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Assessment research on E-business website based on RBF algorithm optimization by fruit fly algorithm

Author(s): Chen Cao

The paper comprehensively researched characteristics and various indexes and properties of E-business websites by the expert grading method. A multi-index hierarchical structure was established for assessment of E-business website competitiveness. An assessment index system for E-business website competiveness was set up to quantize competiveness level of websites. Afterwards, the E-business websites were assessed and researched by the RBF neural network algorithm. Aiming at problems in the assessment research, RBF neural network algorithm was improved by Fruit Fly Optimization Algorithm. It was found in empirical simulation comparison that assessment of E-business websites by FOA-RBF algorithm was obviously better than RBF neural network algorithm in accuracy and handling time. In this way, effectiveness and reliability of algorithm in the paper were verified. Along with rapid development of E-business in recent years, competition has also become increasingly keen. If an E-business website can completely assess and know its competiveness, website construction will be strengthened and the website will be improved. As the premise for an enterprise to strengthen competiveness and obtain competitive advantages, such assessment and acquaintance shall also be realized at present.

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