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| Author | : Jyotsna Kumar Mandal |
| Publisher | : |
| Total Pages | : 674 |
| Release | : 2016-05-19 |
| Genre | : |
| ISBN | : 9781668428146 |
| Author | : Mandal, Jyotsna Kumar |
| Publisher | : IGI Global |
| Total Pages | : 1015 |
| Release | : 2016-05-25 |
| Genre | : Computers |
| ISBN | : 1522500596 |
Nature-inspired computation is an interdisciplinary topic area that connects the natural sciences to computer science. Since natural computing is utilized in a variety of disciplines, it is imperative to research its capabilities in solving optimization issues. The Handbook of Research on Natural Computing for Optimization Problems discusses nascent optimization procedures in nature-inspired computation and the innovative tools and techniques being utilized in the field. Highlighting empirical research and best practices concerning various optimization issues, this publication is a comprehensive reference for researchers, academicians, students, scientists, and technology developers interested in a multidisciplinary perspective on natural computational systems.
| Author | : Shandilya, Shishir K. |
| Publisher | : IGI Global |
| Total Pages | : 627 |
| Release | : 2017-03-10 |
| Genre | : Computers |
| ISBN | : 1522521291 |
Soft computing and nature-inspired computing both play a significant role in developing a better understanding to machine learning. When studied together, they can offer new perspectives on the learning process of machines. The Handbook of Research on Soft Computing and Nature-Inspired Algorithms is an essential source for the latest scholarly research on applications of nature-inspired computing and soft computational systems. Featuring comprehensive coverage on a range of topics and perspectives such as swarm intelligence, speech recognition, and electromagnetic problem solving, this publication is ideally designed for students, researchers, scholars, professionals, and practitioners seeking current research on the advanced workings of intelligence in computing systems.
| Author | : Florea, Andrei George |
| Publisher | : IGI Global |
| Total Pages | : 119 |
| Release | : 2017-03-10 |
| Genre | : Computers |
| ISBN | : 1522522816 |
Developments in bio-inspired computation have impacted multiple fields and created opportunities for new applications. In recent years, these techniques have been increasingly integrated into robotic systems. Membrane Computing for Distributed Control of Robotic Swarms: Emerging Research and Opportunities is an innovative reference source for the latest perspectives on biologically-inspired computation techniques for robot design and control. Highlighting a range of pivotal topics such as software engineering, simulation tools, and robotic security, this book is ideally designed for researchers, academics, students, and practitioners interested in the role of membrane computing in mobile robots.
| Author | : Mo, Hongwei |
| Publisher | : IGI Global |
| Total Pages | : 634 |
| Release | : 2009-04-30 |
| Genre | : Computers |
| ISBN | : 1605663115 |
"This book offers new ideas and recent developments in Natural Computing, especially on artificial immune systems"--Provided by publisher.
| Author | : Aditya Khamparia |
| Publisher | : Walter de Gruyter GmbH & Co KG |
| Total Pages | : 201 |
| Release | : 2021-02-08 |
| Genre | : Computers |
| ISBN | : 311067615X |
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
| Author | : Frank Neumann |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 215 |
| Release | : 2010-11-04 |
| Genre | : Mathematics |
| ISBN | : 3642165443 |
Bioinspired computation methods such as evolutionary algorithms and ant colony optimization are being applied successfully to complex engineering problems and to problems from combinatorial optimization, and with this comes the requirement to more fully understand the computational complexity of these search heuristics. This is the first textbook covering the most important results achieved in this area. The authors study the computational complexity of bioinspired computation and show how runtime behavior can be analyzed in a rigorous way using some of the best-known combinatorial optimization problems -- minimum spanning trees, shortest paths, maximum matching, covering and scheduling problems. A feature of the book is the separate treatment of single- and multiobjective problems, the latter a domain where the development of the underlying theory seems to be lagging practical successes. This book will be very valuable for teaching courses on bioinspired computation and combinatorial optimization. Researchers will also benefit as the presentation of the theory covers the most important developments in the field over the last 10 years. Finally, with a focus on well-studied combinatorial optimization problems rather than toy problems, the book will also be very valuable for practitioners in this field.
| Author | : Hrnjica, Bahrudin |
| Publisher | : IGI Global |
| Total Pages | : 310 |
| Release | : 2018-07-06 |
| Genre | : Medical |
| ISBN | : 1522560068 |
Data is more valuable than ever in the twenty-first century, and tremendous amounts of data are being generated every second. With a fast-growing information industry, engineers are required to develop new tools and techniques that increase human capabilities of mining useful knowledge from the vast amounts of data. Optimized Genetic Programming Applications: Emerging Research and Opportunities is an essential reference source that explores the concept of genetic programming and its role in managing engineering problems. It also examines genetic programming as a supervised machine learning technique, focusing on implementation and application. As a resource that details both the theoretical aspects and implementation of genetic programming, this book is a useful source for academicians, biological engineers, computer programmers, scientists, researchers, and upper-level students seeking the latest research on genetic programming.
| Author | : Gençer, Mehmet |
| Publisher | : IGI Global |
| Total Pages | : 284 |
| Release | : 2020-02-07 |
| Genre | : Computers |
| ISBN | : 1799819140 |
Understanding the social relations within the fields of business and economics is vital for the promotion of success within a certain organization. Analytics and statistics have taken a prominent role in marketing and management practices as professionals are constantly searching for a competitive advantage. Converging these technological tools with traditional methods of business relations is a trending area of research. Applied Social Network Analysis With R: Emerging Research and Opportunities is an essential reference source that materializes and analyzes the issue of structure in terms of its effects on human societies and the state of the individuals in these communities. Even though the theme of the book is business-oriented, an approach underlining and strengthening the ties of this field of study with social sciences for further development is adopted throughout. Therefore, the knowledge presented is valid for analyzing not only the organization of the business world but also for the organization of any given community. Featuring research on topics such as network visualization, graph theory, and micro-dynamics, this book is ideally designed for researchers, practitioners, business professionals, managers, programmers, academicians, and students seeking coverage on analyzing social and business networks using modern methods of statistics, programming, and data sets.
| Author | : Tan, Ying |
| Publisher | : IGI Global |
| Total Pages | : 471 |
| Release | : 2019-12-27 |
| Genre | : Computers |
| ISBN | : 1799816605 |
In recent years, swarm intelligence has become a popular computational approach among researchers working on optimization problems throughout the globe. Several algorithms inside swarm intelligence have been implemented due to their application to real-world issues and other advantages. A specific procedure, Fireworks Algorithm, is an emerging method that studies the explosion process of fireworks within local areas. Applications of this developing program are undiscovered, and research is necessary for scientists to fully understand the workings of this innovative system. The Handbook of Research on Fireworks Algorithms and Swarm Intelligence is a pivotal reference source that provides vital research on theory analysis, improvements, and applications of fireworks algorithm. While highlighting topics such as convergence rate, parameter applications, and global optimization analysis, this publication explores up-to-date progress on the specific techniques of this algorithm. This book is ideally designed for researchers, data scientists, mathematicians, engineers, software developers, postgraduates, and academicians seeking coverage on this evolutionary computation method.
