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An improved adaptive genetic algorithm for solving facility layout problem is proposed. The principle of the algorithm is: during running process, making the crossover and mutation possibility adjust adaptively along with the value of fitness in accordance with the laws of sigmoid function curve; using smaller crossover and mutation possibility for the individuals of better patterns while lager crossover...
Efficient application assignment algorithm is important for high performance and low power consumption in NoC architecture. In this paper, we apply novel algorithm based on GA (genetic algorithm) and maximal free matrix constraint, which aim at using confliction avoidance and minimization between router communications in order to provide less network contentions during several running applications...
As belt transmission can offer a maximum of versatility as power transmission elements and allow the designer considerable flexibility in selecting a location of driver and driven machinery, and can operate smoothly and silently, therefore it is very necessary to use advanced methods to design the belt transmission. Considering the random character of the design parameters and load-bearing capacity,...
Gene expression programming is presented here for two stage evolutionary modeling. It uses character linear chromosomes composed of genes which encode expression trees. This feature which is different from existing algorithms allows the algorithm to perform with high efficiency when dealing with the same problem. And then, the analysis of convergence of this algorithm is mentioned. Finally, a numeric...
This paper deals with a hybrid optimization method for solving the optimization problems with inequality constraints and equality constraints, in which an adaptive penalty strategy is firstly adopted to convert the optimization problem with both equality constraints and inequality constraints to one only with lower and upper bound constraint of decision variables, then an adaptive real-coded genetic...
The constraint conditions of the auto-generating test paper are analyzed. The mathematical model of intelligence test paper generation system is set up and a new method of composing test paper based on the improved genetic algorithm is given. The result of the experiments shows that the new method is more efficient and easier to deal with the problem of autogenerating test paper than the traditional...
Mobile agent which has the features of migration and autonomy can be used in Wireless Sensor Network (WSN). An improved Genetic Algorithm (GA) is proposed to use in mobile agent-based routing algorithm to calculate the best routing for mobile agent's migration in WSN. By improving the arithmetic operators, the improved GA can find the best routing, and optimize the performance of mobile agent-based...
Considering the problem of the local optimization in the adaptive genetic algorithm (AGA), this paper presents an improved adaptive genetic algorithm (IAGA) which can optimize the weights and thresholds of the neural network. A stock prediction system based on neural networks and fuzzy theory is designed. According to the analysis of the history data of the stock, the system predicts this stock's...
The technology of searching for system failure through counterexample in model checking has drawn some attentions recently. For large concurrent systems, the number of states is always in an exponential growth when the number of processes which composed the system increases. It is so ineffective to use common heuristic method to search for the counterexample, that researching how to search for the...
To solve the combination explosion and the undecidable problem on feasibility of complete computation paths when testing the composed Web services programmed by business process execution language (BPEL), this paper presents a simple strategy for generating complete computation paths of BPEL program and an approach for generating test data for feasible complete computation paths based on tabu search...
In this paper, the theories of genetic algorithm (GA) and back propagation (BP) algorithm are introduced. For the purpose of overcoming the disadvantages of standard BP algorithm, such as local optimum and low convergence speed, the paper adopts genetic algorithm optimizing BP neural network for training. By analyzing computer stimulation results and comparing with traditional blind equalization algorithm,...
Inspired from the experience of genetic and clone algorithm, propose an algorithm of danger model immune algorithm (DMIA) according to the danger model theory. It has a good performance in function optimization. From the simulation result, we can see that DMIA is valid, and also with higher efficiency than genetic algorithm.
According to the functional demand of intelligent Test Paper system, we have designed four functional modules: examination database, test paper-generation, grade analysis and system setup. Test paper generation module is the core of the system, The improved Genetic Algorithms is more efficient and easier to get over premature convergence than the traditional algorithms. It is proved by a number of...
Neural network and genetic algorithm have attracted a great deal of attention as methods and theories realizing artificial intelligence recently. The combination of these two is drawing more and more attention. This paper demonstrates the possibility of combining neural network with genetic algorithm. An improved genetic algorithm for the learning of neural network's connection weights is presented...
Fuzzy K-prototypes is a very efficient algorithm for processing large scale mixed data set, but the selection of initial clustering center has an important impact on the clustering effect of algorithm. FKP algorithm is improved by using genetic algorithm in this paper. Seeking the initial clustering center for fuzzy K-prototypes algorithm by using genetic algorithm overcomes the shortcoming effectively,...
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