Автор: Bijaya Ketan Panigrahi; Ponnuthurai Nagaratnam Sug Название: Swarm, Evolutionary, and Memetic Computing ISBN: 3319202936 ISBN-13(EAN): 9783319202938 Издательство: Springer Рейтинг: Цена: 89440.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Differential Evolution with Two Subpopulations.- Intelligent Water Drops Algorithm for Multimodal Spaces.- Glowworm Swarm based Informative attribute.- Simultaneous Feature Selection and Classification.- TLBO Based Hybrid Forecasting Model for Prediction of Exchange Rates.- Evaluating Internet Information Search Channels using Hybrid MCDM technique.- Image Restoration with Fuzzy Coefficient Driven Anisotropic Diffusion.- Principal Component Analysis and General Regression Auto Associative Neural Network Hybrid as One-Class Classifier.- Software Effort Estimation Using Functional Link Neural Networks Tuned with Active Learning and Optimized with Particle Swarm Optimization.- Fraud Detection in Financial Statements using Evolutionary Computation based Rule Miners.- A Fuzzy Entropy based Multi-level Image Thresholding using Differential Evolution.
Автор: Ferrante Neri; Carlos Cotta; Pablo Moscato Название: Handbook of Memetic Algorithms ISBN: 3642269427 ISBN-13(EAN): 9783642269424 Издательство: Springer Рейтинг: Цена: 156720.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Each class of optimization problems, such as constrained optimization, multi-objective optimization, continuous vs combinatorial problems, uncertainties, are analysed separately and, for each problem, memetic recipes for tackling the difficulties are given with some successful examples.
Автор: William E. Hart; Natalio Krasnogor; J.E. Smith Название: Recent Advances in Memetic Algorithms ISBN: 3642061761 ISBN-13(EAN): 9783642061769 Издательство: Springer Рейтинг: Цена: 181670.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Memetic algorithms are evolutionary algorithms that apply a local search process to refine solutions to hard problems.
Автор: Bijaya Ketan Panigrahi; Ponnuthurai Nagaratnam Sug Название: Swarm, Evolutionary, and Memetic Computing ISBN: 3319037528 ISBN-13(EAN): 9783319037523 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The two-volume set LNCS 8297 and LNCS 8298 constitutes the proceedings of the 4th International Conference on Swarm, Evolutionary and Memetic Computing, SEMCCO 2013, held in Chennai, India, in December 2013. They cover cutting-edge research on swarm, evolutionary and memetic computing, neural and fuzzy computing and its application.
Автор: Bijaya Ketan Panigrahi; Ponnuthurai Nagaratnam Sug Название: Swarm, Evolutionary, and Memetic Computing ISBN: 3319037552 ISBN-13(EAN): 9783319037554 Издательство: Springer Рейтинг: Цена: 93160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The two-volume set LNCS 8297 and LNCS 8298 constitutes the proceedings of the 4th International Conference on Swarm, Evolutionary and Memetic Computing, SEMCCO 2013, held in Chennai, India, in December 2013. They cover cutting-edge research on swarm, evolutionary and memetic computing, neural and fuzzy computing and its application.
Автор: D Jude Hemanth Название: Recent advances on memetic algorithms and its applications in image processing ISBN: 9811513619 ISBN-13(EAN): 9789811513619 Издательство: Springer Рейтинг: Цена: 139750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book includes original research findings in the field of memetic algorithms for image processing applications.
Автор: Ale? Zamuda; Swagatam Das; Ponnuthurai Nagaratnam Название: Swarm, Evolutionary, and Memetic Computing and Fuzzy and Neural Computing ISBN: 3030378373 ISBN-13(EAN): 9783030378370 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This volume constitutes the thoroughly refereed post-conference proceedings of the 7th International Conference on Swarm, Evolutionary, and Memetic Computing, SEMCCO 2019, and 5th International Conference on Fuzzy and Neural Computing, FANCCO 2019, held in Maribor, Slovenia, in July 2019.
