Profit Forecasting Using Support Vector Regression for Consulting Engineering Firms

Author

Yepes, Víctor ; Pellicer, Eugenio ; Ferri, Francesc J.

Author_Institution

Sch. of Civil Eng., Univ. Politec. de Valencia, Valencia, Spain

fYear

2009

fDate

Nov. 30 2009-Dec. 2 2009

Firstpage

982

Lastpage

987

Abstract

This paper introduces Support Vector Machines (SVM) in the particular field of decision support systems for consulting engineering companies and studies the differences and particularities of the corresponding solutions. A detailed analysis has been performed in order to assess the suitability and adaptability of these methods for the particular task taking into account the risk/benefit tradeoff.

Keywords

construction industry; consultancies; forecasting theory; profitability; regression analysis; support vector machines; consulting engineering companies; consulting engineering firms; decision support systems; profit forecasting; support vector regression; Artificial neural networks; Civil engineering; Contracts; Costs; Decision support systems; Design engineering; Economic forecasting; Macroeconomics; Pricing; Support vector machines; Bidding; Consulting; Decision Support Systems; Pattern Classification; Support Vector Machines;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Systems Design and Applications, 2009. ISDA '09. Ninth International Conference on

Conference_Location

Pisa

Print_ISBN

978-1-4244-4735-0

Electronic_ISBN

978-0-7695-3872-3

Type

conf

DOI

10.1109/ISDA.2009.43

Filename

5364424