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Genetic algorithm has strong global search ability and robustness, but can not use the feedback of system and easy to do a lot of unnecessary redundancy iteration in the latter, resulting in the decline of convergence rate. Ant colony algorithm has the good characteristic of feedback, but due to lacking of initial pheromone, solving speed is slow. A method of adaptive dynamic integration is presented...
Unbalanced traffic demands of different data center applications are an important issue in designing data center networks (DCN). In this paper, we present our exploratory investigation on a hybrid DCN solution of utilizing wireless transmissions in DCNs. Our work aims to solve the congestion problem caused by a few hot nodes to improve the global performance. We model the wireless transmissions in...
Multiobjective site selection is a class complicated spatial analysis problem which can hardly be solved with traditional methods of Geographical Information System (GIS). In this paper we described an approach based on the gene expression programming (GEP) algorithm, with which the multiobjective site-search problems can be resolved. The validity of this method is verified by using MOP2 function,...
A major problem with text classification problems is the high dimensionality of the feature space. This paper investigates how genetic algorithm and k-means algorithm can help select relevant features in text classification. which uses the genetic algorithm (GA) optimization features to implement global searching, and uses k-means algorithm to selection operation to control the scope of the search,...
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