Construction of Value Chain E-Commerce Model Based on Stationary Wavelet Domain Deep Residual Convolutional Neural Network - Chenyuan Wang (Complexity)
This paper mainly analyzes the current situation of e-commerce in domestic SMEs and points out that there are limited initial investment and difficulty in financing in China’s SMEs; e-commerce control is not scientific; e-commerce personnel of SMEs are not of high quality, in the case of improper setting of the e-commerce sector and shortage of talents, rigid management model, and outdated management concepts. By using the loss function and the value chain management theory of the deep learning in the stationary wavelet domain residual learning model, the e-commerce model of SMEs is newly constructed, and the e-commerce department as the core department of the enterprise is proposed. By training the optimal parameters of the deep residual network and comparing the results with other models, the method of this paper has a good effect against the sample. The original loss function based on the residual learning model deep learning is modified to solve the original model fuzzy problem, which improves the effect and has good robustness. Finally, based on the wavelet residual depth residual evaluation method, this paper evaluates the application effect of this model and proposes relevant suggestions for improving this model, including rationalizing and perfecting the external value chain coordination mechanism, establishing the e-commerce value chain sharing center, and promoting integration of e-commerce business, strengthening measures and recommendations in various aspects of e-commerce information construction. At last, taking the business activities of a company as an example, applying the theory described in this paper to specific practice proves the feasibility and practical value of the theory.