Modeling and Designing Controller of Factors Affecting Profit in Strategic Financial Planning Using Adaptive Neural Control Method

Making more profit in organizations requires them to have accurate tools to strengthen the business for proper financial planning. So far, no comprehensive model for the financial planning of organizations with minimum deviation from predefined goals has been presented. The purpose of this study is to provide such a model to achieve more accurate management decisions. In this research, an intelligent adaptive control model has been developed using the Elman neural network adaptation algorithm in the system identification process. This model has been developed using data extracted from the official website of the Iranian Stock Exchange and Securities Organization. Some of the most important indicators of profit (as a measure of the company's financial performance) and also optimal profit amount as input and the allowable intervals of its changes to achieve the desired profit as output of the model have been determined and examined.