Artificial Neural Networks and Type-2 by Snehashish Chakraverty (.PDF)
File Size: 26.6 MB
Artificial Neural Networks and Type-2 Fuzzy Set: Elements of Soft Computing and Its Applications by Snehashish Chakraverty, Arup Kumar Sahoo, Dhabaleswar Mohapatra
Requirements: .PDF reader, 26.6 MB
Overview: Soft computing is an emerging discipline which aims to exploit tolerance for imprecision, approximate reasoning, and uncertainty to achieve robustness, tractability, and cost effectiveness for building intelligent machines. Soft computing methodologies include neural networks, fuzzy sets, genetic algorithms, Bayesian networks, and rough sets, among others. In this regard, neural networks are widely used for modeling dynamic solvers, classification of data, and prediction of solutions, whereas fuzzy sets provide a natural framework for dealing with uncertainty. Artificial Neural Networks and Type-2 Fuzzy Set: Elements of Soft Computing and Its Applications covers the fundamental concepts and the latest research on variants of Artificial Neural Networks (ANN), including scientific machine learning and Type-2 Fuzzy Set (T2FS). In addition, the book also covers different applications for solving real-world problems along with various examples and case studies. It may be noted that quite a bit of research has been done on ANN and Fuzzy Set theory/Fuzzy logic. Examples in Python.
Genre: Non-Fiction > Tech & Devices
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