of PSO dropped considerably when examining the testing loss and testing accuracy results. For the classification problems, it was found that firefly algorithm, ant colony optimization, and fish school search outperformed PSO for testing loss and testing accuracy. It was also observed that ant colony optimization was the algorithm that performed the best in terms of hidden unit saturation.

Research Anthology on Artificial Neural Network Applications

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Author :
Publisher : IGI Global
ISBN 13 : 1668424096
Total Pages : 1575 pages
Book Rating : 4.6/5 (684 download)

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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 and published by IGI Global. This book was released on 2021-07-16 with total page 1575 pages. 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.

Hybrid Competitive Learning Method Using the Fireworks Algorithm and Artificial Neural Networks

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Author :
Publisher : Springer Nature
ISBN 13 : 303147712X
Total Pages : 112 pages
Book Rating : 4.0/5 (314 download)

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Book Synopsis Hybrid Competitive Learning Method Using the Fireworks Algorithm and Artificial Neural Networks by : Fevrier Valdez

Download or read book Hybrid Competitive Learning Method Using the Fireworks Algorithm and Artificial Neural Networks written by Fevrier Valdez and published by Springer Nature. This book was released on 2023-11-25 with total page 112 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the fields of neural networks, swarm optimization algorithms, clustering and fuzzy logic. This book describes a hybrid method with three different techniques of intelligence computation: neural networks, optimization algorithms and fuzzy logic. Within the neural network techniques, competitive neural networks (CNNs) are used, for the optimization algorithms technique, we used the fireworks algorithm (FWA), and in the area of fuzzy logic, the Type-1 Fuzzy Inference Systems (T1FIS) and the Interval Type-2 Fuzzy Inference Systems (IT2FIS) were used, with their variants of Mamdani and Sugeno type, respectively. FWA was adapted for data clustering with the goal to help of competitive neural network to find the optimal number of neurons. It is important to mention that two variants were applied to the FWA: dynamically adjust of parameters with Type-1 Fuzzy Logic (FFWA) as the first one and Interval Type-2 (F2FWA) as the second one. Subsequently, based on the outputs of the CNN and with the goal of classification data, we designed Type-1 and Interval Type-2 Fuzzy Inference Systems of Mamdani and Sugeno type. This book is intended to be a reference for scientists and engineers interested in applying a different metaheuristic or an artificial neural network in order to solve optimization and applied fuzzy logic techniques for solving problems in clustering and classification data. This book is also used as a reference for graduate courses like the following: soft computing, swarm optimization algorithms, clustering data, fuzzy classify and similar ones. We consider that this book can also be used to get novel ideas for new lines of research, new techniques of optimization or to continue the lines of the research proposed by the authors of the book.

Particle Swarm Optimization and Intelligence: Advances and Applications

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Publisher : IGI Global
ISBN 13 : 1615206671
Total Pages : 328 pages
Book Rating : 4.6/5 (152 download)

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Book Synopsis Particle Swarm Optimization and Intelligence: Advances and Applications by : Parsopoulos, Konstantinos E.

Download or read book Particle Swarm Optimization and Intelligence: Advances and Applications written by Parsopoulos, Konstantinos E. and published by IGI Global. This book was released on 2010-01-31 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book presents the most recent and established developments of Particle swarm optimization (PSO) within a unified framework by noted researchers in the field"--Provided by publisher.

Artificial Intelligence: Theory and Applications

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Publisher : Springer Nature
ISBN 13 : 3030727114
Total Pages : 353 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Artificial Intelligence: Theory and Applications by : Endre Pap

Download or read book Artificial Intelligence: Theory and Applications written by Endre Pap and published by Springer Nature. This book was released on 2021-07-15 with total page 353 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is an up-to-date collection, in AI and environmental research, related to the project ATLAS. AI is used for gaining an understanding of complex research phenomena in the environmental sciences, encompassing heterogeneous, noisy, inaccurate, uncertain, diverse spatio-temporal data and processes. The first part of the book covers new mathematics in the field of AI: aggregation functions with special classes such as triangular norms and copulas, pseudo-analysis, and the introduction to fuzzy systems and decision making. Generalizations of the Choquet integral with applications in decision making as CPT are presented. The second part of the book is devoted to AI in the geo-referenced air pollutants and meteorological data, image processing, machine learning, neural networks, swarm intelligence, robotics, mental well-being and data entry errors. The book is intended for researchers in AI and experts in environmental sciences as well as for Ph.D. students.

