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Titlebook: Soft Computing Applications in Business; Bhanu Prasad Book 2008 Springer-Verlag Berlin Heidelberg 2008 Markov.Markov model.audit.calculus.

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Soft Computing in Intelligent Tutoring Systems and Educational Assessment, significance and generate appropriate questions, to interpretation of noisy spoken responses and statistical assessment of the response quality, through user modeling and determining how best to respond to the learner in order to optimize learning gains. This chapter focuses primarily on the domain
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A Decision Making System for the Treatment of Dental Caries,tem is based on the Bayesian Network (BN) and is designed to decide among various possible treatment plans. The system has been evaluated with the help of 13 different dentists to test its operational effectiveness. The system improves the confidence level of a dentist while deciding the treatment p
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CBR Based Engine for Business Internal Control,of models that automate and facilitate the work of the auditors crucial. A tool for the decision support process has been developed based on a multi-cbr system that incorporates two case-based reasoning systems and automates the business control process. The objective of the system is to facilitate
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An EMD-Based Neural Network Ensemble Learning Model for World Crude Oil Spot Price Forecasting,and forecasting. For this purpose, the original crude oil spot price series were first decomposed into a finite and often small number of intrinsic mode functions (IMFs). Then the three-layer feed-forward neural network (FNN) model was used to model each extracted IMFs so that the tendencies of thes
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Ensembles of Classifiers in Arrears Management,s and two such approaches (minority over-sampling and majority under-sampling) were adopted here. The ensembles outperformed the single classifiers, irrespective of the strategy that was used. The results suggest that an ensemble approach has the potential to provide a high rate of classification accuracy for problem domains of this type.
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1434-9922 This book consists of several important papers on the applications of soft computing techniques for the business field. The soft computing techniques used in this book include (or very closely related to): Bayesian networks, biclustering methods, case-based reasoning, data mining, Dempster-Shafer th
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