Abstract. Credit is very important for the enterprise, analysis of a comprehensive evaluation of enterprise credit, can enhance the risk control ability of enterprise credit, improve enterprise credit rating.The paper establishes BP neural network credit evaluation model based on genetic algorithm (GA)optimization ,and to the power supply enterprise credit evaluation as an example, to verify the practicability of the model in the evaluation of enterprise credit. Examples of verification results indicate that the genetic algorithm (GA) to optimize the BP neural network is better than traditional BP neural network , it's evaluation has higher accuracy, stronger generalization ability, more suitable for the enterprise credit evaluation.
The shortest path problem is a classical problem in graph theory, it is also one of the classical problems in the field of combinatorial optimization. This paper analyzes the basic harmony search algorithm model, and points out its insufficiency in solving the shortest path problem, then modifies the harmony memory and perturbation method. The simulation experiment shows that the improved harmony search algorithm (IHSA) has faster global convergence speed, and can obtain more accurate optimal path. IHSA is an effective solution to solve the shortest path problem.
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