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Neural Networks and Numerical Analysisdoi:10.1515/9783110783186Bruno Despr茅sDe Gruyter
Based on an experimental database consisting of 194 daily cases, artificial neural networks were used to model the removal efficiency of a biofilter for treating hydrogen sulphide (H 2 S). In this work, the removal efficiency of the reactor was considered as a function of the changes in the...
Graph layout algorithms used in network visualization represent the first and the most widely used tool to unveil the inner structure and the behavior of complex networks. Current network visualization software relies on the force-directed layout (FDL) algorithm, whose high computational complexity makes...
Basic ideas of back-propagation neural networks (BPNNs) are presented in short. Then BPNN applications in analysis of the following problems are discussed:... BD Ripley,RM Ripley 被引量: 54发表: 2001年 Neural networks in structural engineering: some recent results and prospects for applications ...
Convolutional networks: These networks are inspired by the animal visual cortex, and therefore are often applied to images, as they can process images in parts multiple times and complete the whole image analysis. Associative memory networks: A type of recurrent network whose equilibrium state is us...
We’re thus now going to see how to treat biases in neural networks, and will then discuss how to justify their inclusions in the neural networks’ architecture from broader principles of linear algebra and numerical analysis. 3. Bias in Neural Networks 3.1. Neural Networks and Linear Functions...
Neural networks are an established class of non-linear modelling technique. This paper offers an introduction and overview to neural nets with particular emphasis on financial applications. We present a brief history of the subject and provide details on two of the more popular models. In addition...
The results show that the neural networks can successfully detect and classify the coarsening in data-sets and, hence, yield insights into the ways in which people count when performing enumeration or other numerical data-compilation exercises. 展开 ...
The method was experimentally validated on a number of numerical tests. As expected, it delivers a fast and reliable algorithm for solving Poisson problems. Keywords: boundary value problems; Laplacian; Poisson problem; neural networks; finite difference discretization; learning data; nonuniform mesh 1...