{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T02:08:46Z","timestamp":1740103726241,"version":"3.37.3"},"reference-count":24,"publisher":"Wiley","license":[{"start":{"date-parts":[[2020,10,13]],"date-time":"2020-10-13T00:00:00Z","timestamp":1602547200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["91646112"],"award-info":[{"award-number":["91646112"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Complexity"],"published-print":{"date-parts":[[2020,10,13]]},"abstract":"<jats:p>This article innovatively builds the infrastructure of farmer credit rating index system into a multilevel unidirectional network structure. First, according to the logical structure of the three-level credit rating index system, a four-level unidirectional network is constructed, and the credit rating calculation formulas of all indexes at the four-level network are established. Furthermore, the special cases of the credit rating formula with the first- and second-level farmer credit rating index system are discussed. On this basis, it is extended to a credit rating index system with more than four levels, and the corresponding credit rating formula is established. Finally, the general formula of credit rating formula of the farmer credit rating index system from first level to multilevel is obtained. In order to solve the problem of farmers' credit rating, this paper also designs a linear segmentation classifier to classify the results of multilayer unidirectional network, establishes the rules of farmers' credit rating and the unidirectional network linear segmentation evaluation model of farmers' credit rating, and discusses the properties of bank credit based on farmers\u2019 credit rating. Finally, the model established in this paper is applied to the credit rating of farmers in <jats:inline-formula>\n                     <a:math xmlns:a=\"https:\/\/2.zoppoz.workers.dev:443\/http\/www.w3.org\/1998\/Math\/MathML\" id=\"M1\">\n                        <a:mi>A<\/a:mi>\n                     <\/a:math>\n                  <\/jats:inline-formula> County, Guangdong Province in China. When the credit rating of 160 farmers is carried out, the evaluation results are in line with the actual credit rating of farmers in <jats:inline-formula>\n                     <c:math xmlns:c=\"https:\/\/2.zoppoz.workers.dev:443\/http\/www.w3.org\/1998\/Math\/MathML\" id=\"M2\">\n                        <c:mi>A<\/c:mi>\n                     <\/c:math>\n                  <\/jats:inline-formula> County, with an accuracy of 100%. This research has the maneuverability to carry on the scientific credit rating to the countryside. This study has important method guidance and operability for rural credit rating.<\/jats:p>","DOI":"10.1155\/2020\/7096952","type":"journal-article","created":{"date-parts":[[2020,10,14]],"date-time":"2020-10-14T20:20:13Z","timestamp":1602706813000},"page":"1-13","source":"Crossref","is-referenced-by-count":1,"title":["Farmer\u2019s Credit Rating Model and Application Based on Multilayer Unified Network with Linear Classifier"],"prefix":"10.1155","volume":"2020","author":[{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0001-7190-2472","authenticated-orcid":true,"given":"Sulin","family":"Pang","sequence":"first","affiliation":[{"name":"School of Emergency Management, Institute of Finance Engineering, Jinan University, Guangzhou 510632, China"},{"name":"School of Emergency Industry, School of Economics and Management, Guangzhou Pearl-River College of Vocational Technology, Huizhou 516131, Guangdong, China"},{"name":"Guangdong Emergency Technology Research Center of Risk Evaluation and Prewarning on Public Network Security, Guangzhou 510632, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0001-5773-998X","authenticated-orcid":true,"given":"Shouyang","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Economics and Management, Chinese Academy of Sciences, Beijing 100190, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0001-9999-3513","authenticated-orcid":true,"given":"Lianhu","family":"Xia","sequence":"additional","affiliation":[{"name":"School of Emergency Industry, School of Economics and Management, Guangzhou Pearl-River College of Vocational Technology, Huizhou 516131, Guangdong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1016\/j.omega.2018.02.001"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.1016\/s0305-0548(99)00149-5"},{"volume-title":"Credit Scoring Models and the Predicting Models in Stock Market\u2013Approach of Statistics, Neural Network and Support Vector Machine","year":"2005","author":"S. 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