Описание: This book aims to provide some insights into recently developed bio-inspired algorithms within recent emerging trends of fog computing, sentiment analysis, and data streaming as well as to provide a more comprehensive approach to the big data management from pre-processing to analytics to visualization phases.
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
Автор: Feldman Moran Название: Algorithms For Big Data ISBN: 981120473X ISBN-13(EAN): 9789811204739 Издательство: World Scientific Publishing Рейтинг: Цена: 21384.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
This unique volume is an introduction for computer scientists, including a formal study of theoretical algorithms for Big Data applications, which allows them to work on such algorithms in the future. It also serves as a useful reference guide for the general computer science population, providing a comprehensive overview of the fascinating world of such algorithms.
To achieve these goals, the algorithmic results presented have been carefully chosen so that they demonstrate the important techniques and tools used in Big Data algorithms, and yet do not require tedious calculations or a very deep mathematical background.
Описание: Data science revolves around two giants, which are big data analytics and deep learning. It is becoming challenging to handle and retrieve useful information due to how fast data is expanding. This book presents the technologies and tools to simplify and streamline the formation of big data along with deep learning systems.
Автор: Liao Heng Название: Mathematics for Future Computing and Communications ISBN: 1316513580 ISBN-13(EAN): 9781316513583 Издательство: Cambridge Academ Рейтинг: Цена: 8554.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: New mathematical ideas go hand-in-hand with innovation in computing, communications and AI. Such innovations are described here in a book that provides a panorama of ideas and applications in computer architecture, software verification, quantum computing, compressed sensing, Bayesian inference, machine learning, reinforcement learning and more.
Автор: Song Tao, Zheng Pan, Wong Dennis Mou Ling, Wang Xu Название: Bio-inspired Computing Models And Algorithms ISBN: 9813143177 ISBN-13(EAN): 9789813143173 Издательство: World Scientific Publishing Рейтинг: Цена: 19008.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Bio-inspired computing (BIC) focuses on the designs and developments of computer algorithms and models based on biological mechanisms and living phenomena. It is now a major subfield of natural computation that leverages on the recent advances in computer science, biology and mathematics.
The ideas provide abundant inspiration to construct high-performance computing models and intelligent algorithms, thus enabling powerful tools to solve real-life problems.
Written by world-renowned researchers, this compendium covers the most influential topics on BIC, where the newly-obtained algorithms, developments and results are introduced and elaborated. The potential and valuable directions for further research are addressed as well.
Автор: Dey Nilanjan, Ashour Amira S., Bhattacharyya Siddhartha Название: Applied Nature-Inspired Computing: Algorithms and Case Studies ISBN: 981139265X ISBN-13(EAN): 9789811392658 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: It introduces readers to a broad range of algorithms, such as genetic algorithms, particle swarm optimization, the firefly algorithm, flower pollination algorithm, collision-based optimization algorithm, bat algorithm, ant colony optimization, and multi-agent systems.
Описание: Explores research developments and applications from an interdisciplinary perspective that combines approaches from operations research, computer science, artificial intelligence, and applied computational mathematics. Contributions cover a range of hybrid algorithm theory and practice as it relates to routing, scheduling, and real-life applications.
Описание: 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.
Автор: Mitzenmacher Название: Probability and Computing ISBN: 110715488X ISBN-13(EAN): 9781107154889 Издательство: Cambridge Academ Рейтинг: Цена: 8237.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This greatly expanded new edition, requiring only an elementary background in discrete mathematics, comprehensively covers randomization and probabilistic techniques in modern computer science. It includes new material relevant to machine learning and big data analysis, plus examples and exercises, enabling students to learn modern techniques and applications.
Автор: Dey Nilanjan, Ashour Amira S., Bhattacharyya Siddhartha Название: Applied Nature-Inspired Computing: Algorithms and Case Studies ISBN: 9811392625 ISBN-13(EAN): 9789811392627 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents a cutting-edge research procedure in the Nature-Inspired Computing (NIC) domain and its connections with computational intelligence areas in real-world engineering applications. It introduces readers to a broad range of algorithms, such as genetic algorithms, particle swarm optimization, the firefly algorithm, flower pollination algorithm, collision-based optimization algorithm, bat algorithm, ant colony optimization, and multi-agent systems. In turn, it provides an overview of meta-heuristic algorithms, comparing the advantages and disadvantages of each. Moreover, the book provides a brief outline of the integration of nature-inspired computing techniques and various computational intelligence paradigms, and highlights nature-inspired computing techniques in a range of applications, including: evolutionary robotics, sports training planning, assessment of water distribution systems, flood simulation and forecasting, traffic control, gene expression analysis, antenna array design, and scheduling/dynamic resource management.
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