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Khanchana, R.
- A Survey on Analysis of Stock Market by using Data Mining Techniques
Authors
1 Department of Computer Science, Sri Ramakrishna Arts and Science College for Women, Coimbatore, Tamil Nadu, IN
Source
Software Engineering, Vol 9, No 2 (2017), Pagination: 27-30Abstract
Stock market prediction is a significant area of financial forecasting. Prediction of the stock market is a great interest of stake holders such as stock investors, stock dealers, and researchers. The techniques available in data mining help to discover knowledge and train the prediction systems by using the historical data and real time dataset. The prediction model helps to discern the knowledge about the rise and fall of shares. So, the main aim of this research work is to review the existing prediction algorithms and techniques available for stock market applications. The stock market prediction model helps to discover stock and trends in a wide range of dataset.
Keywords
Data Mining, Financial Forecasting, Prediction, Stock Price.
- Soft Computing
Authors
1 Department of Computer Science, Sri Ramakrishna College of Arts and Science for Women, Coimbatore, IN
2 Department of Computer Science, Sri Ramakrishna College of Arts and Science for Women, Coimbatore, IN
Source
Fuzzy Systems, Vol 9, No 1 (2017), Pagination: 1-5Abstract
Soft computing is an evolving collection of methodologies, which aims to exploit tolerance for imprecision uncertainty, and partial truth to achieve robustness, tractability, and low cost. It can be a very attractive alternative to a purely digital system, but there are many traps waiting for researches trying to apply this new exciting technology. Software computing provides attractive opportunity to represent the ambiguity in human thinking with real life uncertainty. Fuzzy logic, Neural Networks, and Evolutionary Computation are the core methodologies of soft computing. For nonlinear processing both neural networks and fuzzy systems can be used.