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P.-C. Chang, C.-H. Liu, J.-L. Lin, C.-Y. Fan and C. S. P. Ng, “A Neural Network with a Case Based Dynamic Window for Stock Trading Prediction,” Expert Systems with Applications, Vol. 36, No. 3, 2009, pp. 6889-6898.

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• TITLE: Using Artificial Neural Network Modeling in Forecasting Revenue: Case Study in National Insurance Company/Iraq

  AUTHORS: Itedal Sabri Hashim Bahia

  KEYWORDS: ANN; Regression Analysis; Forecasting Revenue; National Insurance Company

  JOURNAL NAME: International Journal of Intelligence Science, Vol.3 No.3, July 9, 2013

  ABSTRACT: There are few changes that took place in Iraqin many fields during the past few years; the financial aspect is one of the fields that undergone this change. The change has positive impact because it increases the revenue inIraqfrom the oil exports. The National Insurance Company is one of many companies that belongs to the Ministry of Finance inIraqand has affected directly from this change in term of increasing the number of the insurers which we will discuss in this research. The aim of this research is to forecast the insurance premiums revenue of the National Insurance Company between the years 2012 to 2053 using Artificial Neural Network based on the actual annual data of the insurance premiums revenue between the years 1970 to 2011. The data analyses results of this research show that the growth indicator of the insurance premiums revenue for the next 41 years is approximately 120%, the Mean Squared Error is the average squared difference between outputs and targets. Lower values are better. Zero means no error and the regression values are very high. The estimations and forecasts of the insurance premiums revenue using Artificial Neural Network confirmed to be strong and useful to deploy it for forecasting the insurance premiums revenue.