Evaluation of e-commerce website based on fruit fly algorithm optimization RBF algorithm

Gang Lu

School of Management Science and Engineering, Shijiazhuang University of Economics, Shijiazhuang 050031, China

The feature and various index properties of E-commerce website are considered as a whole by applying the expert grading method, with the construction of the multi-index hierarchical structure of an E-commerce website competitiveness index evaluation and the establishment of an E-commerce website competiveness index evaluation index system. The competiveness level of the website is quantified after calculating the competiveness index of the E-commerce website. On this basis, this work adopted Radial Basis Function (RBF) neural network algorithm to perform evaluation research on the competiveness index of E-commerce website. Aiming at the problems exist in the evaluation research, this work tried to use Fruit Fly Optimization Algorithm (FOA) to perform improvement on the RBF neural network algorithm. Through the simulation and comparison of practical examples, FOA-RBF algorithm is obviously better than RBF neural network algorithm when the E-commerce website competiveness index is calculated and evaluated, thus the validity and reliability of calculating method presented in this work are verified.