Improved Colony Predation Algorithm Optimized Convolutional Neural Networks for Electrocardiogram Signal Classification
نویسندگان
چکیده
Recently, swarm intelligence algorithms have received much attention because of their flexibility for solving complex problems in the real world. a new algorithm called colony predation (CPA) has been proposed, taking inspiration from predatory habits groups nature. However, CPA suffers poor exploratory ability and cannot always escape solutions known as local optima. Therefore, to improve global search capability CPA, an improved variant (OLCPA) incorporating orthogonal learning strategy is proposed this paper. Then, considering fact that can go beyond optimum find solution, novel OLCPA-CNN model which uses OLCPA tune parameters convolutional neural network. To verify performance OLCPA, comparison experiments are designed compare with other traditional metaheuristics advanced on IEEE CEC 2017 benchmark functions. The experimental results show ranks first compared algorithms. Additionally, achieves high accuracy rates 97.7% 97.8% classifying MIT-BIH Arrhythmia European ST-T datasets.
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ژورنال
عنوان ژورنال: Biomimetics
سال: 2023
ISSN: ['2313-7673']
DOI: https://doi.org/10.3390/biomimetics8030268