{"title":"利用系统对不同储层细菌总数的影响分析与预测","authors":"I. Radojević, A. Ostojić, N. Stefanović","doi":"10.46793/iccbi21.064r","DOIUrl":null,"url":null,"abstract":"This study was performed using the SeLaR information system (IS). SeLaR IS combines relevant data on reservoirs in Serbia and enables advanced methods of analysis, such as statistical analysis and data mining. For the data analysis, three accumulations with different morphometric properties, trophic status, and dominant community of microorganisms were selected: Gruža, Grošnica, and Bovan. The material in this research is data sets that include standard routine and broader scientific hydrobiological tests of freshwater from certain periods. The data include physicochemical, biochemical, microbiological, and other biological parameters. The analysis aimed to determine the relationship between the entities, to discover unknown relations, the regularity in the dynamics of the specific characteristics, and for predictions. Classification, analysis of influential parameters, and scenario analysis were used for this analysis. The results indicate a clear classification of the values of the total number of bacteria. The obtained models have a small number of influential parameters (one to four) with a large relative impact for each class separately. Influence parameters are different for distinct accumulations. For prediction of the total number of bacteria selected tools did not provide satisfactory results for all three reservoirs.","PeriodicalId":9171,"journal":{"name":"Book of Proceedings: 1st International Conference on Chemo and BioInformatics,","volume":"198 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"IMPACT ANALYSIS AND PREDICTION OF THE TOTAL NUMBER OF BACTERIA IN DIFFERENT RESERVOIRS USING SELAR INFORMATION SYSTEM\",\"authors\":\"I. Radojević, A. Ostojić, N. Stefanović\",\"doi\":\"10.46793/iccbi21.064r\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study was performed using the SeLaR information system (IS). SeLaR IS combines relevant data on reservoirs in Serbia and enables advanced methods of analysis, such as statistical analysis and data mining. For the data analysis, three accumulations with different morphometric properties, trophic status, and dominant community of microorganisms were selected: Gruža, Grošnica, and Bovan. The material in this research is data sets that include standard routine and broader scientific hydrobiological tests of freshwater from certain periods. The data include physicochemical, biochemical, microbiological, and other biological parameters. The analysis aimed to determine the relationship between the entities, to discover unknown relations, the regularity in the dynamics of the specific characteristics, and for predictions. Classification, analysis of influential parameters, and scenario analysis were used for this analysis. The results indicate a clear classification of the values of the total number of bacteria. The obtained models have a small number of influential parameters (one to four) with a large relative impact for each class separately. Influence parameters are different for distinct accumulations. For prediction of the total number of bacteria selected tools did not provide satisfactory results for all three reservoirs.\",\"PeriodicalId\":9171,\"journal\":{\"name\":\"Book of Proceedings: 1st International Conference on Chemo and BioInformatics,\",\"volume\":\"198 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Book of Proceedings: 1st International Conference on Chemo and BioInformatics,\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.46793/iccbi21.064r\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Book of Proceedings: 1st International Conference on Chemo and BioInformatics,","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.46793/iccbi21.064r","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
IMPACT ANALYSIS AND PREDICTION OF THE TOTAL NUMBER OF BACTERIA IN DIFFERENT RESERVOIRS USING SELAR INFORMATION SYSTEM
This study was performed using the SeLaR information system (IS). SeLaR IS combines relevant data on reservoirs in Serbia and enables advanced methods of analysis, such as statistical analysis and data mining. For the data analysis, three accumulations with different morphometric properties, trophic status, and dominant community of microorganisms were selected: Gruža, Grošnica, and Bovan. The material in this research is data sets that include standard routine and broader scientific hydrobiological tests of freshwater from certain periods. The data include physicochemical, biochemical, microbiological, and other biological parameters. The analysis aimed to determine the relationship between the entities, to discover unknown relations, the regularity in the dynamics of the specific characteristics, and for predictions. Classification, analysis of influential parameters, and scenario analysis were used for this analysis. The results indicate a clear classification of the values of the total number of bacteria. The obtained models have a small number of influential parameters (one to four) with a large relative impact for each class separately. Influence parameters are different for distinct accumulations. For prediction of the total number of bacteria selected tools did not provide satisfactory results for all three reservoirs.