Description
Book SynopsisAn analysis of fuzzy sets and the theory of evidence to accounting. It is divided into parts, covering: methodology; inference; prediction; and neural networks.
Table of ContentsPart 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.
