A Fuzzy Statistical Expert System for Cash Flow Analysis and Management under Uncertainty

Abstract

We live in the world of ambiguity and uncertainty. In such a fuzzy world, using tools that are close to natural language and have the ability to conclude like human mind, and even deal with more data and complex relations are important. This paper provides a fuzzy statistical expert system for cash flow management, one of the most important issues in business. It helps managers in managing their organizational cash resources. For this purpose, first input and output variables and their membership functions have been defined. Then, we formed rules using fuzzy inference system to infer ending cash balance from a set of combination of 25 separate rules. Finally, linguistic levels converted to certain numbers by centered method (defuzzification) to help managers to see the effects of changes in the levels of inputs on ending cash balances. defuzzification represents the relationship between the variables with numerical values. The required data for practical illustration of our mode is gathered from Cement Companies listed on Tehran Stock Exchange, which their financial reports are prepared based on Iranian Accounting Standards. The authors believe that the proposed system helps managers to analyze the effects of changes in input variables on ending cash balances.