T. Rizaldi, W. Hermawan, T. Mandang, S. Pertiwi, Rudiyanto
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引用次数: 0
摘要
摘要在操作过程中,车轮会穿透土壤,并在不同的穿透深度下与土壤表面形成一定的角度。为了确定土壤对板渗透的反作用力,在板上安装了贯入仪。本实验中使用的板尺寸分别为5×5 cm2、5×10 cm2、5 x 15 cm2和5×20 cm2。测量在不同的角度和深度进行,即分别为90°、75°、60°、45°、30°和4cm、8cm、12cm和16cm。本研究的目的是开发在不同深度和角度下预测土壤平台渗透阻力的方法。将线性或多项式回归方法与人工神经网络(ANN)进行了比较,提出了预测方法。研究表明,与回归方法相比,人工神经网络产生了更好的预测值,误差幅度较小,分别为9.9%和19.7%。
Development of The Method on The Prediction of Soil Plat Penetration Resistance
Abstract During operation, the lug wheels penetrate the soil and form certain angle to the soil surface at varying penetration depths. In order to determine the soil reaction force against plate penetration given to the soil, penetrometer was mounted on the plate. Plate sizes used in this experiment were 5×5 cm2, 5×10 cm2, 5×15 cm2 and 5×20 cm2. The measurement was carried out at varying angles and depths i.e. 90°, 75°, 60°, 45°, 30° and 4 cm, 8 cm, 12 cm and 16 cm, respectively. The objective of this research was to develop the method on the prediction of soil plat penetration resistance at varying depths and angles. Prediction method was developed using linear or polynomial regression method which compared with Artificial Neural Network (ANN). The research showed that ANN generated better prediction value which indicated by lower error magnitude compared with regression method i.e. 9.9% and 19.7%, respectively.