Описание: In this part, a detailed model of hybrid PV-CSP with thermal storage system is presented and smart optimization techniques like particle swarm optimization (PSO) and genetic algorithm (GA) are also described and used to optimally design the hybrid PV-CSP renewable energy system.
Автор: Robert G. Reynolds, Yousof Gawasmeh Название: Cultural Algorithms: Tools to Model Complex Dynamic Social Systems ISBN: 1119403081 ISBN-13(EAN): 9781119403081 Издательство: Wiley Рейтинг: Цена: 17258.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
A thorough look at how societies can use cultural algorithms to understand human social evolution
For those working in computational intelligence, developing an understanding of how cultural algorithms and social intelligence form the essential framework for the evolution of human social interaction is essential. This book, Cultural Algorithms: Tools to Model Complex Dynamic Social Systems, is the foundation of that study. It showcases how we can use cultural algorithms to organize social structures and develop socio-political systems that work.
For such a vast topic, the text covers everything from the history of the development of cultural algorithms and the basic framework with which it was organized. Readers will also learn how other nature-inspired algorithms can be expressed and how to use social metrics to assess the performance of various algorithms.
In addition to these topics, the book covers topics including:
● The CAT system including the Repast Simphony System and CAT Sample Runs
● How to problem solve using social networks in cultural algorithms with auctions
● Understanding Common Value Action to enhance Social Knowledge Distribution Systems
● Case studies on team formations
● An exploration of virtual worlds using cultural algorithms
For industry professionals or new students, Cultural Algorithms provides an impactful and thorough look at both social intelligence and how human social evolution translates into the modern world.
Автор: J. Joshua Thomas, Pinar Karagoz, B. Bazeer Ahamed, Название: Deep Learning Techniques and Optimization Strategies in Big Data Analytics ISBN: 1799811921 ISBN-13(EAN): 9781799811923 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 35897.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Many approaches have sprouted from artificial intelligence (AI) and produced major breakthroughs in the computer science and engineering industries. Deep learning is a method that is transforming the world of data and analytics. Optimization of this new approach is still unclear, however, and there's a need for research on the various applications and techniques of deep learning in the field of computing. Deep Learning Techniques and Optimization Strategies in Big Data Analytics is a collection of innovative research on the methods and applications of deep learning strategies in the fields of computer science and information systems. While highlighting topics including data integration, computational modeling, and scheduling systems, this book is ideally designed for engineers, IT specialists, data analysts, data scientists, engineers, researchers, academicians, and students seeking current research on deep learning methods and its application in the digital industry.
Автор: J. Joshua Thomas, Pinar Karagoz, B. Bazeer Ahamed, Pandian Vasant Название: Deep Learning Techniques and Optimization Strategies in Big Data Analytics ISBN: 179981193X ISBN-13(EAN): 9781799811930 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 27027.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Many approaches have sprouted from artificial intelligence (AI) and produced major breakthroughs in the computer science and engineering industries. Deep learning is a method that is transforming the world of data and analytics. Optimization of this new approach is still unclear, however, and there's a need for research on the various applications and techniques of deep learning in the field of computing. Deep Learning Techniques and Optimization Strategies in Big Data Analytics is a collection of innovative research on the methods and applications of deep learning strategies in the fields of computer science and information systems. While highlighting topics including data integration, computational modeling, and scheduling systems, this book is ideally designed for engineers, IT specialists, data analysts, data scientists, engineers, researchers, academicians, and students seeking current research on deep learning methods and its application in the digital industry.
This book will focus on the involvement of data mining and intelligent computing methods for recent advances in Biomedical applications and algorithms of nature-inspired computing for Biomedical systems. The proposed meta heuristic or nature-inspired techniques should be an enhanced, hybrid, adaptive or improved version of basic algorithms in terms of performance and convergence metrics. In this exciting and emerging interdisciplinary area a wide range of theory and methodologies are being investigated and developed to tackle complex and challenging problems.
Today, analysis and processing of data is one of big focuses among researchers community and information society. Due to evolution and knowledge discovery of natural computing, related meta heuristic or bio-inspired algorithms have gained increasing popularity in the recent decade because of their significant potential to tackle computationally intractable optimization dilemma in medical, engineering, military, space and industry fields. The main reason behind the success rate of nature inspired algorithms is their capability to solve problems. The nature inspired optimization techniques provide adaptive computational tools for the complex optimization problems and diversified engineering applications.
Tentative Table of Contents/Topic Coverage:?
