Pattern Recognition of the Thigh Amputee Motion Based on Genetic Algorithm and BP

Lecture Notes in Electrical Engineering - Proceedings of 2013 Chinese Intelligent Automation Conference ◽

10.1007/978-3-642-38524-7_31 ◽

2013 ◽

pp. 291-298 ◽

Cited By ~ 2

Author(s):

Lei Liu ◽

Peng Yang ◽

Zuojun Liu ◽

Lingling Chen ◽

Yanli Geng

Keyword(s):

Genetic Algorithm ◽

Pattern Recognition

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Image Pattern Recognition Algorithm Based on Improved Genetic Algorithm

Journal of Physics Conference Series ◽

10.1088/1742-6596/1852/3/032038 ◽

2021 ◽

Vol 1852 (3) ◽

pp. 032038

Author(s):

Qing Kuang

Keyword(s):

Genetic Algorithm ◽

Pattern Recognition ◽

Recognition Algorithm ◽

Improved Genetic Algorithm ◽

Pattern Recognition Algorithm ◽

Image Pattern

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Pattern recognition using multilayer neural-genetic algorithm

Neurocomputing ◽

10.1016/s0925-2312(02)00619-7 ◽

2003 ◽

Vol 51 ◽

pp. 237-247 ◽

Cited By ~ 26

Author(s):

Yas Abbas Alsultanny ◽

Musbah M. Aqel

Keyword(s):

Genetic Algorithm ◽

Pattern Recognition

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A neural network used for PD pattern recognition in large turbine generators with genetic algorithm

Conference Record of the 2000 IEEE International Symposium on Electrical Insulation (Cat. No.00CH37075) ◽

10.1109/elinsl.2000.845406 ◽

2002 ◽

Cited By ~ 1

Author(s):

Guangning Wu

Keyword(s):

Neural Network ◽

Genetic Algorithm ◽

Pattern Recognition ◽

Turbine Generators

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Numeric Pattern Recognition Using Genetic Algorithm and DNA coding

Journal of Korean institute of intelligent systems ◽

10.5391/jkiis.2003.13.1.037 ◽

2003 ◽

Vol 13 (1) ◽

pp. 37-44 ◽

Cited By ~ 1

Author(s):

Dong-Hwa Paek ◽

Seung-Soo Han

Keyword(s):

Genetic Algorithm ◽

Pattern Recognition ◽

Dna Coding

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Seismic Pattern Recognition of Nuclear Explosion Based on Generalization Learning Algorithm of BP Network and Genetic Algorithm

Advances in Neural Networks – ISNN 2004 - Lecture Notes in Computer Science ◽

10.1007/978-3-540-28647-9_158 ◽

2004 ◽

pp. 959-964

Author(s):

Daizhi Liu ◽

Renming Wang ◽

Xihai Li ◽

Zhigang Liu

Keyword(s):

Genetic Algorithm ◽

Pattern Recognition ◽

Learning Algorithm ◽

Nuclear Explosion ◽

Bp Network

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Pattern Recognition for High Throughput Zebrafish Imaging Using Genetic Algorithm Optimization

Pattern Recognition in Bioinformatics - Lecture Notes in Computer Science ◽

10.1007/978-3-642-16001-1_26 ◽

2010 ◽

pp. 301-312 ◽

Cited By ~ 7

Author(s):

Alexander E. Nezhinsky ◽

Fons J. Verbeek

Keyword(s):

Genetic Algorithm ◽

Pattern Recognition ◽

High Throughput ◽

Algorithm Optimization ◽

Genetic Algorithm Optimization

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Pattern recognition with neural networks combined by genetic algorithm

Fuzzy Sets and Systems ◽

10.1016/s0165-0114(98)00232-2 ◽

1999 ◽

Vol 103 (2) ◽

pp. 339-347 ◽

Cited By ~ 47

Author(s):

Sung-Bae Cho

Keyword(s):

Genetic Algorithm ◽

Neural Networks ◽

Pattern Recognition

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A method of multiobjective optimization using a genetic algorithm and an artificial immune system

Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science ◽

10.1243/09544062jmes1313 ◽

2009 ◽

Vol 223 (5) ◽

pp. 1243-1252 ◽

Cited By ~ 3

Author(s):

H Park ◽

N-S Kwak ◽

J Lee

Keyword(s):

Genetic Algorithm ◽

Pattern Recognition ◽

Immune System ◽

Artificial Immune System ◽

Affinity Maturation ◽

Pareto Optimal ◽

Mathematical Function ◽

Pareto Optimal Solutions ◽

Optimal Solutions ◽

Artificial Immune

The immune system has pattern recognition capabilities based on reinforced learning, memory, and affinity maturation interacting between antigens (Ags) and antibodies (Abs). This article deals with an adaptation of artificial immune system (AIS) into genetic-algorithm (GA)-based multi-objective optimization. The present study utilizes the pattern recognition from an AIS and the evolution from a GA. Using affinity measures between Ags and Abs, GA-based immune simulation discovers a generalist Ab that represents the common pattern among Ags. Non-dominated Pareto-optimal solutions are obtained via GA-based immune simulation in which dominated designs are considered as Ags, whereas non-dominated designs are assigned to Abs. This article discusses the procedure of identifying Pareto-optimal solutions through the immune system-based pattern recognition. A number of mathematical function problems that are described by discontinuity or disconnection in the shape of Pareto surface are first examined as test examples. Subsequently, engineering optimization problems such as rotating flywheel disc and ten-bar planar truss are explored to support the present study.

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