Abstract
Modern information technologies such as big data and cloud computing are increasingly important and widely applied in engineering and management. In terms of cold chain logistics, data mining also exerts positive effects on it. Specifically, accurate prediction of cold chain logistics demand is conducive to optimizing management processes as well as improving management efficiency, which is the main purpose of this research. In this paper, we analyze the existing problems related to cold chain logistics in the context of Chinese market, especially the aspect of demand prediction. Then, we conduct the mathematical calculation based on the neural network algorithm and grey prediction. Two forecasting models are constructed with the data from 2013 to 2019 by R program 4.0.2, aiming to explore the cold chain logistics demand. According to the results estimated by the two models, we find that both of models show high accuracy. In particular, the prediction of neural network algorithm model is closer to the actual value with smaller errors. Therefore, it is better to consider the neural network algorithm as the first choice when constructing the mathematical forecasting model to predict the demand of cold chain logistic, which provides a more accurate reference for the strategic deployment of logistics management such as optimizing automation and innovation in cold chain processes to adapt to the trend.
Highlights
With the economic growth and social development, people’s living standard has been steadily improved these years
There are increasingly consumers that have updated view of health and consumption. ey tend to focus on a higher level of life quality such as the requirements of freshness and varieties when selecting and purchasing product, which greatly promoted the vigorous development of cold chain logistics
Cold chain logistics is a special category of supply chain logistics, depending on the refrigeration technology to keep products in the specified temperature environment during the process from production period, circulation period, to sale period
Summary
With the economic growth and social development, people’s living standard has been steadily improved these years. As the social distance became one of the important factors of consumer behaviour, “Contactless” distribution is more and more popular and adopted widely to the logistic development under this special situation, which made many electronic e-business platforms providing fresh products emerge blowout growth in the epidemic situation Faced with such a huge flow of market demand, the problems of cold chain logistics industry are more severe, such as the instability of product supply, shortage of personnel, lack of transport capacity, system collapse, and other issues that need to be solved. Is paper provides more accurate and effective prediction methods by constructing the neural network algorithm model based on data mining, so as to promote the progress of society and the development of cold chain logistics engineering and management According to the mathematical logic of grey prediction and neural network algorithm, relevant program codes with R language are created and run to establish prediction models. en, we compare the prediction effect of the two and find out the relatively better prediction model. is paper provides more accurate and effective prediction methods by constructing the neural network algorithm model based on data mining, so as to promote the progress of society and the development of cold chain logistics engineering and management
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