Research and application of intelligent matching method for manufacturing resources based on cloud platform

被引：0
|
作者：
Zheng J. [1 ]
Cao H. [1 ]
Li H. [2 ]
Cheng E. [1 ]
Zhu L. [3 ]
Xing B. [3 ]
机构：
[1] State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing
[2] School of Advanced Manufacturing Engineering, Chongqing University of Posts and Telecommunications, Chongqing
[3] Chongqing Big Data Innovation Center Co., Ltd., Chongqing
来源：
Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS | 2022年 / 28卷 / 12期
关键词：
adaptive time estimation algorithm; area under curve model; cloud platform; joint embedded convolutional neural network; manufacturing resource; term vectors;
D O I：
10.13196/j.cims.2022.12.004
中图分类号：
学科分类号：
摘要：
To improve the utilization efficiency of manufacturing resources, it is required to connect and dynamically match manufacturing services of discrete distributed manufacturing resources rapidly and effectively under intelligent manufacturing environment. The feature description and vector extraction of manufacturing resources and user demands were carried out through word vector modeling on the cloud platform, and the word vectors of manufacturing resources and user demands were mapped to the public space with vector matching basis by using Joint Embedded Convolutional Neural Network (JE-CNN). The objective function was constructed based on the matching distance of two groups of word vectors, and the objective function was optimized by Adaptive time estimation (Adam) algorithm, and then the matching degree was judged according to the binary classification Area Under Curve (AUC) model, so as to realize the high quality and high efficiency matching of manufacturing resources. The feasibility of the proposed method was verified by an example. © 2022 CIMS. All rights reserved.
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页码：3747 / 3757
页数：10
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