کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
246916 502395 2012 7 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Risk Preference Based Support Vector Machine Inference Model for Slope Collapse Prediction
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی عمران و سازه
پیش نمایش صفحه اول مقاله
Risk Preference Based Support Vector Machine Inference Model for Slope Collapse Prediction
چکیده انگلیسی

Slope collapse prediction inference errors may be divided into two types, namely 1) predicted collapse followed by actual non-collapse (i.e., α error) and 2) predicted non-collapse followed by actual collapse (i.e., β error). As limited time and information make it difficult to reduce the rate of prediction error, making predictions in a manner that considers decision maker risk preferences in order to consider the preferred α to β error ratio in road slope maintenance strategy formulation represents an important issue.This study proposes an innovative inference model, the Risk Preference based Support Vector Machine Inference Model (RP-SIM). RP-SIM infers the mapping relationship between input and output variables from historical cases using a Support Vector Machine (SVM), and then uses a fast messy genetic algorithm (fmGA) to conduct an optimal search based on α and β values set in accordance with actual decision maker risk preference.


► This study proposes an innovative inference model, the RP-SIM that incorporates decision maker risk preference.
► RP-SIM infers the mapping relationship between input and output variables from historical cases using an SVM.
► RP-SIM uses an fmGA to conduct an optimal search based on α and β values set in accordance with risk preference.
► Effectively considers decision maker risk preference.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Automation in Construction - Volume 22, March 2012, Pages 175–181
نویسندگان
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