Optimization algorithms for parameters of generalized Usher model of settlement prediction
Optimization algorithms for parameters of generalized Usher model of settlement prediction
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发表时间：
2010
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通讯作者：
Zhang Jin-lun
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作者：
Zhang Jin-lun
为提高软土路基沉降预测精度，将原用于资源预测的广义Usher模型引入到沉降预测中。基于最小二乘原理，采用微分进化算法求解模型的结构参数。广义Usher模型包含了目前用于沉降预测的6种模型：指数曲线模型、Logistic模型、Gompertz模型、Bertalanffy模型、Weibull模型和Usher模型，表明其具有更强的灵活性和适应性。算例计算结果表明，由差分进化算法优化的广义Usher模型具有较高的预测精度，可应用于实际工程。
To improve the prediction accuracy of settlement of soft clay roadbed,the generalized Usher model originally for resources forecast was introduced in the settlement prediction.Based on the least square principle,the differential evolution algorithms were employed to solve the structural parameters of the model.The generalized Usher model includes the current six kinds of models for settlement prediction: the exponential curve model,the Logistic model,the Gompertz model,the Bertalanffy model,the Weibull model and the Usher model,indicating that it has more powerful flexibility and adaptability.The calculated results of examples show that the generalized Usher model optimized by the differential evolution algorithms has high prediction accuracy and can be applied in actual projects.