{"title":"量化城市生活垃圾堆肥效果的模糊概率模型","authors":"S. Mohurle, M. Devare","doi":"10.1109/ICNTE44896.2019.8945830","DOIUrl":null,"url":null,"abstract":"This work illuminates the machine learning based fuzzy probability model for calculating the compost usability index and measuring its quality. The work reviews the basic concept of fuzzy theory and probability; status of Municipal waste and applications of fuzzy probability. Further work proposes Fuzzy-Probability Model to quantifying the compost quality by analyzing the compost data. Input variables are set of mineral nutrients and its composition in a sample. The output of (FPM) proposed system is the Quality Index of Compost $(C_{i})$ (i.e. measures of the proportion of all elements available in compost and generate an index accordingly, a numeric value) that describes the quality of compost asserting that even if the expertise describes suitability of values in a particular sample of compost, the quality decided by expert may be approximate, assumed or predicted. The results and conclusion show that the proposed FPM system gives a programming model that helps to generate a quality index for agriculture stakeholders to believe in a particular type of compost.","PeriodicalId":292408,"journal":{"name":"2019 International Conference on Nascent Technologies in Engineering (ICNTE)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Fuzzy Probability Model for Quantifying the Effectiveness of the MSW Compost\",\"authors\":\"S. Mohurle, M. Devare\",\"doi\":\"10.1109/ICNTE44896.2019.8945830\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This work illuminates the machine learning based fuzzy probability model for calculating the compost usability index and measuring its quality. The work reviews the basic concept of fuzzy theory and probability; status of Municipal waste and applications of fuzzy probability. Further work proposes Fuzzy-Probability Model to quantifying the compost quality by analyzing the compost data. Input variables are set of mineral nutrients and its composition in a sample. The output of (FPM) proposed system is the Quality Index of Compost $(C_{i})$ (i.e. measures of the proportion of all elements available in compost and generate an index accordingly, a numeric value) that describes the quality of compost asserting that even if the expertise describes suitability of values in a particular sample of compost, the quality decided by expert may be approximate, assumed or predicted. The results and conclusion show that the proposed FPM system gives a programming model that helps to generate a quality index for agriculture stakeholders to believe in a particular type of compost.\",\"PeriodicalId\":292408,\"journal\":{\"name\":\"2019 International Conference on Nascent Technologies in Engineering (ICNTE)\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference on Nascent Technologies in Engineering (ICNTE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICNTE44896.2019.8945830\",\"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 Nascent Technologies in Engineering (ICNTE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNTE44896.2019.8945830","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fuzzy Probability Model for Quantifying the Effectiveness of the MSW Compost
This work illuminates the machine learning based fuzzy probability model for calculating the compost usability index and measuring its quality. The work reviews the basic concept of fuzzy theory and probability; status of Municipal waste and applications of fuzzy probability. Further work proposes Fuzzy-Probability Model to quantifying the compost quality by analyzing the compost data. Input variables are set of mineral nutrients and its composition in a sample. The output of (FPM) proposed system is the Quality Index of Compost $(C_{i})$ (i.e. measures of the proportion of all elements available in compost and generate an index accordingly, a numeric value) that describes the quality of compost asserting that even if the expertise describes suitability of values in a particular sample of compost, the quality decided by expert may be approximate, assumed or predicted. The results and conclusion show that the proposed FPM system gives a programming model that helps to generate a quality index for agriculture stakeholders to believe in a particular type of compost.