M. Terziyska, Zhelyazko Terziyski, S. Hadzhikoleva, E. Hadzhikolev
{"title":"PM10和PM2.5日浓度预测的多输入多输出新模糊神经网络","authors":"M. Terziyska, Zhelyazko Terziyski, S. Hadzhikoleva, E. Hadzhikolev","doi":"10.1109/BdKCSE48644.2019.9010610","DOIUrl":null,"url":null,"abstract":"Multi-Input Multi-Output Neo-Fuzzy Neural Network Structure, based on Neo-fuzzy neuron concept, is used in this study to forecast average daily PM10 and PM2.5 concentration in Plovdiv, Bulgaria. Such a structure is preferred because it has a good generalization capability, high-speed learning, and low computational efforts and guarantee the convergence with the global minimum. The data set used in the present study comprises temperature, humidity, atmospheric pressure, PM10 and PM2.5 daily average concentrations from all 60 monitoring stations located in the city.","PeriodicalId":206080,"journal":{"name":"2019 Big Data, Knowledge and Control Systems Engineering (BdKCSE)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multi-input Multi-output Neo-Fuzzy Neural Network for PM10 and PM2.5 Daily Concentrations Forecasting\",\"authors\":\"M. Terziyska, Zhelyazko Terziyski, S. Hadzhikoleva, E. Hadzhikolev\",\"doi\":\"10.1109/BdKCSE48644.2019.9010610\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Multi-Input Multi-Output Neo-Fuzzy Neural Network Structure, based on Neo-fuzzy neuron concept, is used in this study to forecast average daily PM10 and PM2.5 concentration in Plovdiv, Bulgaria. Such a structure is preferred because it has a good generalization capability, high-speed learning, and low computational efforts and guarantee the convergence with the global minimum. The data set used in the present study comprises temperature, humidity, atmospheric pressure, PM10 and PM2.5 daily average concentrations from all 60 monitoring stations located in the city.\",\"PeriodicalId\":206080,\"journal\":{\"name\":\"2019 Big Data, Knowledge and Control Systems Engineering (BdKCSE)\",\"volume\":\"77 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 Big Data, Knowledge and Control Systems Engineering (BdKCSE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BdKCSE48644.2019.9010610\",\"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 Big Data, Knowledge and Control Systems Engineering (BdKCSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BdKCSE48644.2019.9010610","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multi-input Multi-output Neo-Fuzzy Neural Network for PM10 and PM2.5 Daily Concentrations Forecasting
Multi-Input Multi-Output Neo-Fuzzy Neural Network Structure, based on Neo-fuzzy neuron concept, is used in this study to forecast average daily PM10 and PM2.5 concentration in Plovdiv, Bulgaria. Such a structure is preferred because it has a good generalization capability, high-speed learning, and low computational efforts and guarantee the convergence with the global minimum. The data set used in the present study comprises temperature, humidity, atmospheric pressure, PM10 and PM2.5 daily average concentrations from all 60 monitoring stations located in the city.
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