Автор: Chi-Keong Goh; Yew-Soon Ong; Kay Chen Tan Название: Multi-Objective Memetic Algorithms ISBN: 3642099785 ISBN-13(EAN): 9783642099786 Издательство: Springer Рейтинг: Цена: 204040.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Memetic algorithms are a success story in sophisticated evolutionary computing. Written for as wide a readership as possible, this book reflects the current state-of-the-art in the theory and practice of Memetic algorithms and is an invaluable reference.
Автор: J.-J. Ch. Meyer, W. van der Hoek Название: Epistemic Logic for AI and Computer Science ISBN: 0521602807 ISBN-13(EAN): 9780521602808 Издательство: Cambridge Academ Рейтинг: Цена: 61240.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book, based on courses taught at universities and summer schools, provides a broad introduction to the subject; many exercises are included with their solutions.
What Can Be Computed? is a uniquely accessible yet rigorous introduction to the most profound ideas at the heart of computer science. Crafted specifically for undergraduates who are studying the subject for the first time, and requiring minimal prerequisites, the book focuses on the essential fundamentals of computer science theory and features a practical approach that uses real computer programs (Python and Java) and encourages active experimentation. It is also ideal for self-study and reference.
The book covers the standard topics in the theory of computation, including Turing machines and finite automata, universal computation, nondeterminism, Turing and Karp reductions, undecidability, time-complexity classes such as P and NP, and NP-completeness, including the Cook-Levin Theorem. But the book also provides a broader view of computer science and its historical development, with discussions of Turing's original 1936 computing machines, the connections between undecidability and Godel's incompleteness theorem, and Karp's famous set of twenty-one NP-complete problems.
Throughout, the book recasts traditional computer science concepts by considering how computer programs are used to solve real problems. Standard theorems are stated and proven with full mathematical rigor, but motivation and understanding are enhanced by considering concrete implementations. The book's examples and other content allow readers to view demonstrations of--and experiment with--a wide selection of the topics it covers. The result is an ideal text for an introduction to the theory of computation.
An accessible and rigorous introduction to the essential fundamentals of computer science theory, written specifically for undergraduates taking introduction to the theory of computation
Features a practical, interactive approach using real computer programs (Python in the text, with Java alternatives online) to enhance motivation and understanding
Gives equal emphasis to computability and complexity
Includes special topics that demonstrate the profound nature of key ideas in the theory of computation
Features a companion website that includes additional materials
Автор: Li, Fanzhang / Zhang, Li / Zhang, Zhao Название: Dynamic Fuzzy Machine Learning ISBN: 3110518708 ISBN-13(EAN): 9783110518702 Издательство: Walter de Gruyter Рейтинг: Цена: 149590.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Machine learning is widely used for data analysis. Dynamic fuzzy data are one of the most difficult types of data to analyse in the field of big data, cloud computing, the Internet of Things, and quantum information. At present, the processing of this kind of data is not very mature. The authors carried out more than 20 years of research, and show in this book their most important results. The seven chapters of the book are devoted to key topics such as dynamic fuzzy machine learning models, dynamic fuzzy self-learning subspace algorithms, fuzzy decision tree learning, dynamic concepts based on dynamic fuzzy sets, semi-supervised multi-task learning based on dynamic fuzzy data, dynamic fuzzy hierarchy learning, examination of multi-agent learning model based on dynamic fuzzy logic. This book can be used as a reference book for senior college students and graduate students as well as college teachers and scientific and technical personnel involved in computer science, artificial intelligence, machine learning, automation, data analysis, mathematics, management, cognitive science, and finance. It can be also used as the basis for teaching the principles of dynamic fuzzy learning.
Автор: Steven L. Brunton, J. Nathan Kutz Название: Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control ISBN: 1108422098 ISBN-13(EAN): 9781108422093 Издательство: Amazon Internet Рейтинг: Цена: 0.00 T Наличие на складе: Невозможна поставка. Описание: Data-driven discovery is revolutionizing the modeling, prediction, and control of complex systems. Aimed at advanced undergraduate and beginning graduate students, this textbook provides an integrated viewpoint that shows how to apply emerging methods from data science, data mining, and machine learning to engineering and the physical sciences.
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