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Research on Modeling Method Based on Least Squares Support Vector Machine

机译:基于最小二乘支持向量机的建模方法研究

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A method of support vector machine based on particle swarm optimization was proposed for the question of parameter selecting difficult of least square support vector machine in modeling of gas sensor. Least square support vector machine is used to build the model of gas sensor. Particle swarm optimization arithmetic was introduced to optimize the parameters of support vector machine. The sensor model is tested with the data measured reality. The results prove the accuracy of the model.
机译:提出了一种基于粒子群优化的支持向量机的方法,提出了用于在气体传感器建模中选择最难以方形支持向量机的参数选择难度。最小二乘支持向量机用于构建气体传感器的模型。引入粒子群优化算法以优化支持向量机的参数。通过测量现实测试传感器模型。结果证明了模型的准确性。

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