{"title":"基于概率-可能性-均值(离散数据挖掘算法)的数据挖掘新方法","authors":"A. Tiwari, G. Ramakrishna, L. Sharma, S. Kashyap","doi":"10.1109/ICCCIS48478.2019.8974501","DOIUrl":null,"url":null,"abstract":"The possibilistic mean is reviewed in this paper for prediction of academic data. The mean values of the probabilistic study of the possibilistic mean is classified by fuzzy numbers is the main result of this paper. This result is applied on the prediction of the academic performance over the academic data. Basically, this paper presents an analysis of academic data by fuzzy numbers. The variance of fuzzy numbers classes the big data into dynamic and compact data. This system performs efficiently over the various characteristic of fuzzy numbers. The illustration is also presented in this paper.","PeriodicalId":436154,"journal":{"name":"2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"New Data Mining Method based on Probabilistic-Possibilistic-Mean (Discrete Data Mining Algorithm)\",\"authors\":\"A. Tiwari, G. Ramakrishna, L. Sharma, S. Kashyap\",\"doi\":\"10.1109/ICCCIS48478.2019.8974501\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The possibilistic mean is reviewed in this paper for prediction of academic data. The mean values of the probabilistic study of the possibilistic mean is classified by fuzzy numbers is the main result of this paper. This result is applied on the prediction of the academic performance over the academic data. Basically, this paper presents an analysis of academic data by fuzzy numbers. The variance of fuzzy numbers classes the big data into dynamic and compact data. This system performs efficiently over the various characteristic of fuzzy numbers. The illustration is also presented in this paper.\",\"PeriodicalId\":436154,\"journal\":{\"name\":\"2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCCIS48478.2019.8974501\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCIS48478.2019.8974501","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
New Data Mining Method based on Probabilistic-Possibilistic-Mean (Discrete Data Mining Algorithm)
The possibilistic mean is reviewed in this paper for prediction of academic data. The mean values of the probabilistic study of the possibilistic mean is classified by fuzzy numbers is the main result of this paper. This result is applied on the prediction of the academic performance over the academic data. Basically, this paper presents an analysis of academic data by fuzzy numbers. The variance of fuzzy numbers classes the big data into dynamic and compact data. This system performs efficiently over the various characteristic of fuzzy numbers. The illustration is also presented in this paper.