Performance balance oriented product structure optimization involving heterogeneous uncertainties in intelligent manufacturing with an industrial network

Zhang, Hong; Feng, Ying; Li, Zhiwu; Li, Zhongkai; Hu, Bingtao; Zhang, Zhifeng; Tan, Jianrong

doi:10.1016/j.ins.2022.03.063

Cited by 10 publications

(1 citation statement)

References 48 publications

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“…The internet under heterogeneous distribution can not only support different applications of different protocols and combine advantageous products or systems, but also meet the diverse needs of network business and improve the utilization rate of various multi-functional platforms and systems in the internet. Due to the characteristics of uncertainty, diversity, and flexibility of the internet under heterogeneous distribution, it is necessary to mine internet data under heterogeneous distribution [3,4]. Most internet data mining methods under heterogeneous distribution are unable to quickly, effectively, and accurately mine data, resulting in high packet loss rates, complex data operation processes, and computational errors during operation or operation of the internet under heterogeneous distribution.…”

Section: Introductionmentioning

confidence: 99%

Heterogeneous High Performance Data Mining System for Intelligent Data

Wang,

Li,

2024

SCPE

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In order to improve the utilization rate of internet data under heterogeneous distribution, increase the diversified usage functions and data transmission rate of the internet, and reduce the running time of the internet, it is necessary to mine internet data under heterogeneous distribution. The author proposes an ontology based optimization method for internet data mining under heterogeneous distribution; This method first preprocesses and selects data features from internet data under heterogeneous distribution, and uses a feature selection decision system to select features from the mining data. Based on this, information entropy is used to filter internet data under heterogeneous distribution. During the filtering process, the theoretical values filtered by information entropy are reduced to obtain the optimal data filtering value, finally, based on the various data information obtained in the preprocessing, the iterative calculation results of the information gain value in the decision tree generation algorithm are used to high-precision mine internet data under heterogeneous distribution; The simulation experimental results demonstrate that theproposed method improves the flexibility of internet data operations under heterogeneous distribution, increases the recyclability of internet data, and makes internet operations under heterogeneous distribution more concise and efficient, providing a strong basis for research and development in this field.

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Section: Introductionmentioning

confidence: 99%