Application of Neural Networks and Other Learning

Book Summary:

 

Encyclopedia of Neural Networks in Bioprocessing and Chemical Engineering discusses on the application of neural networks. In computer science and related fields, artificial neural networks are computational models inspired by animals’ central nervous systems that are capable of machine learning and pattern recognition. For example, in a neural network for handwriting recognition, a set of input neurons may be activated by the pixels of an input image representing a letter or digit. The activations of these neurons are then passed on, weighted, and transformed by some function determined by the network’s designer, to other neurons, etc., until finally an output neuron is activated that determines which character was read.

Audience Of this Book:

This book is Useful for Computer Science Engineering Students.

 

Table of Content:

Chapter 1 Comparison of Artificial Neural Network Architecture in
Solving Ordinary Differential Equations

Chapter 2 Artificial Neural Network Modeling for Biological Removal
of Organic Carbon and Nitrogen from Slaughterhouse Wastewater in a Sequencing Batch Reactor

Chapter 3 Improved Kohonen Feature Map Probabilistic Associative
Memory Based on Weights Distribution

Chapter 4 Using Ensemble of Neural Networks to Learn Stochastically
Convection Parameterizations for Climate and Numerical Weather Prediction Models from Data Simulated by a Cloud Resolving Model

Chapter 5 Fuzzified Data-Based Neural Network Modeling for Health
Assessment of Multistorey Shear Buildings

Chapter 6 A Unified Framework for GPS Code and Carrier-Phase
Multipath Mitigation Using Support Vector Regression

Chapter 7 A Novel Learning Scheme for Chebyshev
Functional Link Neural Networks

Chapter 8 Activation Detection on fMRI Time Series Using
Hidden Markov Mode