Reply from Author re: Eero Kaasinen. What Matters — Early Start or Duration of Chemotherapy Instillation Regimens or Patient Characteristics? Eur Urol 2008;53:882–5

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• 作者：J. Alfred Witjes
• 关键词：Settlement ; Shallow foundation ; Support vector machine
• 刊名：European Urology
• 出版年：2008
• 出版时间：May 2008
• 年：2008
• 卷：53
• 期：5
• 页码：885-886
• 全文大小：45 K

文摘

The determination of settlement of shallow foundations on cohesionless soil is an important task in geotechnical engineering. Available methods for the determination of settlement are not reliable. In this study, the support vector machine (SVM), a novel type of learning algorithm based on statistical theory, has been used to predict the settlement of shallow foundations on cohesionless soil. SVM uses a regression technique by introducing an ε – insensitive loss function. A thorough sensitive analysis has been made to ascertain which parameters are having maximum influence on settlement. The study shows that SVM has the potential to be a useful and practical tool for prediction of settlement of shallow foundation on cohesionless soil.