Cash Flow Forecasting Using Probabilistic Neural Networks

Authors

Marwan Ashour, University of Baghdad - IraqFollow

Abstract

This paper aimed to compare the modern methods of cash flow forecasting with the traditional ones. In other words, the researcher compared between the Probabilistic Neural Networks and Transfer Function. It is worth mentioning that cash flow forecasting , nowadays, is very important and helps the upper management plan, control, assess the performance and make decisions. More specifically, in this paper, the Artificial Neural networks were used to diagnose the nature of the cash flow for the next period of time and then forecast the cash flow. The experiment was conducted in The General company for Electricity Distribution in Baghdad. The study found out that the best type of cash flow forecasting is the Probabilistic Neural Networks, which provide a robust and flexible tool for processing since they are characterized for being self-adaptive and qualitative.

Recommended Citation

Ashour, Marwan (2019) "Cash Flow Forecasting Using Probabilistic Neural Networks," Journal of the Arab American University مجلة الجامعة العربية الامريكية للبحوث: Vol. 5: Iss. 1, Article 3.
Available at: https://digitalcommons.aaru.edu.jo/aaup/vol5/iss1/3