Based on the ant colony system （ACS） algorithm and fuzzy logic control, a new design method for optimal fuzzy PID controller was proposed. In this method, the ACS algorithm was used to optimize the input/output scal...Based on the ant colony system （ACS） algorithm and fuzzy logic control, a new design method for optimal fuzzy PID controller was proposed. In this method, the ACS algorithm was used to optimize the input/output scaling factors of fuzzy PID controller to generate the optimal fuzzy control rules and optimal real-time control action on a given controlled object. The designed controller, called the Fuzzy-ACS PID controller, was used to control the CIP-Ⅰ intelligent leg. The simulation experiments demonstrate that this controller has good control performance. Compared with other three optimal PID controllers designed respectively by using the differential evolution algorithm, the real-coded genetic algorithm, and the simulated annealing, it was verified that the Fuzzy-ACS PID controller has better control performance. Furthermore, the simulation results also verify that the proposed ACS algorithm has quick convergence speed, small solution variation, good dynamic convergence behavior, and high computation efficiency in searching for the optimal input/output scaling factors.展开更多
Beer fermentation is a dynamic process that must be guided along a temperature profile to obtain the desired results. Ant colony system algorithm was applied to optimize the kinetic model of this process. During a fix...Beer fermentation is a dynamic process that must be guided along a temperature profile to obtain the desired results. Ant colony system algorithm was applied to optimize the kinetic model of this process. During a fixed period of fermentation time, a series of different temperature profiles of the mixture were constructed. An optimal one was chosen at last. Optimal temperature profile maximized the final ethanol production and minimized the byproducts concentration and spoilage risk. The satisfactory results obtained did not require much computation effort.展开更多
In situation assessment(SA)of missile versus target fighter,the traditional SA models generally have the characteristics of strong subjectivity and poor dynamic adaptability.This paper considers SA as an expectation o...In situation assessment(SA)of missile versus target fighter,the traditional SA models generally have the characteristics of strong subjectivity and poor dynamic adaptability.This paper considers SA as an expectation of future returns and establishes a missile-target simulation battle model.The actor-critic(AC)algorithm in reinforcement learning(RL)is used to train the evaluation network,and a missile-target SA model is established in simulation battle training.Simulation and comparative experiments show that the model can effectively estimate the expected effect of missile attack under the current situation,and it provides an effective basis for missile attack decision.展开更多
As the core algorithm and the most time consuming part of almost every modern network intrusion management system （NIMS）, string matching is essential for the inspection of network flows at the line speed. This pape...As the core algorithm and the most time consuming part of almost every modern network intrusion management system （NIMS）, string matching is essential for the inspection of network flows at the line speed. This paper presents a memory and time efficient string matching algorithm specifically designed for NIMS on commodity processors. Modifications of the Aho-Corasick （AC） algorithm based on the distribution characteristics of NIMS patterns drastically reduce the memory usage without sacrificing speed in software implementations. In tests on the Snort pattern set and traces that represent typical NIMS workloads, the Snort performance was enhanced 1.48%-20% compared to other well-known alternatives with an automaton size reduction of 4.86-6.11 compared to the standard AC implementation. The results show that special characteristics of the NIMS can be used into a very effective method to optimize the algorithm design.展开更多
基金Project(50275150) supported by the National Natural Science Foundation of ChinaProject(20040533035) supported by the National Research Foundation for the Doctoral Program of Higher Education of ChinaProject(05JJ40128) supported by the Natural Science Foundation of Hunan Province, China
文摘Based on the ant colony system （ACS） algorithm and fuzzy logic control, a new design method for optimal fuzzy PID controller was proposed. In this method, the ACS algorithm was used to optimize the input/output scaling factors of fuzzy PID controller to generate the optimal fuzzy control rules and optimal real-time control action on a given controlled object. The designed controller, called the Fuzzy-ACS PID controller, was used to control the CIP-Ⅰ intelligent leg. The simulation experiments demonstrate that this controller has good control performance. Compared with other three optimal PID controllers designed respectively by using the differential evolution algorithm, the real-coded genetic algorithm, and the simulated annealing, it was verified that the Fuzzy-ACS PID controller has better control performance. Furthermore, the simulation results also verify that the proposed ACS algorithm has quick convergence speed, small solution variation, good dynamic convergence behavior, and high computation efficiency in searching for the optimal input/output scaling factors.
文摘Beer fermentation is a dynamic process that must be guided along a temperature profile to obtain the desired results. Ant colony system algorithm was applied to optimize the kinetic model of this process. During a fixed period of fermentation time, a series of different temperature profiles of the mixture were constructed. An optimal one was chosen at last. Optimal temperature profile maximized the final ethanol production and minimized the byproducts concentration and spoilage risk. The satisfactory results obtained did not require much computation effort.
基金the National Natural Science Foundation of China(No.61627810)the Joint Fund of Advanced Aerospace Manufacturing Technology Research of China(No.USCAST2016)the National Key Research and Development Program of China(No.2018YFB1305003)。
文摘In situation assessment(SA)of missile versus target fighter,the traditional SA models generally have the characteristics of strong subjectivity and poor dynamic adaptability.This paper considers SA as an expectation of future returns and establishes a missile-target simulation battle model.The actor-critic(AC)algorithm in reinforcement learning(RL)is used to train the evaluation network,and a missile-target SA model is established in simulation battle training.Simulation and comparative experiments show that the model can effectively estimate the expected effect of missile attack under the current situation,and it provides an effective basis for missile attack decision.
基金the Juniper Research Grant and Intel IXA Univer-sity Program
文摘As the core algorithm and the most time consuming part of almost every modern network intrusion management system （NIMS）, string matching is essential for the inspection of network flows at the line speed. This paper presents a memory and time efficient string matching algorithm specifically designed for NIMS on commodity processors. Modifications of the Aho-Corasick （AC） algorithm based on the distribution characteristics of NIMS patterns drastically reduce the memory usage without sacrificing speed in software implementations. In tests on the Snort pattern set and traces that represent typical NIMS workloads, the Snort performance was enhanced 1.48%-20% compared to other well-known alternatives with an automaton size reduction of 4.86-6.11 compared to the standard AC implementation. The results show that special characteristics of the NIMS can be used into a very effective method to optimize the algorithm design.
