• DocumentCode
    501130
  • Title

    Dynamic Control Model of Engineering Costs Forecasting in Implementation Stage for Construction Enterprises

  • Author

    Jianbing, Liu ; Hong, Ren ; Zhiming, Li

  • Author_Institution
    Sch. of Constr. Manage. & Real Estate, CHONGQING Univ., Chongqing, China
  • Volume
    1
  • fYear
    2009
  • fDate
    6-7 June 2009
  • Firstpage
    254
  • Lastpage
    258
  • Abstract
    The gray fuzzy predictive theory is introduced to engineering costs forecasting in implementation phase, which has been drawn a gray fuzzy predictive model, which is used to estimate the budget costs work scheduled of the unfinished engineering, then the budget costs work scheduled are optimized and adjusted, the buffer management mechanism of engineering in implementation stage is designed ,which is applied to be a timely dynamics warning of engineering costs control. The gray fuzzy predictive model is combined with the buffer management mechanism of engineering costs control ,which can be used to early dynamic warn and control in the whole construction implementation process, engineering costs are ensured to be effectively controlled from start to finish. At last ,the whole control objectives of engineering costs can be achieved .The gray fuzzy predictive model of engineering costs and the buffer management mechanism of engineering costs in implementation stage can provide a new kind of way to forecast the budget costs work scheduled of unfinished engineering of the implementation stage, which can provide an important guiding significance for construction enterprises cost management practice.
  • Keywords
    construction; costing; fuzzy control; predictive control; budget costs; buffer management; construction enterprises; dynamic control; engineering costs forecasting; gray fuzzy predictive theory; Conference management; Cost function; Design engineering; Economic forecasting; Engineering management; Financial management; Fuzzy control; Investments; Predictive models; Shape control; dynamic control; early warning buffer management; engineering costs forecasting; implementation stage; unfinished engineering costs;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Natural Computing, 2009. CINC '09. International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-0-7695-3645-3
  • Type

    conf

  • DOI
    10.1109/CINC.2009.13
  • Filename
    5231143