{"title":"基于FIS的股票市场预测","authors":"T. Chandrasegar, Mehul Kumar Piruka","doi":"10.1109/i-PACT44901.2019.8960107","DOIUrl":null,"url":null,"abstract":"Stock price forecasting is a prevalent and critical subject in financial and academic studies. The objective of this paper is to forecast today’s high price in the market from open of today, open from yesterday and closing of yesterday. We are using the real dataset from NSE NIFTY. We will be implementing a fuzzy intuition system such as Mamdani, Sugeno, and machine learning algorithms like CNN and LSTM. Cost optimization would be used for Sugeno. This paper would compare and improvise the algorithm which will show a higher prediction accuracy rate and would be proved statistically.","PeriodicalId":214890,"journal":{"name":"2019 Innovations in Power and Advanced Computing Technologies (i-PACT)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Prediction of Share Market using FIS\",\"authors\":\"T. Chandrasegar, Mehul Kumar Piruka\",\"doi\":\"10.1109/i-PACT44901.2019.8960107\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Stock price forecasting is a prevalent and critical subject in financial and academic studies. The objective of this paper is to forecast today’s high price in the market from open of today, open from yesterday and closing of yesterday. We are using the real dataset from NSE NIFTY. We will be implementing a fuzzy intuition system such as Mamdani, Sugeno, and machine learning algorithms like CNN and LSTM. Cost optimization would be used for Sugeno. This paper would compare and improvise the algorithm which will show a higher prediction accuracy rate and would be proved statistically.\",\"PeriodicalId\":214890,\"journal\":{\"name\":\"2019 Innovations in Power and Advanced Computing Technologies (i-PACT)\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 Innovations in Power and Advanced Computing Technologies (i-PACT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/i-PACT44901.2019.8960107\",\"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 Innovations in Power and Advanced Computing Technologies (i-PACT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/i-PACT44901.2019.8960107","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Stock price forecasting is a prevalent and critical subject in financial and academic studies. The objective of this paper is to forecast today’s high price in the market from open of today, open from yesterday and closing of yesterday. We are using the real dataset from NSE NIFTY. We will be implementing a fuzzy intuition system such as Mamdani, Sugeno, and machine learning algorithms like CNN and LSTM. Cost optimization would be used for Sugeno. This paper would compare and improvise the algorithm which will show a higher prediction accuracy rate and would be proved statistically.