Title :
Material Consumption Estimation of High-Rise Buildings Based on SVM
Author :
Jie Ni ; Fei Tan
Author_Institution :
Dept. of Project Eng. & Econ., Hohai Univ., Nanjing, China
Abstract :
Estimation of steel consumption is an essential part of the implementation of quota design. Increasing accuracy of this estimation will not only help control the design phase, but also back up project decision and make it possible to conduct procurement plan earlier, which will shorten project life cycle. This paper adopts Support Vector Machine method among the numerous methods to apply it to this estimation in high-rise residential buildings and achieve relatively high accuracy through case verification. Furthermore, the influences of input variables´ variation on the outcome are revealed via sensitivity analysis, which can sustain project decision.
Keywords :
buildings (structures); construction industry; design engineering; procurement; project management; steel; structural engineering computing; support vector machines; SVM; case verification; design phase; high-rise residential buildings; material consumption estimation; procurement plan; project decision; project life cycle; quota design; sensitivity analysis; steel consumption; support vector machine method; Accuracy; Estimation; Feature extraction; Floors; Steel; Support vector machines; Support Vector Machine; high-rise buildings; material consumption; project decision; project estimation;
Conference_Titel :
Intelligent Human-Machine Systems and Cybernetics (IHMSC), 2013 5th International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-0-7695-5011-4
DOI :
10.1109/IHMSC.2013.34