Search

Starting from the problems of imperfect evaluation index system, non-standard evaluation method and single factor of performance evaluation model, this paper applies the unified grey clustering analysis algorithm to establish the index system of software organization status and software project characteristics, and defines the connotation of software project performance. A new network topology design method is proposed, and a software project performance evaluation model based on fuzzy neural network is established. An improved particle swarm optimization algorithm is introduced to solve the problem of determining the connection weight coefficient of the evaluation model accurately and efficiently. This paper introduces the basic concept of project performance evaluation, and explains the necessity and importance of performance evaluation in the project.

This paper introduces the general principles that should be followed in project performance evaluation: through the analysis of the main factors affecting software project performance evaluation, it provides a guiding principle for the construction of project performance evaluation index system including software project characteristics and project characteristics. The empirical study shows that the model can effectively evaluate software project performance and knowledge. It provides decision support information for software organizations to formulate risk aversion strategies, improve project performance level and other risk factors.