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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)
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)
In this study, we validate that the incremental leaning as a technique in data mining can be used to classify the students according to their interest by conducting some aptitude test including psychometric tests on students. So that the students can get the correct carrier choice, student can learn the subject in which he/she is interested and improve(More)
Optimization problems arise in many real-world applications. Cultural Algorithms are a class of computational models derived from observing the cultural evolution process in nature, compared with genetic algorithm the cultural algorithms have high convergence speed. Aiming at the disadvantages of basic cultural algorithms like being trapped easily into a(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)