Zobrazeno 1 - 10
of 127
pro vyhledávání: '"dqn algorithm"'
Autor:
LI Weiguang, CHEN Dong
Publikováno v:
Zhihui kongzhi yu fangzhen, Vol 46, Iss 3, Pp 62-69 (2024)
Aiming at the characteristics of large solution space, discrete, dynamic and nonlinear of firepower-target assignment problem, this paper proposes a deep reinforcement learning algorithm based on DQN. By combining the 6-layer fully connected feedforw
Externí odkaz:
https://doaj.org/article/1d9e1746d40f44e19ef42acb3797af00
Autor:
Ibrahim Omran, Ahmed Mostafa, Ahmed Seddik, Mohamed Ali, Mohand Hussein, Youssef Ahmed, Youssef Aly, Mohamed Abdelwahab
Publikováno v:
Ain Shams Engineering Journal, Vol 15, Iss 5, Pp 102670- (2024)
Efficient control of automotive engine idle speed is crucial for achieving better fuel economy and smoother engine running. This paper presents a comparison between proportional-integral-derivative (PID) control and Reinforcement Learning (RL) using
Externí odkaz:
https://doaj.org/article/52954f7d850d4c9ab71380d7dbb0851a
Autor:
Jianping Lan, Xiujuan Dong
Publikováno v:
IEEE Access, Vol 12, Pp 57059-57070 (2024)
With the continuous development of science and technology, the application of artificial intelligence in robot technology, especially in the progress of sports robot technology, has received great attention. This development provides new opportunitie
Externí odkaz:
https://doaj.org/article/13f7c468f6ed4ceaac24ea6812efb116
A multi-stage coordinated cyber-physical topology attack method based on deep reinforcement learning
Publikováno v:
电力工程技术, Vol 42, Iss 4, Pp 149-158 (2023)
With the development of smart grid and the continuous introduction of communication equipments into cyber physical system (CPS), CPS is confronted with a new attack mode with more destructive—coordinated cyber physical attack (CCPA). CCPA is not on
Externí odkaz:
https://doaj.org/article/2cead1266b894f65828cd6c9954401c2
Publikováno v:
Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024)
Traditional sheet metal processing enterprises are facing problems such as upgrading manufacturing systems, lower material utilization rate, and lower efficiency of CNC machining. In this paper, we design a flexible manufacturing production line for
Externí odkaz:
https://doaj.org/article/67f5ab952e5f4b629ac4550d72096ed6
Publikováno v:
Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024)
AGC is the main means to maintain the active power balance of the power system and ensure the system frequency quality. In this paper, deep learning techniques are used to optimize AGC active coordinated control. The linearized model simplifies the d
Externí odkaz:
https://doaj.org/article/31de2d8ea6a4426d8994b4b1f28fa0e1
Publikováno v:
Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024)
This paper analyzes and researches the network attack in the electric power information environment. The intrusion attack steps are examined, and the Bayesian inference method is applied to investigate the attack source information network delivery.
Externí odkaz:
https://doaj.org/article/4592cf19a83a430e947f2d68a04c610a
Autor:
Wang Yuzhen, Wang Jian
Publikováno v:
Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024)
The use of deep reinforcement learning algorithms for strategy formulation in supply chain management enables the nodes in the supply chain to better improve their management strategies. In this paper, a supply chain model is constructed as a startin
Externí odkaz:
https://doaj.org/article/45b2968be535403d89a55a6953ec05b0
Publikováno v:
Zhihui kongzhi yu fangzhen, Vol 45, Iss 1, Pp 150-156 (2023)
Emergency communication has the characteristics of strong sudden and uncertainty, to meet the requirements of flexible network planning, on the basis of different characteristics of diverse layered network to accomplish the modeling description, appl
Externí odkaz:
https://doaj.org/article/52e0a78739ff49c69ef1540c6bf5f730
Publikováno v:
IEEE Access, Vol 11, Pp 5919-5928 (2023)
Aiming at the problems of punctuality, parking accuracy and energy saving of urban rail train operation, an intelligent control method for automatic train operation (ATO) based on deep Q network (DQN) is proposed. The train dynamics model is establis
Externí odkaz:
https://doaj.org/article/0a94c05180c04beaa95b159bbcde93db