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Syst."],"published-print":{"date-parts":[[2024,4]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>The disaster caused by landslide is huge. To prevent the spread of the disaster to the maximum extent, it is particularly important to carry out landslide disaster treatment work. The selection of landslide disaster treatment alternative is a large scale group decision-making (LSGDM) problem. Because of the wide application of social media, a large number of experts and the public can participate in decision-making process, which is conducive to improving the efficiency and correctness of decision-making. A IF-TW-LSGDM method based on three-way decision (TWD) and intuitionistic fuzzy set (IFS) is proposed and applied to the selection of landslide treatment alternatives. First of all, considering that experts and the public participate in the evaluation of LSGDM events, respectively, the method of obtaining and handling the public evaluation information is given, and the information fusion approach of the public and experts evaluation information is given. Second, evaluation values represented by fuzzy numbers are converted into intuitionistic fuzzy numbers (IFNs), and the intuitionistic fuzzy evaluation decision matrix described by IFNs is obtained. Then, a new LSGDM method of alternatives classification and ranking based on IFS and TWD is proposed, the calculation steps and algorithm description are given. In this process, we first cluster the experts, then consider the identification and management of non-cooperative behavior of expert groups. This work provides an effective method based on LSGDM for the selection of landslide treatment alternatives. Finally, the sensitivity of parameters is analyzed, and the feasibility and effectiveness of this method are compared and verified.<\/jats:p>","DOI":"10.1007\/s40747-023-01307-w","type":"journal-article","created":{"date-parts":[[2024,1,10]],"date-time":"2024-01-10T09:02:11Z","timestamp":1704877331000},"page":"3041-3056","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Selection of landslide treatment alternatives based on LSGDM method of TWD and IFS"],"prefix":"10.1007","volume":"10","author":[{"given":"Fang","family":"Liu","sequence":"first","affiliation":[]},{"given":"Zhongli","family":"Zhou","sequence":"additional","affiliation":[]},{"given":"Jin","family":"Wu","sequence":"additional","affiliation":[]},{"given":"Chengxi","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Yi","family":"Liu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,1,10]]},"reference":[{"key":"1307_CR1","doi-asserted-by":"publisher","DOI":"10.1016\/j.earscirev.2020.103225","volume":"207","author":"A Merghadi","year":"2020","unstructured":"Merghadi A, Yunus AP, Dou J et al (2020) Machine learning methods for landslide susceptibility studies: a comparative overview of algorithm performance. 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