Developing a Neural Networks Model for Evaluating Financial Performance of Residential Companies based on FCM

Abstract

Intense competition among construction companies urges for continuous improvement and evaluation of performance. Many researches recognized the importance of financial performance (FP) and attempted to develop a reliable model to evaluate the company FP. The main objective of this research is developing an accurate model to evaluate the financial performance of residential construction companies. Financial data of a number of residential construction companies were collected from the Egyptian Authority of Money Market in the form of balance sheets and income statement. The most six ratios affecting company financial performance were identified and calculated. Every financial point (case) defined with six financial ratios. The financial ratios represent the model input while the model output, i.e. performance index, is developed using fuzzy c-mean clustering (FCM). Artificial Neural Network (ANN) is utilized to develop the relation between the input and output variables. Some points were kept for the purpose of testing the validity of the developed model. The validation of the model showed satisfactory results which provide a sufficientdegree of reliability to use the model in evaluating the financial performance of construction companies.