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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.

Online EBSCO Academic Comprehensive Collection

Artificial neural networks

An artificial neural network (ANN) is a type of artificial intelligence technology which implements more complex data-analysis features into existing applications by an intelligent, human-like application of knowledge. ANN can be considered as a mathematical or computational model based on biological (brain) neural networks. ANN is an adaptive system that changes its structure based on external or internal information that is processed within the network during the learning stage. ANNs implement algorithms that attempt to achieve neurologically-related processes and performances such as learning from experience, making generalisations from similar situations and judging states where poor results were achieved in the past. This new and important book gathers the most current research from across the globe in the study of artificial neural networks.

Online EBSCO Academic Comprehensive Collection

Artificial neural networks

This volume presents examples of how Artificial Neural Networks (ANNs) are applied in biological sciences and related areas. Chapters cover a wide variety of topics, including the analysis of intracellular sorting information, prediction of the behavior of bacterial communities, biometric authentication, studies of Tuberculosis, gene signatures in breast cancer classification, the use of mass spectrometry in metabolite identification, visual navigation, and computer diagnosis. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, application details for both the expert and non-expert reader, and tips on troubleshooting and avoiding known pitfalls. Authoritative and practical, Artificial Neural Networks: Third Edition should be of value to all scientists interested in the hands-on application of ANNs in the biosciences.

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Motivation in education

Education and psychology