Research On Engineering Cost Fuzzy Intelligent Control And Measures Reasoning

Engineering Cost Control has always been the key point of the projectmanagement during the construction stage of the construction company. While mostconstruction companies would take active measures to control the cost, yet due to thelong construction period of the project, the complex construction environment,uncertain factors and other conditions, besides, the current cost control is mainly basedupon passive feedback, which leads to low efficiency in cost control. Artificialintelligence technology is an effective way to solve the problem. This paper fuzzyintelligent control technology is introduced in engineering cost control, trying to lookfor more effective means of cost control.This paper analyzes the current status of the project cost control, process anddeficiencies. Based on the analysis of the affecting factors of cost control, this paperintroduces the definition of project cost Fuzzy Intelligent Control. At the part ofknowledge representation and knowledge discovery, this paper has define the range ofengineering cost knowledge, building the system of combing production reasoningrepresentation with XML case-based representation. At the part of fuzzy controllerresearch, this paper has developed a classification of cost deviation standards, andcalculated the cost deviation given value. based on the Mamdani inference engine, thispaper has designed Engineering Cost fuzzy controller. The application of this controllersuccessfully outputs the control variables of cost control, combined with Matlab, querytable of cost fuzzy control has been produced. At the part of case-based reasoning,based on a sample library, this paper has been reasoned correction control measures,combined with modified rules, this paper has determined the recommended optimalprogram of measures. In each chapter of the thesis, a number of examples related to cost control are listed, to demonstrate the effectiveness of the technology.This paper has combined rough set, fuzzy control and case-based reasoningtechnology to make an innovation research on the existing cost control. The mainachievements include: knowledge discovery of affecting factors of cost control, designof project cost fuzzy controller, application of case-based reasoning modelquantitatively given the cost of corrective actions.This paper has introduced artificial intelligence technology into the field of projectcost, providing new ideas for the research of this field, enriching the existing costcontrol system in theory. Methods and achievements of this paper can be used as areference of the actual cost control for the company, pointing out the direction for thefollow-up research on intellectualized and informationized project cost, which has acertain theoretical and practical significance.