稳健的集合代用模型及其在联合收割机现场数据建模和分析中的应用

IF 2.2 3区工程技术 Q2 ENGINEERING, MULTIDISCIPLINARY

Engineering Optimization Pub Date : 2023-12-07 DOI:10.1080/0305215x.2023.2286509

Jinpeng Hu, Chaoyong Zong, Maolin Shi, Liying Wang, Qiushi Bi, Lizhang Xu

引用次数: 0

摘要

本文提出了一种基于扩展自适应混合函数和模糊聚类的稳健集合模型。在离群点检测阶段，每个样本都会被分配成员，以判断离群点的大小。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Engineering Optimization 管理科学-工程：综合

CiteScore

5.90

自引率

7.40%

发文量

审稿时长

3.5 months

期刊介绍： Engineering Optimization is an interdisciplinary engineering journal which serves the large technical community concerned with quantitative computational methods of optimization, and their application to engineering planning, design, manufacture and operational processes. The policy of the journal treats optimization as any formalized numerical process for improvement. Algorithms for numerical optimization are therefore mainstream for the journal, but equally welcome are papers which use the methods of operations research, decision support, statistical decision theory, systems theory, logical inference, knowledge-based systems, artificial intelligence, information theory and processing, and all methods which can be used in the quantitative modelling of the decision-making process. Innovation in optimization is an essential attribute of all papers but engineering applicability is equally vital. Engineering Optimization aims to cover all disciplines within the engineering community though its main focus is in the areas of environmental, civil, mechanical, aerospace and manufacturing engineering. Papers on both research aspects and practical industrial implementations are welcomed.