Titlebook: Soft Computing Approaches in Chemistry; Hugh M. Cartwright,Les M. Sztandera Book 2003 Springer-Verlag Berlin Heidelberg 2003 Base.Chemical

女歌星

Soft Computing, Molecular Orbital, and Density Functional Theory in the Design of Safe Chemicals,olecular modeling to establish databases of various molecular properties of azo dyes required as input for our neural network approach; 2) designing and implementing a neural network architecture suitable to process these databases; and 3) investigating combinations of molecular descriptors needed to predict various properties of the azo dyes.

宽度

Real-time Monitoring of Environmental Pollutants in the Workplace Using Neural Networks and FTIR Sping limits. This chapter describes the use of Neural Networks, combined with Genetic Algorithm optimization, to develop software tools that are capable of identifying atmospheric pollutants, determining whether their concentration exceeds a defined threshold, and, if required, determining that concentration.

Prophylaxis

Application of Evolutionary Algorithms to Combinatorial Library Design,ustries. This change is due to the introduction of automation techniques which allow tens or hundreds of thousands compounds to be synthesised simultaneously and then to be screened for activity rapidly. These techniques of combinatorial synthesis and high throughput screening have vastly increased

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Clustering of Large Data Sets in the Life Sciences,nable us to better understand organisms at the molecular level and to elucidate the mechanisms by which diseases disrupt biological processes. With the advent of whole genome expression technologies such as DNA microarrays and proteomics, scientists can at last determine how the genes and proteins c

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Enthralling

Soft Computing, Molecular Orbital, and Density Functional Theory in the Design of Safe Chemicals,ance to the U.S. textile industry. Where appropriate, modern molecular orbital (MO) and density functional (DF) techniques are employed to establish the necessary databases of molecular properties to be used in conjunction with the neural network approach. In this research, we focused on: 1) using m

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Fuzzy logic and fuzzy classification techniques,ecognition systems, fuzzy c-means, fuzzy ARTMAP, SFAM and radial basis function neural networks are described and compared using standard circle-insquare and iris datasets. A fuzzy classifier for analysis of volatiles using data from an electronic nose is described as an example of constructing a sp

HUMID

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Genetic Algorithms for the Geometry Optimization of Clusters and Nanoparticles,icles, where the interactions between atoms, ions or molecules are described by a variety of potential energy functions (force fields). A detailed description is presented of the Birmingham Cluster Genetic Algorithm Program, developed in our group, and a number of specific applications are highlight

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