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Soft Computing For Problem Solving Socpros 2017 Volume 2 1st Ed Jagdish Chand Bansal

  • SKU: BELL-7328436
Soft Computing For Problem Solving Socpros 2017 Volume 2 1st Ed Jagdish Chand Bansal
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Soft Computing For Problem Solving Socpros 2017 Volume 2 1st Ed Jagdish Chand Bansal instant download after payment.

Publisher: Springer Singapore
File Extension: PDF
File size: 34.52 MB
Author: Jagdish Chand Bansal, Kedar Nath Das, Atulya Nagar, Kusum Deep, Akshay Kumar Ojha, (eds.)
ISBN: 9789811315947, 9789811315954, 9811315949, 9811315957
Language: English
Year: 2019
Edition: 1st ed.

Product desciption

Soft Computing For Problem Solving Socpros 2017 Volume 2 1st Ed Jagdish Chand Bansal by Jagdish Chand Bansal, Kedar Nath Das, Atulya Nagar, Kusum Deep, Akshay Kumar Ojha, (eds.) 9789811315947, 9789811315954, 9811315949, 9811315957 instant download after payment.

This two-volume book presents outcomes of the 7th International Conference on Soft Computing for Problem Solving, SocProS 2017. This conference is a joint technical collaboration between the Soft Computing Research Society, Liverpool Hope University (UK), the Indian Institute of Technology Roorkee, the South Asian University New Delhi and the National Institute of Technology Silchar, and brings together researchers, engineers and practitioners to discuss thought-provoking developments and challenges in order to select potential future directions The book presents the latest advances and innovations in the interdisciplinary areas of soft computing, including original research papers in the areas including, but not limited to, algorithms (artificial immune systems, artificial neural networks, genetic algorithms, genetic programming, and particle swarm optimization) and applications (control systems, data mining and clustering, finance, weather forecasting, game theory, business and forecasting applications). It is a valuable resource for both young and experienced researchers dealing with complex and intricate real-world problems for which finding a solution by traditional methods is a difficult task.

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