IGI Global | Applications Of Artificial Neural Networks For Nonlinear Data (2021 EN)

Author: Hiral Ashil Patel, A.V. Senthil Kumar
Full Title: Applications Of Artificial Neural Networks For Nonlinear Data
Publisher: IGI Global (September 25, 2020)
Year: 2021
ISBN-13: 9781799840435 (978-1-79-984043-5), 9781799840428 (978-1-79-984042-8), 9781799851509 (978-1-79-985150-9)
ISBN-10: 1799840433, 1799840425, 1799851508
Pages: 315
Language: English
Genre: Educational: Neural Networks
File type: PDF (True, but nonnative Cover)
Quality: 9/10
Price: $245.00


Processing information and analyzing data efficiently and effectively is crucial for any company that wishes to stay competitive in its respective market. Nonlinear data presents new challenges to organizations, however, due to its complexity and unpredictability. The only technology that can properly handle this form of data is artificial neural networks. These modeling systems present a high level of benefits in analyzing complex data in a proficient manner, yet considerable research on the specific applications of these intelligent components is significantly deficient.

Applications of Artificial Neural Networks for Nonlinear Data is a collection of innovative research on the contemporary nature of artificial neural networks and their specific implementations within data analysis. While highlighting topics including propagation functions, optimization techniques, and learning methodologies, this book is ideally designed for researchers, statisticians, academicians, developers, scientists, practitioners, students, and educators seeking current research on the use of artificial neural networks in diagnosing and solving nonparametric problems.


Topics Covered:
✓ Hidden Layers
✓ Learning Methodologies
✓ Multi-Perceptions
✓ Network Design
✓ Neural System Models
✓ Nonlinearity
✓ Optimization Techniques
✓ Predictive Problem Solving
✓ Propagation Functions
✓ Weight Assignment

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