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 A Method Football Team Model Optimization and Application of the Optimization Control
Tác giả hoặc Nhóm tác giả: Nguyen Hoang Mai
Nơi đăng: ISAT-17 conference ant University of Danang; Số: 1;Từ->đến trang: 95-99;Năm: 2018
Lĩnh vực: Khoa học công nghệ; Loại: Báo cáo; Thể loại: Quốc tế
TÓM TẮT
The development of the AI, IoT, and Big Data have to become strongly apply to discrete event strings systems. That are modern developments of the world. Therefore, we have to have an advanced method to develop adaptive applications, especially with MIMO discrete event systems. There is a limit while using a continuous calculation to control systems because the big calculation is an obstacle. So we have to find an optimization method to reduce the number of parameters in the calculation at any time [14],[15],[16]. We could do it by choice the main parameters and except auxiliary parameters. In this paper, we introduce a Football Team Optimization (FTO) method, which is a new method to do optimization problem while control with many parameters system. The application and analysis to compare any method as PSO, traditional PID, which takes out the difference of this algorithm.
ABSTRACT
The development of the AI, IoT, and Big Data have to become strongly apply to discrete event strings systems. That are modern developments of the world. Therefore, we have to have an advanced method to develop adaptive applications, especially with MIMO discrete event systems. There is a limit while using a continuous calculation to control systems because the big calculation is an obstacle. So we have to find an optimization method to reduce the number of parameters in the calculation at any time [14],[15],[16]. We could do it by choice the main parameters and except auxiliary parameters. In this paper, we introduce a Football Team Optimization (FTO) method, which is a new method to do optimization problem while control with many parameters system. The application and analysis to compare any method as PSO, traditional PID, which takes out the difference of this algorithm.
[ 2020\2020m09d07_8_28_4Abstract-paper_ISAT17-nguyenhoangmai.pdf ]
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