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Zustand: New. Eight edition cation India Ltd. NO-PA16APR2015-KAP.

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Zustand: New. Prof. (Dr.) Sushil Chandra Dimri, M.Tech., Ph.D. (Computer Science), is currently working with Graphic Era deemed to be University as professor in the Department of Computer Science and Engineering. His teaching industry experience is more than 26.

Hardcover. Zustand: Brand New. 248 pages. 6.14x0.69x9.21 inches. In Stock.

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Hardcover. Zustand: new. Hardcover. This book presents key computational intelligence approaches applied across diverse areas of computer science, demonstrating their effectiveness in solving real-world problems. It highlights how nature-inspired methods are shaping the future of intelligent systems and offering powerful, efficient, and elegant solutions to complex challenges.Computational intelligence (CI) extends far beyond the optimization of complex computations. It provides robust, generic, and adaptable mechanisms for addressing challenging problems across science and technology where traditional mathematical reasoning encounters uncertainty, nonlinearity, and complexity.In computer science, CI strongly influences algorithm design, system architectures, and optimization schemes. Unlike classical artificial intelligence, which is largely rule- and logic-based, computational intelligence relies on nature-inspired methodologies that model learning, adaptation, and evolution.Traditionally, CI has been built upon three foundational paradigms: Neural networks, fuzzy systems, and evolutionary computation. Neural networks emulate the structure and learning behavior of the human brain; fuzzy systems incorporate linguistic reasoning to manage uncertainty and imprecise data; and evolutionary computation draws inspiration from biological evolution, incorporating mechanisms such as selection, mutation, and reproduction.Today, CI has expanded to include machine learning methods, swarm intelligence, support vector machines, and chaotic systems. These techniques enable faster, more accurate, and less complex decision-making across a wide range of computational problems. This book explores computational intelligencenature-inspired methods such as neural networks, fuzzy systems, evolutionary computation, and swarm intelligenceshowing how they enable faster, more accurate decision-making and powerful solutions to complex problems across computer science. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

HRD. Zustand: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

HRD. Zustand: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Hardcover. Zustand: new. Hardcover. This book presents key computational intelligence approaches applied across diverse areas of computer science, demonstrating their effectiveness in solving real-world problems. It highlights how nature-inspired methods are shaping the future of intelligent systems and offering powerful, efficient, and elegant solutions to complex challenges.Computational intelligence (CI) extends far beyond the optimization of complex computations. It provides robust, generic, and adaptable mechanisms for addressing challenging problems across science and technology where traditional mathematical reasoning encounters uncertainty, nonlinearity, and complexity.In computer science, CI strongly influences algorithm design, system architectures, and optimization schemes. Unlike classical artificial intelligence, which is largely rule- and logic-based, computational intelligence relies on nature-inspired methodologies that model learning, adaptation, and evolution.Traditionally, CI has been built upon three foundational paradigms: Neural networks, fuzzy systems, and evolutionary computation. Neural networks emulate the structure and learning behavior of the human brain; fuzzy systems incorporate linguistic reasoning to manage uncertainty and imprecise data; and evolutionary computation draws inspiration from biological evolution, incorporating mechanisms such as selection, mutation, and reproduction.Today, CI has expanded to include machine learning methods, swarm intelligence, support vector machines, and chaotic systems. These techniques enable faster, more accurate, and less complex decision-making across a wide range of computational problems. This book explores computational intelligencenature-inspired methods such as neural networks, fuzzy systems, evolutionary computation, and swarm intelligenceshowing how they enable faster, more accurate decision-making and powerful solutions to complex problems across computer science. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Hardcover. Zustand: new. Hardcover. This book presents key computational intelligence approaches applied across diverse areas of computer science, demonstrating their effectiveness in solving real-world problems. It highlights how nature-inspired methods are shaping the future of intelligent systems and offering powerful, efficient, and elegant solutions to complex challenges.Computational intelligence (CI) extends far beyond the optimization of complex computations. It provides robust, generic, and adaptable mechanisms for addressing challenging problems across science and technology where traditional mathematical reasoning encounters uncertainty, nonlinearity, and complexity.In computer science, CI strongly influences algorithm design, system architectures, and optimization schemes. Unlike classical artificial intelligence, which is largely rule- and logic-based, computational intelligence relies on nature-inspired methodologies that model learning, adaptation, and evolution.Traditionally, CI has been built upon three foundational paradigms: Neural networks, fuzzy systems, and evolutionary computation. Neural networks emulate the structure and learning behavior of the human brain; fuzzy systems incorporate linguistic reasoning to manage uncertainty and imprecise data; and evolutionary computation draws inspiration from biological evolution, incorporating mechanisms such as selection, mutation, and reproduction.Today, CI has expanded to include machine learning methods, swarm intelligence, support vector machines, and chaotic systems. These techniques enable faster, more accurate, and less complex decision-making across a wide range of computational problems. This book explores computational intelligencenature-inspired methods such as neural networks, fuzzy systems, evolutionary computation, and swarm intelligenceshowing how they enable faster, more accurate decision-making and powerful solutions to complex problems across computer science. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…