{"title":"利用神经网络计算机系统分析浮游植物种群的流式细胞术数据","authors":"D. Frankel, R. Olson, S. Frankel, S. Chisholm","doi":"10.1109/IJCNN.1989.118316","DOIUrl":null,"url":null,"abstract":"Summary form only given. A description is given of the application of neural net computer technology to the analysis of flow cytometry data. Although the data used in this study are from oceanographic research, the results are general and should be directly applicable to flow cytometry data or any sort. The neural network described offers the advantages of adaptability to changing conditions and potential real-time analysis. High accuracy and processing speed, near that required for real-time classification, have been achieved in a software simulation of the neural network on a Macintosh SE personal computer.<<ETX>>","PeriodicalId":199877,"journal":{"name":"International 1989 Joint Conference on Neural Networks","volume":"123 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1989-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"69","resultStr":"{\"title\":\"Use of a neural net computer system for analysis of flow cytometric data of phytoplankton populations\",\"authors\":\"D. Frankel, R. Olson, S. Frankel, S. Chisholm\",\"doi\":\"10.1109/IJCNN.1989.118316\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Summary form only given. A description is given of the application of neural net computer technology to the analysis of flow cytometry data. Although the data used in this study are from oceanographic research, the results are general and should be directly applicable to flow cytometry data or any sort. The neural network described offers the advantages of adaptability to changing conditions and potential real-time analysis. High accuracy and processing speed, near that required for real-time classification, have been achieved in a software simulation of the neural network on a Macintosh SE personal computer.<<ETX>>\",\"PeriodicalId\":199877,\"journal\":{\"name\":\"International 1989 Joint Conference on Neural Networks\",\"volume\":\"123 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1989-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"69\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International 1989 Joint Conference on Neural Networks\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IJCNN.1989.118316\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International 1989 Joint Conference on Neural Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IJCNN.1989.118316","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Use of a neural net computer system for analysis of flow cytometric data of phytoplankton populations
Summary form only given. A description is given of the application of neural net computer technology to the analysis of flow cytometry data. Although the data used in this study are from oceanographic research, the results are general and should be directly applicable to flow cytometry data or any sort. The neural network described offers the advantages of adaptability to changing conditions and potential real-time analysis. High accuracy and processing speed, near that required for real-time classification, have been achieved in a software simulation of the neural network on a Macintosh SE personal computer.<>