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Research and analysis of deep learning algorithms for investment decision support model in electronic commerce

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Abstract

In order to improve the accuracy of e-commerce decision-making, this paper proposes an investment decision-making support model in e-commerce based on deep learning calculation to support the company. Investment decision-making system is not only an important means of enterprise investment and financing, but also an important way for investors to make profits. It also plays an important role in macroeconomic regulation, resource allocation and other aspects. This paper takes investment data related to Internet and e-commerce business as the research object, studies the theory and method of investment decision-making quality evaluation at home and abroad, and puts forward a prediction model of company decision-making quality evaluation based on deep learning algorithm, aiming at providing decision support for investors. Then a neural network investment quality evaluation model is constructed, including model structure, parameters and algorithm design. The experimental data are input into training, and the data processing process and prediction results are displayed. Experiments show that the evaluation indexes of prediction model is mainly used to judge the quality of investment of Internet or commercial enterprises. Based on this deep learning model, various index data of enterprises are analyzed, which can assist investors in decision-making.

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  1. School of Economics, Liaoning University, Shenyang, 110036, Liaoning Province, China

    Zhizhong Lei

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Lei, Z. Research and analysis of deep learning algorithms for investment decision support model in electronic commerce. Electron Commer Res 20, 275–295 (2020). https://doi.org/10.1007/s10660-019-09389-w

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