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To achieve a minimal time to through the urban traffic trunk road. However, the traditional analytical algorithm can not be applied in actual traffic widely. By combining the genetic BP neural network with the traditional analytical, A novel dynamic two-direction green wave coordinate control strategy was proposed, which applied in solving the function optimization problem. Finally, the new algorithm...
Under the background of the balance of exploration and exploitation, this paper analyzes the causes of the optimization hardness by using the concepts of effective ratio of exploration and exploitation. Then, a novel method is proposed to estimate the optimal feature factor, which is the essential part of optimal contraction theorem. At last, the method is tested with eight test functions. Some disadvantages...
Interactive genetic algorithms (IGAs) are effective methods of solving optimization problems with qualitative indices. The problem of user fatigue resulting from his/her evaluations, however, restricts their applications in complex optimization problems. Employing various surrogate models to evaluate (a part of) individuals instead of a user is a feasible approach to solving the above problem. Previous...
Traditional PSO algorithms suffer form the “curse of dimensionality”, which implies that their performance deteriorates as the dimensionality of the search space increase. This paper presents a variation on the traditional PSO algorithms, called improved cooperative particle swarm optimization, or COPSO, employing cooperative behavior to significantly improve the performance of the original algorithms...
In order to better simulate objective's vibration in transportation. A new vibration test whose each arm connected with crank-rocker mechanism is brought forward on the basis of Delta parallel mechanism. It can carry out vibration from three different directions. Given the inverse position analysis. The objective function is to satisfy harmonic oscillation of moveplatform under the constant speed...
In order to reduce the size and improve the convergence of PSO (particle swarm optimization) algorithm, an improved PSO algorithm, called TPSO (two particles PSO) algorithm, is presented in this paper. The swarm is only composed of two particles in TPSO algorithm. The algorithm is guaranteed to converge to the global optimization solution with probability one. Its global search ability is enhanced...
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