Applied Aspects of Neural Modeling in the Process of Diagnosing the Capital of Agricultural Enterprises

The aim of the article is to study and disclose the possibility of using neural network modeling in the process of diagnosing the capital of agricultural enterprises. Systematized theoretical and practical aspects of the use of neural models in the economy. Using the graphical method implemented graphic illustration of the modeling process. The study used structural-logic method and regression analysis. As the result of the study a neural model of diagnosing capital of agricultural enterprises is built. As the initial data for modeling taken components of equity and performance indicators - net profit (loss) of the enterprise. It is proved that the most appropriate architecture and parameters for modeling the impact of the components of equity in the financial result is a multilayer perceptron. Implemented the forecast of change in net profit from the changes in the components of equity. It is proved that the use of artificial neural networks in the process of diagnosing the capital will facilitate the adoption of effective management decisions.