Abstract
Abstract With the improvement of people’s living quality, more attention has been paid in food safety and quality. This is especially true for perishable agricultural and dairy products. It is quite often that customers receive poor or broken products due to mistakes or wrong ways in transportation. This leads customers the unsatisfied for companies’ products are relatively low. To solve the above problem, this paper proposes a new approach of using frequent closed sequential mining technology to analysis logistics data for helping companies to track the possible transportation problems. The approach consists of several important steps: RFID-enabled raw data collection, frequent sequential patterns mining, and patterns analysis. The experiment shows the proposed analysis method can discover many inside transportation service causes.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
