Artificial Neural Networks: New Research


Gayle Cain (Editor)

Series: Computer Science, Technology and Applications
BISAC: COM014000

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. (Imprint: Nova)

Table of Contents

Table of Contents


Chapter 1. Applications of Artificial Neural Networks in Chemical Engineering
Ivan M. Savic, Dragoljub G. Gajic and Ivana M. Savic-Gajic (Faculty of Technology, University of Nis, Bulevar oslobodjenja, Leskovac, Serbia, and others)

Chapter 2. Applications of Artificial Neural Networks in Chemistry and Chemical Engineering
Aderval S. Luna, Eduardo R. A. Lima and Kese Pontes Freitas Alberton (Institute of Chemistry, Rio de Janeiro State University, Rio de Janeiro, Brazil, and others)

Chapter 3. Applications of Artificial Neural Networks to Energy and Buildings
Cinzia Buratti, Domenico Palladino and Francesco Cristarella Orestano (University of Perugia, Department of Engineering, Italy)

Chapter 4. Applications of Artificial Neural Networks to Predict Biodiesel Fuel Properties from Fatty Acid Constituents
Solomon O. Giwa (Department of Agricultural and Mechanical Engineering, College of Engineering and Environmental Studies, Olabisi Onabanjo University, Ibogun Campus, Ifo, Ogun State, Nigeria)

Chapter 5. Applications of ANN Methods for Solar Radiation Estimation
Gilles Notton, Kahina Dahmani, Rabah Dizene, Marie-Laure Nivet, Cyril Voyant, and Christophe Paoli (Laboratory Sciences for Environment, University of Corsica Pascal Paoli, UMR CNRS, Route des Sanguinaires, Ajaccio, France, and others)

Chapter 6. The use of in Silico Methods to Design and Evaluate Skin UV Filters
Snezana Agatonovic-Kustrin and David W. Morton (Faculty of Pharmacy, Universiti Teknologi MARA (UiTM), Selangor, Malaysia, and others)

Chapter 7. Modeling the Milling Tool Wear by using a Multilayer Perceptron Artificial Neural Network from Milling Run Experimental Data
P. J. García Nieto and E. García-Gonzalo (Department of Mathematics, University of Oviedo, Oviedo, Spain, and others)

Chapter 8. Parameter Extraction of Small-Signal and Noise Models of Microwave Transistors based on Artificial Neural Networks
Zlatica Marinkoviæ, Vladica Ðorðeviæ, Nenad Ivkoviæ, Olivera Proniæ-Ranèiæ, Vera Markoviæ, Alina Caddemi (University of Niš, Faculty of Electronic Engineering, Niš, Serbia, and others)

Chapter 9. Applying Artificial Neural Networks to Deep Learning and Predictive Analysis in Semantic TCM Telemedicine Systems
Wilfred W. K. Lin and Allan K. Y. Wong (Department of Computing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China)


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