Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
MILA – multilevel immune learning algorithm and its application to anomaly detection
Soft Computing - A Fusion of Foundations, Methodologies and Applications
A novel immune evolutionary algorithm incorporating chaos optimization
Pattern Recognition Letters
On the performance of artificial bee colony (ABC) algorithm
Applied Soft Computing
Journal of Global Optimization
Parameter identification of chaotic systems using evolutionary programming approach
Expert Systems with Applications: An International Journal
Chaos-based secure satellite imagery cryptosystem
Computers & Mathematics with Applications
Expert Systems with Applications: An International Journal
Chaotic Bayesian optimal prediction method and its application in hydrological time series
Computers & Mathematics with Applications
No-chattering sliding mode control chaos in Hindmarsh-Rose neurons with uncertain parameters
Computers & Mathematics with Applications
Computers & Mathematics with Applications
Robust synchronization of fractional-order unified chaotic systems via linear control
Computers & Mathematics with Applications
Learning and optimization using the clonal selection principle
IEEE Transactions on Evolutionary Computation
Hybrid Taguchi-genetic algorithm for global numerical optimization
IEEE Transactions on Evolutionary Computation
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In this paper, a novel evolutionary learning algorithm is proposed by hybridizing the Taguchi method, chaos disturbance operation, multilevel immune algorithm (MIA), and artificial bee colony algorithm (ABC). The algorithm is thus called HTCMIABC to estimate the parameter of chaotic systems. The HTCMIABC comprises two main different phases. First, we use the MIA as the recognition phase to balance local and global searches and accelerate the search speed to enhance the evolutionary phase. Second, the evolutionary phase is built on the ABC and chaos disturbance operation to have the capabilities of exploration and exploitation. Moreover, the Taguchi method and crossover operation are inserted between the recognition phase and evolutionary phase for the recombination and diversification of several antibodies to improve the searching ability. Finally, the HTCMIABC algorithm is examined by parameter identification of the nonlinear chaotic system. Simulation results show that the proposed algorithm is more efficient than some typical existing algorithms. The effects of noise and population size are investigated as well.