Genetic pattern search and its application to brain image classification
type: Item
instance of: scholarly article
title: Genetic pattern search and its application to brain image classification
zbMATH Open document ID: 1299.90431
DOI: 10.1155/2013/580876
author: Genlin Ji
author: Zhengchao Dong
author: Yudong Zhang
author: Shuihua Wang
published in: Mathematical Problems in Engineering
publication date: 2014-11-24T00:00:00Z
review text: Summary: A novel global optimization method, based on the combination of genetic algorithm (GA) and generalized pattern search (PS) algorithm, is proposed to find global minimal points more effectively and rapidly. The idea lies in the facts that GA tends to be quite good at finding generally good global solutions, but quite inefficient in finding the last few mutations for the absolute optimum, and that PS is quite efficient in finding absolute optimum in a limited region. The novel algorithm, named as genetic pattern search (GPS), employs the GA as the search method at every step of PS. Experiments on five different classical benchmark functions (consisting of Hump, Powell, Rosenbrock, Schaffer, and Woods) demonstrate that the proposed GPS is superior to improved GA and improved PS with respect to success rate. We applied the GPS to the classification of normal and abnormal structural brain MRI images. The results indicate that GPS exceeds BP, MBP, IGA, and IPS in terms of classification accuracy. This suggests that GPS is an effective and viable global optimization method and can be applied to brain MRI classification.
Mathematics Subject Classification ID: 90C59
Mathematics Subject Classification ID: 94A08
Mathematics Subject Classification ID: 68T10
Mathematics Subject Classification ID: 90C90
zbMATH DE Number: 6372778
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2013/580876
OpenAlex ID: W1992239936
cites work: Genetic algorithms and finite element coupling for mechanical optimization
cites work: Solving two-dimensional HP model for firefly algorithm and simplified energy function
cites work: A proposed method for learning rule weights in fuzzy rule-based classification systems
cites work: Generalized pattern search methods for a class of nonsmooth optimization problems with structure
cites work: An improved genetic algorithm for the distributed and flexible job-shop scheduling problem
cites work: Pattern search ranking and selection algorithms for mixed variable simulation-based optimization
cites work: Satellite image compression by post-transforms in the wavelet domain
Wikidata QID: Q21284825
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description: scientific article; zbMATH DE number 6372778