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[DOC File]LECTURE #9: FUZZY LOGIC & NEURAL NETS
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By applying a direct kernel transform, traditional methods such as Principal Component Analysis (PCA), Ridge Regression, Partial Least Squares (PLS), Independent Component Analysis (ICA) or simple one-layered neural networks, can be transformed into powerful nonlinear modeling and …

[DOC File]1
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Neural Nets 9. Decision Trees 10. Memory-based Reasoning 11. Genetic Algorithms 12. Link Analysis 12. Market Basket Analysis 13 ... The statistic methods used here are different from the standard statistic methods such as regression. Market basket analysis is a form of clustering used for finding groups of items that tend to occur together in a ...

[DOC File]Case Western Reserve University: One of the nation’s best
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The Candidate will have technical skills in 1) computer science and statistics – neural nets, pattern recognition, graph theory, network and path analysis, linear regression, and multivariate analysis. 2) Genetics methods and data, including crosses, mutants, and chromosome substitution strains, DNA sequence, mRNA and miRNA profiles, and ...

[DOC File]Mathematical Modeling of Chemical Processes
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Perform a degrees of freedom analysis (Section 2.3) to ensure that the model equations can be solved. ... linear regression. nonlinear regression . ... (use optimization code to fit parameters) nonlinear models such as neural nets are becoming popular (automatic modeling) Uses of Mathematical Modeling . to improve understanding of the process .

[DOC File]Using Artificial Neural Networks Analysis For Small ...
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Neural nets vs. logistic regression: A comparison of each model’s ability to predict commercial bank failures. Proceedings of the 1990 Deloitte & Touche/University of Kansas Symposium on Auditing Problems, pp. 29-53.

[DOC File]LECTURE #9: FUZZY LOGIC & NEURAL NETS
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A neural network can be viewed as a least-squares model-free regression-like approximator that can implement almost any map. The illustration of a forecasting model for the world's population with a simple neural network proceeds similar to regression analysis and relatively straightforward.

[DOCX File]Survey of Intelligent STLF Methods
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Six approaches have been reviewed in this paper:(1) Regression Methods(2)Times Series (3)Neural Networks Method (4)Fuzzy Logic Method (5)Knowledge Based Expert System (6)Petri nets system. After surveying all these approaches, we can observe a clear trend toward new, stochastic, and dynamic forecasting techniques.

REFERENCES ON APPLICATIONS OF NEURAL NETWORKS IN …
Newsgroup comp.ai.neural_nets (FAQ file) Resources for Economists on the Internet (Bill Goffe) Backpropagator (by Donald Tverter) Tutorial on NN in Finance (A. Episcopos) Finance and Technology ...

[DOC File]NEURAL NETWORKS FOR FAULT DIAGNOSIS BASED ON …
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• A special strength of neural nets. Neural Net for classification at run time. Neural Networks vs. other techniques • Complements traditional modelling, rule-based systems, optimization, regression, interpolation, and control • Focus is on nonlinear systems, vs. traditional linear techniques that may be more efficient for linear systems

Abstract: - A4academics
Neural nets and decision trees can also be used to perform regressions, and some types of neural nets can even perform clustering. 2.1 Introduction to Data warehousing: In the current knowledge economy, it is now an indisputable fact that information is the key to organizations for gaining competitive advantage.

Regression analysis with neural nets