{"title":"Intelligent financial decision support system based on data mining","authors":"Cheng-xuan Geng, Yunkai Xu, N. Metawa","doi":"10.3233/JIFS-189838","DOIUrl":null,"url":null,"abstract":"With the development of information technology, intelligent control technology is the comprehensive application of modern management techniques and methods. This paper mainly studies the intelligent financial decision support system based on data mining. This paper mainly introduces data mining technology, an intelligent financial decision support system and the application of data mining technology in an intelligent financial decision support system. The intelligent financial decision support system proposed in this paper uses a relational database to store massive business data, to improve the system expansion ability. By using mathematical model and data mining technology, an intelligent financial decision support system can automatically analyze data, discover the internal relationship between data, and mine the model that plays an important role in prediction and decision-making behavior, to establish a new business model, help decision-makers to make marketing strategies in line with the market and make correct decisions. The experimental results show that: the actual total profit of the company in 2019 is 43.37 million yuan, and the predicted total profit in 2019 is 43.38 million yuan. The similarity between the actual total profit in 2019 and the predicted total profit in 2019 is 99.98%. In 2019, the company’s sales revenue is 37.61 million yuan. The predicted sales revenue in 2019 is 37.62 million yuan, which is 99.97% similar to the actual sales revenue in 2019. The managers of the company can make marketing strategies and make correct decisions according to the sales revenue forecast in 2020.","PeriodicalId":44705,"journal":{"name":"International Journal of Fuzzy Logic and Intelligent Systems","volume":null,"pages":null},"PeriodicalIF":1.5000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Fuzzy Logic and Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3233/JIFS-189838","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
引用次数: 4
Abstract
With the development of information technology, intelligent control technology is the comprehensive application of modern management techniques and methods. This paper mainly studies the intelligent financial decision support system based on data mining. This paper mainly introduces data mining technology, an intelligent financial decision support system and the application of data mining technology in an intelligent financial decision support system. The intelligent financial decision support system proposed in this paper uses a relational database to store massive business data, to improve the system expansion ability. By using mathematical model and data mining technology, an intelligent financial decision support system can automatically analyze data, discover the internal relationship between data, and mine the model that plays an important role in prediction and decision-making behavior, to establish a new business model, help decision-makers to make marketing strategies in line with the market and make correct decisions. The experimental results show that: the actual total profit of the company in 2019 is 43.37 million yuan, and the predicted total profit in 2019 is 43.38 million yuan. The similarity between the actual total profit in 2019 and the predicted total profit in 2019 is 99.98%. In 2019, the company’s sales revenue is 37.61 million yuan. The predicted sales revenue in 2019 is 37.62 million yuan, which is 99.97% similar to the actual sales revenue in 2019. The managers of the company can make marketing strategies and make correct decisions according to the sales revenue forecast in 2020.
期刊介绍:
The International Journal of Fuzzy Logic and Intelligent Systems (pISSN 1598-2645, eISSN 2093-744X) is published quarterly by the Korean Institute of Intelligent Systems. The official title of the journal is International Journal of Fuzzy Logic and Intelligent Systems and the abbreviated title is Int. J. Fuzzy Log. Intell. Syst. Some, or all, of the articles in the journal are indexed in SCOPUS, Korea Citation Index (KCI), DOI/CrossrRef, DBLP, and Google Scholar. The journal was launched in 2001 and dedicated to the dissemination of well-defined theoretical and empirical studies results that have a potential impact on the realization of intelligent systems based on fuzzy logic and intelligent systems theory. Specific topics include, but are not limited to: a) computational intelligence techniques including fuzzy logic systems, neural networks and evolutionary computation; b) intelligent control, instrumentation and robotics; c) adaptive signal and multimedia processing; d) intelligent information processing including pattern recognition and information processing; e) machine learning and smart systems including data mining and intelligent service practices; f) fuzzy theory and its applications.