R p arya (41 risultati)

Condizione: New. pp. vi + 312 , Illus.

broschiert. Condizione: Akzeptabel. 22 cm ; First Edition. Softcover, 64 Seiten mit zahlreichen farbigen Karten. Umschlag etwas berieben/knittrig und mit grün übermalter Schabstelle. pwB7.

Condizione: Good. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

Condizione: New.

Condizione: New.

Condizione: New.

Soft cover. Condizione: Fine. No Jacket. Updated & revised Edition. pp.48, illustrated with colured maps and tables. Pictorial red glossy card covers. fine.

Condizione: New.

Saddle-stapled softcover. Condizione: Very Good. 64pp Size: Slim 8vo - over 7¾" - 9¾" tall. Color maps (illustratore).

Condizione: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

Softcover/Paperback. Condizione: Gut. 56 p. ; maps. Good. Ex-library with usual markings. Title page creased. Clean pages. Sprache: Englisch Gewicht in Gramm: 220.

Condizione: New. pp. xx + 769.

Hardcover. Condizione: As New. Dust Jacket Included. Contents Foreword. Preface. Acknowledgements. I. Natural resource appraisal 1. Managing natural resources of Northern India for environmental and livelihood security/V.N. Sharda. 2. India 60 natural resources management and poverty reduction/K.G. Tejwani. 770 pp. …

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Hardcover. Condizione: Brand New. 180 pages. In Stock.

Condizione: New.

paperback. Condizione: Gut. 64 Seiten; 9788187460008.3 Gewicht in Gramm: 500.

Condizione: New. 2025. hardcover. . . . . .

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Condizione: New.

Hardcover. Condizione: Brand New. 350 pages. 9.21x6.14x0.69 inches. In Stock.

Condizione: New. In English.

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Condizione: New. 2025. hardcover. . . . . . Books ship from the US and Ireland.

Hardback. Condizione: New. We have witnessed an explosion of research activity around nature-inspired computing and bio-inspired optimization techniques, which can provide powerful tools for solving learning problems and data analysis in very large data sets. To design and implement optimization algorithms, several methods are used that bring superior performance. However, in some applications, the search space increases exponentially with the problem size. To overcome these limitations and to solve efficiently large scale combinatorial and highly nonlinear optimization problems, more flexible and adaptable algorithms are necessary. Nature-inspired computing is oriented towards the application of outstanding information-processing aptitudes of the natural realm to the computational domain. The discipline of nature-inspired optimization algorithms is a major field of computational intelligence, soft computing and optimization. Metaheuristic search algorithms with population-based frameworks are capable of handling optimization in high-dimensional real-world problems for several domains including imaging, IoT, smart manufacturing, and healthcare. The integration of intelligence with smart technology enhances accuracy and efficiency. Smart devices and systems are revolutionizing the world by linking innovative thinking with innovative action and innovative implementation. The aim of this edited book is to review the intertwining disciplines of nature-inspired computing and bio-inspired soft-computing (BISC) and their applications to real world challenges. The contributors cover the interaction between metaheuristics, such as evolutionary algorithms and swarm intelligence, with complex systems. They explain how to better handle different kinds of uncertainties in real-life problems using state-of-art of machine learning algorithms. They also explore future research perspectives to bridge the gap between theory and real-life day-to-day challenges for diverse domains of engineering. The book will offer valuable insights to researchers and scientists from academia and industry in ICTs, IT and computer science, data science, AI and machine learning, swarm intelligence and complex systems. It is also a useful resource for professionals in related fields, and for advanced students with an interest in optimization and IoT applications.…

Buch. Condizione: Neu. Neuware - We have witnessed an explosion of research activity around nature-inspired computing and bio-inspired optimization techniques, which can provide powerful tools for solving learning problems and data analysis in very large data sets. To design and implement optimization algorithms, several methods are used that bring superior performance. However, in some applications, the search space increases exponentially with the problem size. To overcome these limitations and to solve efficiently large scale combinatorial and highly nonlinear optimization problems, more flexible and adaptable algorithms are necessary. Nature-inspired computing is oriented towards the application of outstanding information-processing aptitudes of the natural realm to the computational domain. The discipline of nature-inspired optimization algorithms is a major field of computational intelligence, soft computing and optimization. Metaheuristic search algorithms with population-based frameworks are capable of handling optimization in high-dimensional real-world problems for several domains including imaging, IoT, smart manufacturing, and healthcare. The integration of intelligence with smart technology enhances accuracy and efficiency. Smart devices and systems are revolutionizing the world by linking innovative thinking with innovative action and innovative implementation. The aim of this edited book is to review the intertwining disciplines of nature-inspired computing and bio-inspired soft-computing (BISC) and their applications to real world challenges. The contributors cover the interaction between metaheuristics, such as evolutionary algorithms and swarm intelligence, with complex systems. They explain how to better handle different kinds of uncertainties in real-life problems using state-of-art of machine learning algorithms. They also explore future research perspectives to bridge the gap between theory and real-life day-to-day challenges for diverse domains of engineering. The book will offer valuable insights to researchers and scientists from academia and industry in ICTs, IT and computer science, data science, AI and machine learning, swarm intelligence and complex systems. It is also a useful resource for professionals in related fields, and for advanced students with an interest in optimization and IoT applications.…