Presenting a combinative model based on Learning Classifier Systems, Rough Set Theory and GA for predicting the value of stocks
Publish Year: 1394
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
ICMEH01_034
تاریخ نمایه سازی: 11 مرداد 1396
Abstract:
Investment has played an important role in the economic development of the country. The importance of this factor and its role can be clearly seen in the country with a capitalist system. Stock is, without a doubt, an important factor in order to gain small investments and to use them in greater growth of a company. Investors expect people to achieve their expected profits. So the most important thing in this context is to buy a share with a lower price and to sell it with a higher price. The stock market has nonlinear and chaotic systems that rely on politics, economics and psychology and this has caused various methods of predicting values of stocks such as neural networks and fuzzy anticipations and genetic algorithms to arise. This study presents an innovative way to predict the value of stocks including LCS, RST and GA algorithms.
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Authors
Amin Allahverdipoor
Department of Management,Maku Branch,Islamic Azad University,Maku,Iran
Siamak kazemzadeh
Department of Management,Maku Branch,Islamic Azad University,Maku,Iran
Hadi fathalizadeh
Department of camputer,Maku Branch,Islamic Azad University,Maku,Iran
Vahed Ganjizadeh
Department of Management,Maku Branch,Islamic Azad University,Maku,Iran
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