Intelligent Data Analysis in Science
Series: Oxford Chemistry Masters; 4;
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Product details:
- Publisher OUP Oxford
- Date of Publication 27 April 2000
- ISBN 9780198502333
- Binding Hardback
- No. of pages220 pages
- Size 253x193x17 mm
- Weight 623 g
- Language English
- Illustrations numerous line figures 0
Categories
Short description:
This is a fundamental reference work for any scientist contemplating using AI for data analysis.
MoreLong description:
Scientists have been enthusiastic advocates of computational methods of data analysis for as long as computers have been widely available. This book introduces the growing range of computational methods which arise from research into Artificial Intelligence (AI), and which are coming to be recognised as tools of great potential in modern scientific analysis. These methods offer tremendous potential in the analysis of scientific data: papers reporting the application of AI methods in chemistry are currently being published at a rate of several hundred a year; similar figures apply to other areas of science, and the numbers are increasing rapidly. This book leads the reader into the relevant research literature, and provides both the principles and applications of the subject at a level accessible to senior undergraduates and beginning postgraduates.
" This area is an intellectually active one that has inspired many research students, not only in chemistry but also engineering, biology and computer science. This book certainly is a useful and valuable reference, written exactly at the level that a computationally literate graduate student can take home, read and find out what is what before deciding whether to delve deeper" Chemistry and Industry
Table of Contents:
Contents List - Page 1
1. Introduction to intelligent data analysisD Brynn Hibbert2. Knowledge transfer: human experts to expert systemsSharbari Lahiri and Martin J Stillman3. The genetic algorithms, linkage learning, and scalable data miningHillol Kargupta, Eleonora Riva Sanseverino, Erik Johnson, and Samir Agrawal4. Theory and application of fuzzy methodologyPaul P Wang and Fuji Lai5. Data representations for evolutionary computationIan C Parmee, Carlos A Coello Coello, and Andrew H Watson6. Applications of artificial neural networks to the analysis of multivariate dataRoyston Goodacre7. Applications of knowledge-based systemsMary Mulholland and D Brynn Hibbert8. Automatic design of analog electrical circuits using genetic programmingJohn R Koza, Forrest H Bennett III, David Andre, and Martin A KeaneIndex
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