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首页> 外文会议>International Conference on Informatics in Control, Automation and Robotics >ANN-based classifiers automatically generated by new multi-objective bionic algorithm
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ANN-based classifiers automatically generated by new multi-objective bionic algorithm

机译：新的多目标仿生算法自动生成基于ANN的分类器

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摘要

An artificial neural network (ANN) based classifier design using the modification of a meta-heuristic called Co-Operation of Biology Related Algorithms (COBRA) for solving multi-objective unconstrained problems with binary variables is presented. This modification is used for the ANN structure selection. The weight coefficients of the ANN are adjusted with the original version of COBRA. Two medical diagnostic problems, namely Breast Cancer Wisconsin and Pima Indian Diabetes, were solved with this technique. Experiments showed that both variants of COBRA demonstrate high performance and reliability in spite of the complexity of the optimization problems solved. ANN-based classifiers developed in this way outperform many alternative methods on the mentioned classification problems. The workability of the proposed meta-heuristic optimization algorithms was confirmed.
机译：提出了一种基于人工神经网络（ANN）的分类器设计，该模型使用一种称为“生物学相关算法的协同操作”（COBRA）的元启发式算法进行了修改，以解决带有二进制变量的多目标无约束问题。此修改用于ANN结构选择。人工神经网络的权重系数使用原始版本的COBRA进行调整。这项技术解决了两个医学诊断问题，即乳腺癌威斯康星州和比马印第安人糖尿病。实验表明，尽管解决了优化问题的复杂性，但COBRA的两个变体都表现出了高性能和可靠性。以这种方式开发的基于ANN的分类器在提到的分类问题上优于许多替代方法。证实了所提出的元启发式优化算法的可操作性。

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