Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
An introduction to genetic algorithms
An introduction to genetic algorithms
Computational investigations of low-discrepancy sequences
ACM Transactions on Mathematical Software (TOMS)
Intelligence through simulated evolution: forty years of evolutionary programming
Intelligence through simulated evolution: forty years of evolutionary programming
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Damage detection by an adaptive real-parameter simulated annealing genetic algorithm
Computers and Structures
Differential evolution strategy for structural system identification
Computers and Structures
A hybrid Particle Swarm Optimization - Simplex algorithm (PSOS) for structural damage identification
Advances in Engineering Software
Modified genetic algorithm strategy for structural identification
Computers and Structures
Direct identification of structural parameters from dynamic responses with neural networks
Engineering Applications of Artificial Intelligence
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This paper is the first of two-part series on a uniformly sampled genetic algorithm with gradient search devised to efficiently solve the optimization-based structural identification. The strategy involves multi-species exploration, adaptive search space reduction and quasi-random sequence sampling. The use of a small number of uniform samples enables preliminary exploration in the solution space so as to shorten the ''learning curve'' considerably. The proposed strategy is shown by numerical study to give much better identification accuracy than the original search space reduction method, while using much less computational time for identification of known-mass and unknown-mass systems.