Novel Aggregation Functions Based on Domain Partition with Concentrate Region of Data

Hengshan Zhang, Tianhua Chen, Zhongmin Wang, Yanping Chen

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Combining numerous input arguments, specially in case most arguments lie in a concentrate region, is a complex issue. This chapter proposes to partition the input domain on the basis of the concentrate region, which can then be tackled based on the sub regions. Furthermore, two bi-variate aggregation functions are proposed, which aim to behave differently in response to the corresponding sub-regions. The bi-variate functions are extended further into multivariate functions in combination with the popular Ordered Weighted Averaging OWA operators. Finally, the proposed aggregation functions are assessed using a case study where the maintainability of the Linux Kernels is evaluated, demonstrating the effectiveness of the proposed functions.
Original languageEnglish
Title of host publicationFuzzy Logic
Subtitle of host publicationRecent Applications and Developments
EditorsJenny Carter, Francisco Chiclana, Arjab Singh Khuman, Tianhua Chen
PublisherSpringer Nature Switzerland AG
Chapter8
Pages107-129
Number of pages23
Edition1
ISBN (Electronic)9783030664749
ISBN (Print)9783030664732, 9783030664763
DOIs
Publication statusPublished - 24 May 2021

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