9786207654413 - Soft Computing by Bhambri, Pankaj; Malhi, Manpreet; Kumar, Suresh (10 results)

Condition: New. In.

Condition: New.

Taschenbuch. Condition: Neu. Soft Computing | Pankaj Bhambri (u. a.) | Taschenbuch | Englisch | 2025 | LAP LAMBERT Academic Publishing | EAN 9786207654413 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

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

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

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -'Soft Computing' covers fuzzy logic, neural networks, and evolutionary algorithms in a complete introduction to the area. The book begins by charting computing from traditional AI to computational intelligence, preparing readers for soft computing. It teaches machine learning fundamentals. The book covers fuzzy logic, including fuzzy sets, relations, and inference systems. Readers learn about fuzzy logic in expert systems and decision-making through thorough discussions on membership functions and fuzzy reasoning. In the second section, the book covers neural network evolution, construction, and training techniques. Readers learn about neural network models and machine learning applications, from feedforward networks to adaptive resonance structures. Genetic algorithms, their biological origin, optimization methods, and comparison to classical algorithms are covered in the book's conclusion. Reading examples and case studies helps readers understand genetic algorithms and their applicability in difficult optimization issues. 'Soft Computing' is a useful reference for students, academics, and practitioners investigating the wide field of soft computing. 92 pp. Englisch.

Condition: New. Print on Demand.

Condition: New. PRINT ON DEMAND.

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -'Soft Computing' covers fuzzy logic, neural networks, and evolutionary algorithms in a complete introduction to the area. The book begins by charting computing from traditional AI to computational intelligence, preparing readers for soft computing. It teaches machine learning fundamentals. The book covers fuzzy logic, including fuzzy sets, relations, and inference systems. Readers learn about fuzzy logic in expert systems and decision-making through thorough discussions on membership functions and fuzzy reasoning. In the second section, the book covers neural network evolution, construction, and training techniques. Readers learn about neural network models and machine learning applications, from feedforward networks to adaptive resonance structures. Genetic algorithms, their biological origin, optimization methods, and comparison to classical algorithms are covered in the book's conclusion. Reading examples and case studies helps readers understand genetic algorithms and their applicability in difficult optimization issues. 'Soft Computing' is a useful reference for students, academics, and practitioners investigating the wide field of soft computing.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 92 pp. Englisch.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 'Soft Computing' covers fuzzy logic, neural networks, and evolutionary algorithms in a complete introduction to the area. The book begins by charting computing from traditional AI to computational intelligence, preparing readers for soft computing. It teaches machine learning fundamentals. The book covers fuzzy logic, including fuzzy sets, relations, and inference systems. Readers learn about fuzzy logic in expert systems and decision-making through thorough discussions on membership functions and fuzzy reasoning. In the second section, the book covers neural network evolution, construction, and training techniques. Readers learn about neural network models and machine learning applications, from feedforward networks to adaptive resonance structures. Genetic algorithms, their biological origin, optimization methods, and comparison to classical algorithms are covered in the book's conclusion. Reading examples and case studies helps readers understand genetic algorithms and their applicability in difficult optimization issues. 'Soft Computing' is a useful reference for students, academics, and practitioners investigating the wide field of soft computing.