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An analysis of fuzzy sets and the theory of evidence to accounting. It is divided into parts, covering: methodology; inference; prediction; and neural networks.
List of contents
Part 1 Methodology: utilizing fuzzy logic in decision making - new frontiers, Kursheed Omer and Andre de Korvin; fuzzy set theory and behavioural models for decision making under ambiguity, Awni Zebda. Part 2 Applying fuzzy-set theory to target costing in the automobile industry, Mohamed E. Bayou and Alan Reinstein; quality contingent replenishment policies under fuzzy demand, Jess S. Boronico; a fuzzy decision support for cost management systems design, Akhilesh Chandra and Surendra Agrawal; knowledge acquisition and the development of decision rules - studying and evaluating internal control structure, Philip H. Siegel, Jerry Strawser and Andre de Korvin. Part 3 Inference: assessment of short term liquidity risk using fuzzy sets, Ashutosh Deshmukh and Sia Nassiripour; a fuzzy set approach to client acceptance decision, Ashutosh Deshmukh, Jeffery Romaine and T.L.N. Tallaru; fuzzy expert systems - the problem of validation, Michelle McEacharn, Awni Zebda and James Calloway; uncertainty handling in accounting expert systems - a comparison of alternative approaches to knowledge representation, Ram S. Sriram and Patrick Wheeler. Part 4 Prediction: modelling ambiguity in both value and demand functions - the applications of fuzzy sets to stochastic modelling under uncertainty, Jess S. Boronico and Robert Kleyle; assessment of capital budgeting sophistication - an application of fuzzy set theory, Pamela H. Church, J. David Spiceland and Carolyn R. George; the audit risk model under the risk of fraud, Saurav Dutta, Keith E. Harrison and Rajendra P. Srivastava; project cost control - a fuzzy logic approach to crashing project activity, Kursheed Omer, Margaret F. Shipley and Andre de Korvin; the peer review process - a fuzzy decision model, Kursheed Omer et al. Part 5 Neural networks: a comparative analysis of artificial network algorithms - application to a bank financial risk model, Ram S. Sriram, R. Srikanth and Roy George; improving artificial neural network performance through input variable selection, Ali Tahai, Steven Walczak and John Rigsby; improved cash flows using neural network models for forecasting foreign rates, Steven Walczak, Ali Tahai and Khondar Karim.
Summary
An analysis of fuzzy sets and the theory of evidence to accounting. It is divided into parts, covering: methodology; inference; prediction; and neural networks.
