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  • 基于RS-GP模型的邊坡安全系數預測

    Prediction of slope safety factor based on the RS-GP model

    • 摘要: 鑒于邊坡系統影響因素之間的高度非線性和不確定性,融合RS-GP模型的優勢,提出了依據邊坡穩定性影響因素類比計算邊坡安全系數的方法.該方法通過學習樣本的數據特征分析、計算屬性的重要性及約簡規則,降低了遺傳規劃預測模型的結構規模.人工神經網絡(ANN)模型與RS-GP模型計算結果比較表明:該方法具有計算速度快、容錯能力強及精度高等特點.

       

      Abstract: Considering the high nonlinearity and uncertainty of influence factors in a slope system and making full use of the ad-vantages of the rough set theory and genetic programming (RS-GP model), a novel method based on the influencing factors of slope stability was brought up to calculate the safety factor of a slope. This method can reduce the structure scale of a genetic programming prediction model by analyzing the data characteristics of learning samples, calculating the significance of attributes and reducing rules. The results of an ANN model and the RS-GP model show that the proposed method has such merits as fast computing speed, high fault-tolerance capacity and high precision.

       

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