RFID-based logistics big data asset evaluation and data mining research

نویسندگان

چکیده

Abstract With the rapid rise of e-commerce platforms, in view sharp increase amount data logistics system, timely update and processing relevant information have assumed a particular relevance. In this paper, we fully draw on excellent performance radio frequency identification (RFID) technology mining technology, begin by using RFID to authenticate commodities, move extracting feature finally carry out detailed comparison between k-nearest neighbour algorithm, support vector machine (SVM) logistic regression (LR) algorithm improved LR algorithm. The provides solution method for asset collection channel classification It meets needs different customers, variety working modes, which helps improve time operation efficiency algorithms. results show that SVM only achieves 93.8% accuracy when iterating 50 times samples containing objective functions x 1 2 . stochastic gradient descent has 94.6% after iterations. RFID-based big evaluation research obvious advantages, rate reaches 97.3%.

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ژورنال

عنوان ژورنال: Applied mathematics and nonlinear sciences

سال: 2022

ISSN: ['2444-8656']

DOI: https://doi.org/10.2478/amns.2021.2.00236