2019 VOL.2 Aug No.4

• Title: Design of Forecast System for Agricultural Goods Intelligent Transportation Logistics Based on Big Data Analysis
• Name: Jung Daesung
• Company: Pukyong National University
• Abstract:

  The traditional agricultural product transportation logistics flow forecasting system relies too much on people's subjective experience in forecasting, and the forecasting results are not accurate enough. In order to solve this problem, based on big data analysis, a new agricultural product transportation logistics flow forecasting system is studied, and the hardware and software parts of the system are designed. The system hardware consists of five parts: data collector, data analyzer, matcher, processor and tracker. The internal composition of each build is accurately described. The software working process is information input, information analysis, information matching, information processing and information tracking. The software work flow chart is given. The working results of the research system are verified by comparison with the traditional cargo quantity prediction system. It can be seen from the experimental results that the system under study is highly intelligent and can accurately predict the amount of logistics goods transported in a short period of time, which has important guiding significance for the transportation development of agricultural products.

• Keyword: big data analysis; agricultural product transportation; intelligent transportation; logistics cargo flow; cargo flow forecastin
• DOI: 10.12250/jpciams2019040122
• Citation form: Jung Daesung.Design of Forecast System for Agricultural Goods Intelligent Transportation Logistics Based on Big Data Analysis[J]. Computer Informatization and Mechanical System, 2019, vol. 2, pp. 53-57.

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