{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T13:31:42Z","timestamp":1753882302432,"version":"3.41.2"},"reference-count":26,"publisher":"World Scientific Pub Co Pte Ltd","issue":"01","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Model. Simul. Sci. Comput."],"published-print":{"date-parts":[[2023,2]]},"abstract":"<jats:p> Stock market forecast improves the economic development of the country. People invest in the stock market at high risk without performing the appropriate analysis. So, it is essential to identify the stock market value prediction through existing stock market datasets. This analysis can be made through machine learning algorithms. Machine Learning is defined as the process through which only investors will gain the profit when investing the money into the stock market. Many prediction models have been contributed by the existing investigators to estimate the stock value. The contribution by Hybrid Heuristic algorithm is that it provides a coherent future prediction of stock market prices and investors will also get the insights about how to sell and buy a specific stock to get more profit. Gann square technique is used to forecast a price maneuver dependent on value, pattern analysis and period which is also used for intraday online trading without prior knowledge. <\/jats:p>","DOI":"10.1142\/s1793962322430061","type":"journal-article","created":{"date-parts":[[2022,8,24]],"date-time":"2022-08-24T13:22:26Z","timestamp":1661347346000},"source":"Crossref","is-referenced-by-count":1,"title":["Efficient prediction of future stock values with Gann square using machine learning algorithm"],"prefix":"10.1142","volume":"14","author":[{"given":"K. 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