Case-Based Reasoning for Cash-Flow Forecasting using Fuzzy Retrieval

Case-Based Reasoning (CBR) simulates the human way of solving problems as it solves a new problem using a successful past experience applied to a similar problem. In this paper we describe a CBR system that develops forecasts for cash flow accounts. Forecasting cash flows to a certain degree of accuracy is an important aspect of a Working Capital Decision Support System. Working Capital (WC) management decisions reflect a choice among different options on how to arrange the cash flow. The decision establishes an actual event in the cash flow which means that one needs to envision the consequences of such a decision. Hence, forecasting cash flows accurately can minimize losses caused by usually unpredictable events. Cash flows are usually forecasted by a combination of different techniques enhanced by human experts' feelings about the future, which are grounded in past experience. This makes the use of the CBR paradigm the proper choice. Advantages of a CBR system over other Artificial Intelligence techniques are associated to knowledge acquisition, knowledge representation, reuse, updating, and justification. An important step in developing a CBR system is the retrieval of similar cases. The proposed system makes use of fuzzy integrals to calculate the synthetic evaluations of similarities between cases instead of the usual weighted mean.

[1]  Lotfi A. Zadeh,et al.  The Concepts of a Linguistic Variable and its Application to Approximate Reasoning , 1975 .

[2]  M. Sugeno.  FUZZY MEASURES AND FUZZY INTEGRALS—A SURVEY , 1993 .

[3]  Toyoo Fukuda,et al.  Case organization in a case-based engineering design support system , 1991, Conference Proceedings 1991 IEEE International Conference on Systems, Man, and Cybernetics.

[4]  A. M. Ireland,et al.  Object-oriented model integration in a financial decision support system , 1991, Decis. Support Syst..

[5]  A. Kaufman,et al.  Introduction to the Theory of Fuzzy Subsets. , 1977 .

[6]  Syed Shahabuddin.  Expert systems and forecasting , 1990 .

[7]  F. Golshani,et al.  Uncertain reasoning using the Dempster-Shafer method: an application in forecasting and marketing management , 1990 .

[8]  R. Pohlman,et al.  Cash Flow Estimation Practices of Large Firms , 1988 .

[9]  Madan M. Gupta,et al.  Fuzzy automata and decision processes , 1977 .

[10]  G. Klir,et al.  Fuzzy Measure Theory , 1993 .

[11]  Liya Ding,et al.  Approximate case-based reasoning on neural networks , 1994, Int. J. Approx. Reason..

[12]  Christopher M. Miller,et al.  Applying case-based reasoning to forecasting retail sales , 1993 .

[13]  David F. D'Attilio.  Net Working Capital Forecasting at Dupont , 1992 .

[14]  Stephen Slade,et al.  Case-Based Reasoning: A Research Paradigm , 1991, AI Mag..

[15]  John D. Johnson,et al.  A decision support system for in-sample simultaneous equation systems forecasting using artificial neural systems , 1994, Decis. Support Syst..

[16]  Jed Marti,et al.  Scripting highly autonomous simulation behavior using case-based reasoning , 1992, Annual Simulation Symposium.

[17]  Alan E. Singer,et al.  DCF without forecasts , 1994 .

[18]  Jed Marti,et al.  Scripting highly autonomous simulation behavior using case-based reasoning , 1992, Proceedings. 25th Annual Simulation Symposium.

[19]  A. Bonaert.  Introduction to the theory of Fuzzy subsets , 1977, Proceedings of the IEEE.

[20]  James C. Van Home.  Fundamentals of Financial Management , 1977 .

[21]  James F. Baldwin,et al.  Evidential support logic, FRIL and case based reasoning , 1993, Int. J. Intell. Syst..

[22]  Agnar Aamodt,et al.  Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches , 1994, AI Commun..

[23]  Christopher K. Riesbeck,et al.  Inside Case-Based Reasoning , 1989 .

[24]  William Loscalzo.  Cash flow forecasting , 1982 .

[25]  Vincent A. Mabert,et al.  Constrained Forecasting: Some Implementation Guidelines , 1992 .

[26]  Janet L. Kolodner,et al.  Case-Based Reasoning , 1988, IJCAI 1989.

[27]  Edward Yourdon,et al.  Object-oriented analysis , 2012 .

[28]  Madan M. Gupta,et al.  Approximate reasoning in expert systems , 1985 .

[29]  Alejandro Martins,et al.  Object Oriented Analysis and Programming for a Working Capital Management System 1 , 1995 .

[30]  Robert Scott,et al.  An intelligent forecasting support system in auditing: expert system and neural network approach , 1994, 1994 Proceedings of the Twenty-Seventh Hawaii International Conference on System Sciences.

[31]  Paul Herbig,et al.  The do's and don'ts of sales forecasting , 1993 .

[32]  T.S.L. Lo.  An expert system for choosing demand forecasting techniques , 1994 .