Data mining and analysis system based on two-brain Trading Strategy Model

Huayu Liu; Jiawei Chen; Honglin Fang

doi:10.1117/12.2644530

10 November 2022 Data mining and analysis system based on two-brain Trading Strategy Model

Huayu Liu, Jiawei Chen, Honglin Fang

Proceedings Volume 12301, 6th International Conference on Mechatronics and Intelligent Robotics (ICMIR2022); 123011U (2022) https://doi.org/10.1117/12.2644530
Event: 6th International Conference on Mechatronics and Intelligent Robotics, 2022, Kunming, China

Abstract

This article through the establishment of quantitative model and the corresponding prediction model orientation of network information mining, through the database to adjust some of this information and integration, the database of the directivity classification work, can according to the requirements in terms of system analysis of data at the same time, through the data to forecast its trend, get the best prediction model and the prediction results. In this paper, a data set is established based on the stage new information indicators of database information and the corresponding rise and fall trend broken line graph, and a quantitative Model and trend prediction system based on two-brain Strategy Model are established to predict and evaluate the situation of directional information. And then to predict the trend of fluctuations is relatively accurate prediction results quantitative optimization model is established, the grid strategy and hedge strategy is adopted to improve the decision-making and judgment, decision variable coding as operands, can converge to the optimal solution with large probability, data analysis and forecast the dynamic change of process, with different weights allocation scheme to give corresponding risk prediction.

Citation Download Citation

Huayu Liu, Jiawei Chen, and Honglin Fang "Data mining and analysis system based on two-brain Trading Strategy Model", Proc. SPIE 12301, 6th International Conference on Mechatronics and Intelligent Robotics (ICMIR2022), 123011U (10 November 2022); https://doi.org/10.1117/12.2644530

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