Nothing Special   »   [go: up one dir, main page]

He et al., 2006 - Google Patents

Damage detection by an adaptive real-parameter simulated annealing genetic algorithm

He et al., 2006

Document ID
16820969591463268396
Author
He R
Hwang S
Publication year
Publication venue
Computers & Structures

External Links

Snippet

An effective algorithm, which combined an adaptive real-parameter genetic algorithm with simulated annealing, is proposed to detect damage occurrence in beam-type structures. The proposed algorithm uses the displacements of static response and natural frequencies of …
Continue reading at www.sciencedirect.com (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computer systems based on biological models
    • G06N3/12Computer systems based on biological models using genetic models
    • G06N3/126Genetic algorithms, i.e. information processing using digital simulations of the genetic system
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computer systems based on biological models
    • G06N3/02Computer systems based on biological models using neural network models
    • G06N3/08Learning methods
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computer systems based on biological models
    • G06N3/02Computer systems based on biological models using neural network models
    • G06N3/04Architectures, e.g. interconnection topology
    • G06N3/0472Architectures, e.g. interconnection topology using probabilistic elements, e.g. p-rams, stochastic processors
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass
    • G06N99/005Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/50Computer-aided design
    • G06F17/5009Computer-aided design using simulation
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10Complex mathematical operations
    • G06F17/18Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00Computer systems utilising knowledge based models
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N7/00Computer systems based on specific mathematical models
    • G06N7/005Probabilistic networks

Similar Documents

Publication Publication Date Title
He et al. Damage detection by an adaptive real-parameter simulated annealing genetic algorithm
Kikuchi et al. Dynamic modeling of genetic networks using genetic algorithm and S-system
Chelouah et al. Genetic and Nelder–Mead algorithms hybridized for a more accurate global optimization of continuous multiminima functions
Nannen et al. A method for parameter calibration and relevance estimation in evolutionary algorithms
He et al. Damage detection by a hybrid real-parameter genetic algorithm under the assistance of grey relation analysis
US8700548B2 (en) Optimization technique using evolutionary algorithms
Giannakoglou et al. Aerodynamic shape design using evolutionary algorithms and new gradient-assisted metamodels
US20060212279A1 (en) Methods for efficient solution set optimization
Uyar et al. A new population based adaptive domination change mechanism for diploid genetic algorithms in dynamic environments
JP4157477B2 (en) Improving the performance of an artificial neural network model in the presence of mechanical noise and measurement errors
CN110377511B (en) Test case generation method oriented to data flow
Efstratiadis et al. An evolutionary annealing-simplex algorithm for global optimisation of water resource systems
Asteris et al. Prediction of shear strength of corrosion reinforced concrete beams using Artificial Neural Network
CN110210072B (en) Method for solving high-dimensional optimization problem based on approximate model and differential evolution algorithm
Lagaros et al. Neurocomputing strategies for solving reliability‐robust design optimization problems
Lu et al. Genetic algorithm modelling and solution of inspection path planning on a coordinate measuring machine (CMM)
Gebert et al. Genetic networks and anticipation of gene expression patterns
Voke et al. A Framework for Feature Selection using Data Value Metric and Genetic Algorithm
Syberfeldt et al. A parallel surrogate-assisted multi-objective evolutionary algorithm for computationally expensive optimization problems
Hao et al. An effective Markov network based EDA for flexible job shop scheduling problems under uncertainty
Abbas et al. Volterra system identification using adaptive genetic algorithms
KR20230090959A (en) Business data analyzing method
Yuan et al. Convergency of genetic regression in data mining based on gene expression programming and optimized solution
JP3287738B2 (en) Relational function search device
Moroz et al. New two-parametric mutation operator for inductive modelling using combinatorial-genetic algorithm