Application of Deep Learning to Production Forecasting in Intelligent Agricultural Product Supply Chain

Production prediction is an important factor influencing the realization of an intelligent agricultural supply chain.In an Internet of Things(IoT)environment,accurate yield prediction is one of the prerequisites for achieving an efficient response in an intelligent agricultural supply chain.As an example,this study applied a conventional prediction method and deep learning prediction model to predict the yield of a characteristic regional fruit(the Shatian pomelo)in a comparative study.The root means square error(RMSE)values of regression analysis,exponential smoothing,grey prediction,grey neural network,support vector regression(SVR),and long short-term memory(LSTM)neural network methods were 53.715,6.707,18.440,1.580,and 1.436,respectively.Among these,the mean square error(MSE)values of the grey neural network,SVR,and LSTM neural network methods were 2.4979,31.652,and 2.0618,respectively;and theirRvalues were 0.99905,0.94,and 0.94501,respectively.The results demonstrated that the RMSE of the deep learning model is generally lower than that of a traditional prediction model,and the prediction results are more accurate.The prediction performance of the grey neural network was shown to be superior to that of SVR,and LSTM neural network,based on the comparison of parameters.

Application of Distributed Intelligent Power Supply Technology in Expressway Tunnels

With the coordinated development of today's social economy with science and technology,various advanced technologies are being used in highway engineering,especially the distributed intelligent power supply technology in expressway tunnels,which has a very significant advantage.In order to realize the effective application of this technology and promote the power supply effect in expressway tunnel,this study analyzes the advantages of this technology and its application in expressway tunnel,hoping to provide scientific reference for the application of distributed intelligent power supply technology and the engineering development of expressway tunnels.

Guest editorial of “Intelligent logistics and supply chains”

Information and communication technology （ICT） has been considered as an enabling tool for having more effective and efficient operations in the management of logistics and supply chains for many years. Various information and communication technologies are used to improve perfor- mance of the logistics and supply chain network, such as ＂data mining＂, ＂radio frequency identification （RFID）＂, ＂machine learning＂, ＂smart transportation＂. While ICT systems are vital components in logistics and supply chains, their successful management rests on intelligent and inte- grated decision making throughout the logistics network. Intelligent decision technologies are applied to collect and store real-time data and then analyze and interpret the data and information of product, inventory, manufacturing and sales to discover useful knowledge for making better operation and management decisions. Advanced simulation and optimization of planning and scheduling systems are also used for improvement of inventory, production, pro-curement, and distribution planning. Intelligent agents can communicate with different partners in the supply chain, assist in collecting information, share product information, negotiate prices, and distribute alerts throughout the logis- tics and supply chains networks.