Title :
GAQPR and its application in discovering frequent structures in time series
Author :
Bin, Li ; Junan, Yang ; Zhenquan, Zhuang
Author_Institution :
Dept. of Electron. Sci. & Technol., Univ. of Sci. & Technol. of China, Hefei, China
Abstract :
A new genetic algorithm based on the quantum probability representation (GAQPR) is proposed, in which each individual evolves independently; a new crossover operator is designed to integrate searching processes of multiple individuals into a more efficient global searching process; a new mutation operator is also proposed. The algorithm is used to discover frequent structures in time series, experiment results show that the GAQPR is efficient for the complex multi-peak searching problem.
Keywords :
genetic algorithms; probability; quantum computing; time series; GAQPR; complex multipeak searching problem; crossover operator; frequent structures discovery; genetic algorithm based on the quantum probability representation; global searching process; mutation operator; searching processes; time series; Algorithm design and analysis; Biological cells; Data mining; Genetic algorithms; Genetic mutations; Heuristic algorithms; Merging; Quantum computing; Quantum mechanics;
Conference_Titel :
Neural Networks and Signal Processing, 2003. Proceedings of the 2003 International Conference on
Conference_Location :
Nanjing
Print_ISBN :
0-7803-7702-8
DOI :
10.1109/ICNNSP.2003.1279293
