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Robot path planning is a NP problem; traditional optimization methods are not very effective to solve it. Traditional genetic algorithm trapped into the local minimum easily. Therefore, based on a simple genetic algorithm and combine the base ideology of orthogonal design method then applied it to the population initialization, using the intergenerational(More)
K-Nearest Neighbor (KNN) is one of the most popular algorithms for data classification. Many researchers have found that the KNN algorithm accomplishes very good performance in their experiments on different datasets. The traditional KNN text classification algorithm has limitations: calculation complexity, the performance is solely dependent on the(More)
The traveling salesman problem (TSP) is one of the most widely studied NP-hard combinatorial optimization problems and traditional genetic algorithm trapped into the local minimum easily for solving this problem. Particle Swarm Optimization (PSO) algorithm was developed under the inspiration of behavior laws of bird flocks, fish schools and human(More)
Traditional evolutionary algorithm trapped into the local minimum easily. Therefore, based on a simple evolutionary algorithm and combine the base ideology of orthogonal test then applied it to the population initialization, crossover operator, as well as the introduction of inver-over operator to prevent local convergence to form a new evolutionary(More)
This work investigates the application of cultural algorithms in the field of evolutionary electronics. Cultural Algorithms is an evolutionary model inspired by the cultural evolution process which shows many excellent characteristics and has succeeded in solving some complicated problems. Based on the population space in which individual evolves, the(More)
Since data and resources have massive feature and feature of data are increasingly complex, traditional data structures are not suitable for current data anymore. Therefore, traditional single-label learning method cannot meet the requirements of technology development and the importance of multi-label leaning method becomes more and more highlighted.(More)