Research Paper | Finance | Hungary | Volume 8 Issue 1, January 2019
Mapping the Unified Field: Artificial Intelligence Foundations for the Financial Instruments of Business Planning: Hybrid Data Mining and the Consciousness Model
Dr. Laskai Andras
With the continuous development of data mining instruments we acquire increasingly accurate and deep knowledge regarding the processes and network correlations related to business planning that can be considered one of the cornerstones of the world of business. During data mining activity patterns can be derived that provide assistance in the analysis of basic correlations. By the application of data mining a consciousness model can be formulated, which evaluates and analyzes company movements, operations and decision making mechanisms. Data mining is one of the most important current paradigms of advanced business analyses and decision making instruments. (AMANIA-FADLALLA 2017). It is a multidisciplinary approach that applies various techniques in the areas of statistics, machine learning and databases. One of the special branches of data mining inspects the correlations of financial balance sheets and reports as well as their derived indicators. In the case of this method, data mining provides the identification of data patterns in an innovative and ultimately interpretable manner. (PUJARI 2001) Data mining makes it possible for organizations to identify the statistical correlations between performance indicators more easily (ITTNER-LARCKER 2001).
Keywords: Consciousness model, Data mining, Artificial network, International Business Planning, Financial instruments, Conscioussness
Edition: Volume 8 Issue 1, January 2019
Pages: 907 - 913
How to Cite this Article?
Dr. Laskai Andras, "Mapping the Unified Field: Artificial Intelligence Foundations for the Financial Instruments of Business Planning: Hybrid Data Mining and the Consciousness Model", International Journal of Science and Research (IJSR), https://www.ijsr.net/search_index_results_paperid.php?id=ART20193910, Volume 8 Issue 1, January 2019, 907 - 913
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