International Conference on Construction and Real Estate Management 2016
Cost Prediction Research for Commissioning Projects of Thermal Power Plants Based on a Hybrid Algorithm
Publication: ICCREM 2016: BIM Application and Off-Site Construction
ABSTRACT
Commissioning projects of thermal power plant forms the foundation to ensure safe and reliable operation of equipment; thus, cost prediction of commissioning project has aroused more and more attention. It’s not only the key to determine the goal of cost and prepare the cost plan but also can improve the economic benefits of power plant. In order to improve the forecasting accuracy, least squares support vector machine (LSSVM) optimized by fruit fly optimization algorithm (FOA) is applied in this paper, which can avoid the randomness of parameter selection. A case study in Hebei Province is carried out. The results indicate that FOA-LSSVM model shows high accuracy in cost prediction of commissioning projects of thermal power plant.
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Information & Authors
Information
Published In
ICCREM 2016: BIM Application and Off-Site Construction
Pages: 428 - 437
Editors: Yaowu Wang, Ph.D., Professor, Harbin Institute of Technology, Mohamed Al-Hussein, Ph.D., Professor, University of Alberta, Geoffrey Q. P. Shen, Ph.D., Professor, The Hong Kong Polytechnic University, and Yimin Zhu, Ph.D., Professor, Louisiana State University
ISBN (Online): 978-0-7844-8027-4
Copyright
© 2017 American Society of Civil Engineers.
History
Published online: Aug 14, 2017
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