Assessing the Investment Efficiency of Developing Complex On-Board Equipment Using Mathematical Modeling Methods

The procedure for modeling work related to the design and development of complex on-board equipment has been studied. In this study, the model is developed using machine learning algorithms, and its training is carried out based on data obtained from previous developments in this field. The model was created for two algorithms: neural network and random forest. Based on the data obtained at the design stage, it has been possible to form the electronic structure of the product in advance and then fill it in during the development process in accordance with the company's regulations. The ability to quickly obtain a predicted product structure allows you to simplify the planning process before the development stage. Using this model it is possible to carry out an accurate assessment of work.