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In this paper, we investigate a no-regret learning algorithm for an exact potential game that allows cognitive radio pairs to update their transmission powers and frequencies simultaneously. We show by simulations that the No-regret algorithm converges to a pure Nash equilibrium, and that it achieves similar performance with the traditional game theoretic framework, while requiring less knowledge...
A novel self-adaptive Ant Colony Optimization algorithm based on Quantum mechanism for Traveling salesman problem(TQACO) is proposed. Firstly, initializing the population of the ant colony with superposition of Q-bit, Secondly, using self-adaptive operator, namely in prophase we use higher probability to explore more search space and to collect useful global information; otherwise in anaphase we use...
To avoid premature convergence and stagnation problems in classical ant colony system, a novel multi-behavior based multi-colony ant algorithm (MBMCAA) is proposed. The ant colony is divided into several sub-colonies; the sub-colonies have their own population evolved independently and in parallel according to four different behavior options, and update their local pheromone and global pheromone level...
This work presents an anti-windup control methodology to deal with the stabilization of nonlinear time-delay systems which are represented by Takagi-Sugeno (T-S) fuzzy models. The generic output feedback controller with anti-windup term is synthesized against the effect of actuator saturation. Based on delay-independent Lyapunov-Krasovskii functional analysis, a region of attraction that ensures convergence...
A novel parallel quantum evolutionary algorithm based on chaotic searching technique (PCQEA) is proposed. In the algorithm, the use of a chaotic searching technique provides this methodology with superior global search ability; several antibody diversification schemes were incorporated into the algorithm in order to enhance the exploitation and exploration. It can help to obtain the multi-modal optimal...
A novel real-coded immune quantum evolutionary algorithm for multi-modal function optimization (MRIQEA) is proposed. By niching methods population is divided into subpopulations automatically, local search is carried by the immune mechanism, each subpopulation can obtain precise solutions, and then the population can maintain all optimal solutions. Because of the quantum evolutionary algorithm with...
A novel immune quantum evolutionary algorithm based on chaotic searching for global optimization (CRIQEA) is proposed. Firstly, by niching methods population is divided into subpopulations automatically. Secondly, by using immune and catastrophe operator each subpopulation can obtain optimal solutions. Because of the quantum evolutionary algorithm with intrinsic parallelism it can maintain quite nicely...
The parallel genetic algorithm (PGA) realizes converging rate greatly as a result of fully displaying the natural parallelism of GA. This paper is just about applying this idea to fuzzy c-mean clustering, introducing immunity density adjustment mechanism, and proposing a new FCM clustering method - IGA-FCM double groups parallel clustering algorithm (another form of PGA). In order to realize the algorithm,...
Support vector machines (SVM) is a powerful supervised learning method. It has been used mostly for regression and classification. Some SVM parameters are usually selected artificially, which hampers the efficiency of the SVM algorithm in practical applications. A improved artificial fish swarm algorithm (IAFSA) based on the predatory search strategy of animals was used to optimize the parameters...
A novel quantum evolutionary algorithm based immune mechanism for solving multi-objective public traffic optimization (PRIQEA) is proposed. By niche methods population is divided into subpopulations of real-coded chromosome automatically, and then local search is carried by the immune mechanism, each subpopulation can obtain optimal solution. By exchanging optimal pattern between subpopulations, we...
This paper presents a novel cultural algorithm, in which an adaptive Cauchy mutated particle swarm optimizer (ACMPSO) is used as a population space; the Cauchy allows larger mutations and in this way producing more diversified individuals and covering more major space. The knowledge sources contained in the belief space are specifically designed according to the ACMPSO evolution features. Different...
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