Artificial Neural Networks: New Research

This current book provides new research on artificial neural networks (ANNs). Topics discussed include the application of ANNs in chemistry and chemical engineering fields; the application of ANNs in the prediction of biodiesel fuel properties from fatty acid constituents; the use of ANNs for solar radiation estimation; the use of in silico methods to design and evaluate skin UV filters; a practical model based on the multilayer perceptron neural network (MLP) approach to predict the milling tool flank wear in a regular cut, as well as entry cut and exit cut, of a milling tool; parameter extraction of small-signal and noise models of microwave transistors based on ANNs; and the application of ANNs to deep-learning and predictive analysis in semantic TCM telemedicine systems

Table of Contents

Chapter 1. Applications of Artificial Neural Networks in Chemical Engineering
Chapter 2. Applications of Artificial Neural Networks in Chemistry and Chemical Engineering
Chapter 3. Applications of Artificial Neural Networks to Energy and Buildings
Chapter 4. Applications of Artificial Neural Network to Predict Biodiesel Fuel Properties from Fatty Acid Constituents
Chapter 5. Applications of ANN Methods for Solar Radiation Estimation
Chapter 6. The Use of In Silico Methods to Design and Evaluate Skin UV Filters
Chapter 7. Modeling the Milling Tool Wear by Using a Multilayer Perceptron Artificial Neural Network from Milling Run Experimental Data
Chapter 8. Parameter Extraction of Small-Signal and Noise Models of Microwave Transistors Based on Artificial Neural Networks
Chapter 9. Applying Artificial Neural Networks to Deep Learning and Predictive Analysis in Semantic TCM Telemedicine Systems