Abstract: Stock market prediction (SMP) plays an important role in the modern era for any economy which is on the development phase. Genetic Algorithm (GA) is an evolutionary algorithm that is useful for solving problems which are too complex in nature. This paper surveys different GA models that have been experimented in stock market prediction with special enhancement techniques used with them to improve the prediction accuracy. The classification is made in terms of GA with two layer, multilayer, neural network variants and modified evolutionary algorithms. Through the surveyed paper it is shown that the performance of GA excels when integrated with other machine learning algorithms.

• Publication Date: 05-May-2013
• DOI: 10.15224/978-981-07-6261-2-39
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Abstract: In this paper, embodied conceptual schematization for the ‘public service export platform’ building that based on ROK\'s public information. For a more effective use of public information, suggested by linkage of LOD (Linked Open Data). In also, before the gathering of data, for beneficiaries, requirements analysis should precede and existing data reprocessing or missing data should be re-collection. Through this process, would like to propose that it is possible to build more effective knowledge service platform.

• Publication Date: 05-May-2013
• DOI: 10.15224/978-981-07-6261-2-38
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• Downloads: 0