- Neural Computation
- Evolutionary Computing Methods
- Neuroscience driven AI Inspired Algorithms
- Biological System based algorithms
- Hybrid and Intelligent Computing Algorithms
- Application of Natural Computing
- Review and State of art analysis of Optimization algorithms
- Molecular and Quantum computing applications
- Swarm Intelligence
- Population based algorithm and other optimizations
THE SERIES: FRONTIERS IN COMPUTATIONAL INTELLIGENCE
The series Frontiers In Computational Intelligence is envisioned to provide comprehensive coverage and understanding of cutting edge research in computational intelligence. It intends to augment the scholarly discourse on all topics relating to the advances in artifi cial life and machine learning in the form of metaheuristics, approximate reasoning, and robotics. Latest research findings are coupled with applications to varied domains of engineering and computer sciences. This field is steadily growing especially with the advent of novel machine learning algorithms being applied to different domains of engineering and technology. The series brings together leading researchers that intend to continue to advance the field and create a broad knowledge about the most recent research.
Series Editor
Dr. Siddhartha Bhattacharyya, CHRIST (Deemed to be University), Bangalore, India
Editorial Advisory Board
Dr. Elizabeth Behrman, Wichita State University, Kansas, USA
Dr. Goran Klepac
Dr. Leo Mrsic, Algebra University College, Croatia
Dr. Aboul Ella Hassanien, Cairo University, Egypt
Dr. Jan Platos, VSB-Technical University of Ostrava, Czech Republic
Dr. Xiao-Zhi Gao, University of Eastern Finland, Finland
Dr. Wellington Pinheiro dos Santos, Federal University of Pernambuco, Brazil
Автор: Balamurugan S., Vyas Ajay Kumar, Hiran Kamal Kant Название: Artificial Intelligence for Renewable Energy Systems ISBN: 1119761697 ISBN-13(EAN): 9781119761693 Издательство: Wiley Рейтинг: Цена: 25811.00 р. Наличие на складе: Поставка под заказ.
Описание: Cyril, Bishop of Alexandria (412-444), is best known as a protagonist in the christological controversy of the second quarter of the fifth century. Readers may be surprised therefore to find such polemic absent from this early work on the twelve minor prophets of the Old Testament. Cyril appears in this work as a balanced commentator, eclectic in his attitude and tolerant of alternative views.
Описание: This book presents the latest trends and approaches in artificial intelligence research and its application to intelligent systems. It discusses hybridization of algorithms, new trends in neural networks, optimisation algorithms and real-life issues related to the application of artificial methods. The book constitutes the second volume of the refereed proceedings of the Artificial Intelligence and Algorithms in Intelligent Systems of the 7th Computer Science On-line Conference 2018 (CSOC 2018), held online in April 2018.
Описание: Although recommendation systems have become a vital research area in the fields of cognitive science, approximation theory, information retrieval and management sciences, they still require improvements to make recommendation methods more effective and intelligent. <br><br><em>Intelligent Techniques in Recommendation Systems: Contextual Advancements and New Methods</em> is a comprehensive collection of research on the latest advancements of intelligence techniques and their application to recommendation systems and how this could improve this field of study.
Описание: This book presents research in artificial techniques using intelligence for energy transition, outlining several applications including production systems, energy production, energy distribution, energy management, renewable energy production, cyber security, industry 4.0 and internet of things etc.
Описание: This book focuses on the most well-regarded and recent nature-inspired algorithms capable of solving optimization problems with multiple objectives. Firstly, it provides preliminaries and essential definitions in multi-objective problems and different paradigms to solve them. It then presents an in-depth explanations of the theory, literature review, and applications of several widely-used algorithms, such as Multi-objective Particle Swarm Optimizer, Multi-Objective Genetic Algorithm and Multi-objective GreyWolf Optimizer Due to the simplicity of the techniques and flexibility, readers from any field of study can employ them for solving multi-objective optimization problem. The book provides the source codes for all the proposed algorithms on a dedicated webpage.
Автор: Bhattacharyya Siddhartha, Banerjee Pinaki, Majumdar Dipankar Название: Handbook of Research on Advanced Hybrid Intelligent Techniques and Applications ISBN: 1466694742 ISBN-13(EAN): 9781466694743 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 41580.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Conventional computational methods, and even the latest soft computing paradigms, often fall short in their ability to offer solutions to many real-world problems due to uncertainty, imprecision, and circumstantial data. Hybrid intelligent computing is a paradigm that addresses these issues to a considerable extent.The Handbook of Research on Advanced Research on Hybrid Intelligent Techniques and Applications highlights the latest research on various issues relating to the hybridization of artificial intelligence, practical applications, and best methods for implementation. Focusing on key interdisciplinary computational intelligence research dealing with soft computing techniques, pattern mining, data analysis, and computer vision, this book is relevant to the research needs of academics, IT specialists, and graduate-level students.
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