{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,2]],"date-time":"2025-08-02T18:10:19Z","timestamp":1754158219295,"version":"3.41.2"},"reference-count":28,"publisher":"Emerald","issue":"1","license":[{"start":{"date-parts":[[2019,11,1]],"date-time":"2019-11-01T00:00:00Z","timestamp":1572566400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["GS"],"published-print":{"date-parts":[[2019,11,1]]},"abstract":"<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title>\n<jats:p>The purpose of this paper is to propose a grey clustering model based on kernel and information field to deal with the situation in which both the observation values and the turning points of the whitenization weight function are interval grey numbers.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title>\n<jats:p>First, the \u201cunreduced axiom of degree of greyness\u201d was expanded to obtain the inference of \u201cinformation field not-reducing\u201d. Then, based on the theoretical basis of inference, the expression of whitenization weight function with interval grey number was provided. The grey clustering model and fuzzy clustering model were compared to analyse the relationship and difference between the two models. Finally, the paper model and the fuzzy clustering model were applied to the example analysis, and the interval grey number clustering model was established to analyse the influencing factors of regional drought disaster risk in Henan Province.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Findings<\/jats:title>\n<jats:p>The example analysis results illustrate that although the two clustering methods have different theoretical basis, they are suitable for dealing with complex systems with uncertainty or grey characteristic, solving the problem of incomplete system information, which has certain feasibility and rationality. The clustering results of case study show that five influencing factors of regional drought disaster risk in Henan Province are divided into three classes, consistent with the actual situation, and they show the validity and practicability of the clustering model.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title>\n<jats:p>The paper proposes a new whitenization weight function with interval grey number that can transform interval grey number operations into real number operations. It not only simplifies the calculation steps, but it has a great significance for the \u201csmall data sets and poor information\u201d grey system and has a universal applicability.<\/jats:p>\n<\/jats:sec>","DOI":"10.1108\/gs-08-2019-0029","type":"journal-article","created":{"date-parts":[[2019,11,6]],"date-time":"2019-11-06T04:32:43Z","timestamp":1573014763000},"page":"56-67","source":"Crossref","is-referenced-by-count":7,"title":["Grey clustering model based on kernel and information field"],"prefix":"10.1108","volume":"10","author":[{"given":"Dang","family":"Luo","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9360-3315","authenticated-orcid":false,"given":"Zhang","family":"Huihui","sequence":"additional","affiliation":[]}],"member":"140","reference":[{"issue":"2","key":"key2020011415260584400_ref001","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1108\/IJICC-04-2017-0038","article-title":"A fuzzy trust-based routing model for mitigating the 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