{"title":"基于长短期记忆网络的掺假牛奶分析","authors":"Xin Li, Jiangping Liu","doi":"10.1080/00387010.2023.2194950","DOIUrl":null,"url":null,"abstract":"Abstract Taking adulterated milk as the research object, the principal component analysis method combined with long short-term memory network was used to study, aiming to find a simple and efficient rapid detection method for adulterated milk. In this paper, qualitative and quantitative analysis of adulterated milk was carried out based on near-infrared hyperspectral data (400–1000 nm). The experimental results verified the feasibility of using near-infrared hyperspectral technology to identify adulterated milk.","PeriodicalId":21953,"journal":{"name":"Spectroscopy Letters","volume":"56 1","pages":"204 - 210"},"PeriodicalIF":1.1000,"publicationDate":"2023-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Analysis of adulterated milk based on a long short-term memory network\",\"authors\":\"Xin Li, Jiangping Liu\",\"doi\":\"10.1080/00387010.2023.2194950\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract Taking adulterated milk as the research object, the principal component analysis method combined with long short-term memory network was used to study, aiming to find a simple and efficient rapid detection method for adulterated milk. In this paper, qualitative and quantitative analysis of adulterated milk was carried out based on near-infrared hyperspectral data (400–1000 nm). The experimental results verified the feasibility of using near-infrared hyperspectral technology to identify adulterated milk.\",\"PeriodicalId\":21953,\"journal\":{\"name\":\"Spectroscopy Letters\",\"volume\":\"56 1\",\"pages\":\"204 - 210\"},\"PeriodicalIF\":1.1000,\"publicationDate\":\"2023-04-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Spectroscopy Letters\",\"FirstCategoryId\":\"92\",\"ListUrlMain\":\"https://doi.org/10.1080/00387010.2023.2194950\",\"RegionNum\":4,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"SPECTROSCOPY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Spectroscopy Letters","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.1080/00387010.2023.2194950","RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"SPECTROSCOPY","Score":null,"Total":0}
Analysis of adulterated milk based on a long short-term memory network
Abstract Taking adulterated milk as the research object, the principal component analysis method combined with long short-term memory network was used to study, aiming to find a simple and efficient rapid detection method for adulterated milk. In this paper, qualitative and quantitative analysis of adulterated milk was carried out based on near-infrared hyperspectral data (400–1000 nm). The experimental results verified the feasibility of using near-infrared hyperspectral technology to identify adulterated milk.
期刊介绍:
Spectroscopy Letters provides vital coverage of all types of spectroscopy across all the disciplines where they are used—including novel work in fundamental spectroscopy, applications, diagnostics and instrumentation. The audience is intended to be all practicing spectroscopists across all scientific (and some engineering) disciplines, including: physics, chemistry, biology, instrumentation science, and pharmaceutical science.