Research on Forecasting Model of New Retail Sales Volume Based on BP Artificial Neural Network and RBF Neural Network Algorithm

DOI

10.2991/aebmr.k.220307.160How to use a DOI?

Keywords

Pearson correlation analysis; grey correlation analysis; BP artificial neural network; RBF neural network

Abstract

With the continuous development of China’s consumer market, the production mode of new retail enterprises is gradually moving forward to multi-variety and small batch. Therefore, the importance of accurate demand forecast for sales categories is self-evident. First of all, this paper makes an analysis and judgment on the main factors affecting sales volume through Pearson correlation analysis and grey correlation analysis. Then, considering the requirements of some factors, the BP artificial neural network model is used to predict the monthly sales of the target class accurately and quickly. Finally, under the requirements of comprehensive and in-depth consideration of various factors, the sales volume of the target subcategory is refined, and the weekly sales of all skc in the subcategory are predicted by the PBF model. In this paper, an analysis model of influencing factors of sales volume based on Pearson correlation analysis and grey correlation analysis is established, and the significance of the results is tested. Then the artificial neural network model is established, and the BP algorithm is used to predict the sales volume of the target subclass. Finally, the RBF neural network model is used to predict the sales volume of skc in a specified period of time. The two elements of subclass level and skc level are comprehensively considered, which is consistent with the expected goal.

Copyright

© 2022 The Authors. Published by Atlantis Press International B.V.

Open Access

This is an open access article under the CC BY-NC license.

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TY  - CONF
AU  - Longhao Pang
PY  - 2022
DA  - 2022/03/26
TI  - Research on Forecasting Model of New Retail Sales Volume Based on BP Artificial Neural Network and RBF Neural Network Algorithm
BT  - Proceedings of the 2022 7th International Conference on Financial Innovation and Economic Development (ICFIED 2022)
PB  - Atlantis Press
SP  - 971
EP  - 975
SN  - 2352-5428
UR  - https://doi.org/10.2991/aebmr.k.220307.160
DO  - 10.2991/aebmr.k.220307.160
ID  - Pang2022
ER  -