Urban cold-chain logistics demand predicting model based on improved neural network model

Abstract

With the popularity of the Internet and mobile terminals, the development of e-commerce has become hotter. Therefore, e-commerce research starts to focus on the statistics and prediction of the cargo volume of logistics. This study briefly introduced the back-propagation (BP) neural network model and principal component analysis (PCA) method and combined them to obtain an improved PCA-BP neural network model. Then the traditional BP neural network model and the improved PCA-BP neural network model were used to perform the empirical analysis of the cold chain logistics demand of fruits and vegetables in city A from 2010 to 2018. The results showed that the main factors that affected the local cold chain logistics demand were the growth rate of GDP, the added value of primary industry, the planting area of fruits and vegetables, and the consumption price index of fruits and vegetables; both kinds of neural networks model could effectively predict the cold chain logistics demand, but the predicted value of the PCA-BP neural network model was more fitted with the actual value. The prediction error of the BP neural network model was larger, and the fluctuation was obvious within the prediction interval. Moreover, the time required for the prediction by the PCA-BP neural network model was less than that by the BP neural network model. In summary, the improved PCA-BP neural network model is faster and more accurate than the traditional BP model in predicting the cold chain logistics demand.

Performance of cold chain logistics service providers in the fast-moving consumer goods industry in Nigeria: a systematic review

“…Logistics service providers face numerous challenges in delivering quality, effective, efficient and reliable services [47], [67][68][69] these challenges range from infrastructure problems, technological problems, product temperature monitoring, tracking, and tracing, information management, coordinating real time information and energy efficiency problems. A study by [70] suggests that improving the cold-chain logistics system through use of intelligent methods.…”

“…However, the performance of cold chain logistics service providers in the Nigeria tomatoes value chain is impeded by inadequate Infrastructure development, poor technology adoption, absence of regulatory frameworks and non-compliance with established forms of regulatory norms, limited industry collaboration, financial constraint and professional skills deficiencies in the industry [16], [17], [19], [20], [85], [86]. Thus, improving the state of chain logistics infrastructure and technological limitations, implementing innovative solutions and adapting best practices from developed economies such as the G20 with highly advanced technologies such as the G5 Technologies, SMART technologies, Radio frequency identification device(RFID), from internet of things (IoT), internet of everything (IoE) ,with the development of cloud computing and big data technology is very important for the enhancement of cold chain logistics operations and performance in Nigeria [33], [67],…”

“…Thus, order to overcome this deficiency, a time-temperature indicator (TTI) based cold-chain logistics system with wireless sensors for collecting temperature data and formulation of Critical Control Point (CCP) criteria throughout the entire delivery process is needed. Similarly, studies of [67], [68], [113], and [114] reveal that the use temperature monitoring technologies such as wireless sensors, IoT (Internet of Things), and cloud-based platforms enables early real time detection of temperature deviations and execution of timely corrective actions to maintain product quality. Furthermore, studies by [31], [115], and [116] focused on temperature monitoring in cold storage facilities.…”

Research on the Purchase Intention of Children's Educational Products Based on Feedforward Neural Network and Factor Analysis

“…Promotion, discounts, gifts and other marketing means are a variety of ways to convey product value to consumers. First, both customer perceived value and product value are equally important in influencing consumers' purchase intention [7]. Product value mainly includes functional value, experience value, social value, perceived value and other dimensions.…”