Intelligent decision making for service providers selection in maintenance service network: An adaptive fuzzy-neuro approach

Weibo Ren, Kezhong Wu, Qiusheng Gu, Yaoguang Hu*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

34 Citations (Scopus)

Abstract

Establishment of a maintenance service network has become increasingly urgent to ensure the safety and reliability of agricultural operation in busy farming seasons. This paper aims to design the maintenance service network in agriculture and focuses on the joint selection of service providers in network nodes. A novel intelligent decision-making approach is developed based on expert knowledge and machine learning techniques. First, a set of evaluation criteria for the group of service providers is defined from both qualitative and quantitative aspects. The adaptive fuzzy-neuro approach is proposed for selection of the group of service providers. Fuzzy rules designed by experts are applied for scheme classification and adaptive neural network is developed for the modification of memberships functions. Lastly, the proposed methodology is demonstrated by designing a real maintenance service network in Hunan, China. Experimental results in real application scenarios manifest that the proposed approach provides optimal solutions for decision making and providers’ selection in a maintenance service network.

Original languageEnglish
Article number105263
JournalKnowledge-Based Systems
Volume190
DOIs
Publication statusPublished - 29 Feb 2020

Keywords

  • Evaluation criteria
  • Fuzzy-neuro approach
  • Maintenance service network
  • Service providers selection

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