Designing Artificial Neural Network Using Particle Swarm Optimization

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Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (139 download)

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Book Synopsis Designing Artificial Neural Network Using Particle Swarm Optimization by : Pooria Mazaheri

Download or read book Designing Artificial Neural Network Using Particle Swarm Optimization written by Pooria Mazaheri and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural network modeling has become a special interest for many engineers and scientists to be utilized in different types of data as time series, regression, and classification and have been used to solve complicated practical problems in different areas, such as medicine, engineering, manufacturing, military, business. To utilize a prediction model that is based upon artificial neural network (ANN), some challenges should be addressed that optimal designing and training of ANN are major ones. ANN can be defined as an optimization task because it has many hyper parameters and weights that can be optimized. Metaheuristic algorithms such as swarm intelligence-based methods are a category of optimization methods that aim to find an optimal structure of ANN and to train the network by optimizing the weights. One of the commonly used swarm intelligence-based algorithms is particle swarm optimization (PSO) that can be used for optimizing ANN. In this study, we review the conducted research works on optimizing the ANNs using PSO. All studies are reviewed from two different perspectives: optimization of weights and optimization of structure and hyper parameters.

Advances in Swarm Intelligence, Part I

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Author :
Publisher : Springer
ISBN 13 : 3642215157
Total Pages : 668 pages
Book Rating : 4.6/5 (422 download)

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Book Synopsis Advances in Swarm Intelligence, Part I by : Ying Tan

Download or read book Advances in Swarm Intelligence, Part I written by Ying Tan and published by Springer. This book was released on 2011-05-31 with total page 668 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set (LNCS 6728 and 6729) constitutes the refereed proceedings of the International Conference on Swarm Intelligence, ICSI 2011, held in Chongqing, China, in June 2011. The 143 revised full papers presented were carefully reviewed and selected from 298 submissions. The papers are organized in topical sections on theoretical analysis of swarm intelligence algorithms, particle swarm optimization, applications of pso algorithms, ant colony optimization algorithms, bee colony algorithms, novel swarm-based optimization algorithms, artificial immune system, differential evolution, neural networks, genetic algorithms, evolutionary computation, fuzzy methods, and hybrid algorithms - for part I. Topics addressed in part II are such as multi-objective optimization algorithms, multi-robot, swarm-robot, and multi-agent systems, data mining methods, machine learning methods, feature selection algorithms, pattern recognition methods, intelligent control, other optimization algorithms and applications, data fusion and swarm intelligence, as well as fish school search - foundations and applications.

Swarm Intelligence Optimization

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Author :
Publisher : John Wiley & Sons
ISBN 13 : 1119778743
Total Pages : 384 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Swarm Intelligence Optimization by : Abhishek Kumar

Download or read book Swarm Intelligence Optimization written by Abhishek Kumar and published by John Wiley & Sons. This book was released on 2021-01-07 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: Resource optimization has always been a thrust area of research, and as the Internet of Things (IoT) is the most talked about topic of the current era of technology, it has become the need of the hour. Therefore, the idea behind this book was to simplify the journey of those who aspire to understand resource optimization in the IoT. To this end, included in this book are various real-time/offline applications and algorithms/case studies in the fields of engineering, computer science, information security, and cloud computing, along with the modern tools and various technologies used in systems, leaving the reader with a high level of understanding of various techniques and algorithms used in resource optimization.

Swarm Intelligence for Multi-objective Problems in Data Mining

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Publisher : Springer Science & Business Media
ISBN 13 : 3642036244
Total Pages : 296 pages
Book Rating : 4.6/5 (42 download)

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Book Synopsis Swarm Intelligence for Multi-objective Problems in Data Mining by : Carlos Coello Coello

Download or read book Swarm Intelligence for Multi-objective Problems in Data Mining written by Carlos Coello Coello and published by Springer Science & Business Media. This book was released on 2009-09-28 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this book is to collect contributions that are at the intersection of multi-objective optimization, swarm intelligence (specifically, particle swarm optimization and ant colony optimization) and data mining.

Handbook On Computational Intelligence (In 2 Volumes)

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Publisher : World Scientific
ISBN 13 : 9814675024
Total Pages : 964 pages
Book Rating : 4.8/5 (146 download)

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Book Synopsis Handbook On Computational Intelligence (In 2 Volumes) by : Plamen Parvanov Angelov

Download or read book Handbook On Computational Intelligence (In 2 Volumes) written by Plamen Parvanov Angelov and published by World Scientific. This book was released on 2016-03-18 with total page 964 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the Internet, the proliferation of Big Data, and autonomous systems, mankind has entered into an era of 'digital obesity'. In this century, computational intelligence, such as thinking machines, have been brought forth to process complex human problems in a wide scope of areas — from social sciences, economics and biology, medicine and social networks, to cyber security.The Handbook of Computational Intelligence (in two volumes) prompts readers to look at these problems from a non-traditional angle. It takes a step by step approach, supported by case studies, to explore the issues that have arisen in the process. The Handbook covers many classic paradigms, as well as recent achievements and future promising developments to solve some of these very complex problems. Volume one explores the subjects of fuzzy logic and systems, artificial neural networks, and learning systems. Volume two delves into evolutionary computation, hybrid systems, as well as the applications of computational intelligence in decision making, the process industry, robotics, and autonomous systems.This work is a 'one-stop-shop' for beginners, as well as an inspirational source for more advanced researchers. It is a useful resource for lecturers and learners alike.