毕业设计外文翻译—成本管理计划支持系统——工程造价控制策划和规划的新范例-工程造价(编辑修改稿)

毕业设计外文翻译—成本管理计划支持系统——工程造价控制策划和规划的新范例-工程造价(编辑修改稿)内容摘要：

ince only C and D have been defined as the attributes preceding F, p(F = 1) will only reflect the influence of C and D. Assumption 5 If an attribute gets into the active state, it has an independent capacity to cause a certain percentage cost escalation (% CE) in the estimated project cost, ., if an attribute gets into the active state, it might influence the attributes following it, and also independently cause a % CE by influencing certain line items that were estimated based on an assumed state of the attribute. All the assumptions have been carefully considered to provide an ease in putation and modeling of the plex nature of the first assumption is necessary to create a situation that would provide ease in puting the active state probability of attributes and in modeling the interrelationship between the attributes. It might be argued that in the construction context, all the attributes are interrelated under one situation or another and are thus dependent. However, it is putationally tedious and unproductive to consider the labyrinth of relationships existing between the attributes. Thus, it is imperative to define a structured and putationally manageable approach, as defined in the assumption. The second and third assumptions are derived from (1) the definition of the system (defined earlier。 refer to Fig. 1)。 (2) the interrelationships between attributes established in the influence pattern。 and (3) the need to create a structured environment for puting the influence of attributes on each other and also on the project cost. The fourth assumption has been included to establish the fact that, although the attributes preceding a particular attribute might have attained the active state, there exists a probability that the attribute in question may not attain the active state, ., [1p(CIA)] 2: 0 (refer to Fig. 1). The fifth assumption was derived from the definition of the influence pattern and the active state of attributes。 ., the influence pattern is a shadow work of attributes and these attributes are significant only when they attain the active state. This would imply that there has been a change in the status or value of the attribute from what was assumed at the estimating stage. This change in state of an attribute would thus directly influence the cost of certain line items that were estimated based on an assumed status or value of the attribute. These assumptions collectively provide a structured environment for modeling the plex interrelationship between the attributes and to make the DSS more responsive to the user. THE DSS COMPASS A DSS is defined as a puterbased system for decision support, with an ability to improve the effectiveness and productivity of the decision maker by utilizing the builtin analytical, situation modeling, and database management facilities (Ghiaseddin 1987). Accordingly, COMPASS was developed in three modules (refer to Fig. 2): (1) module Ito isolate pertinent information from past project performance data and to calibrate the data for a new project with respect to the project characteristics。 (2) module 2to determine the probable cost influence of attributes in a new project。 and (3) module 3to develop a project cost control strategy to minimize the expected loss. FRAMEWORK OF COMPASS The accuracy of a system depends to a large extent on the validity of the input data provided by the user. Therefore, it is important to properly analyze past project performance data before the data are used in identifying the potential risk attributes and in developing a project cost control strategy for a new project. The DPM was developed to assist the user in this aspect and to isolate the necessary information from the available past project performance data. DPM However, since every construction project is unique, the historical data cannot be used in analyzing a new project without giving proper consideration to the new project characteristics. The GDM was developed to take into account this important aspect and to calibrate the past project performance data (as analyzed in the DPM) before the data are used in analyzing a new project. The calibration is performed by soliciting subjective input from the team members with respect to the unique characteristics of the new project (refer to Fig. 2). The PWPCE model assists the user in calculating the probability of an attribute influencing the cost of a project and also the percentage cost escalation (with respect to the estimated project cost) due to that influence. This model utilizes the input provided by the DPM and the GDM to calculate the expected percentage cost escalation in a new project and also the individual cost influence of attributes in that output of the PWPCE model (., the individual cost influence of attributes and their probability of influencing the project cost) is then utilized by the DAM to formulate a cost control strategy for the new project. The puterization of the COMPASS methodology has eliminated the need for the user to follow the flow of information within the modules. To apply the COMPASS methodology, the user interaction with the system is limited to the decision making points, while the data analysis and putations are performed by the system. The user interaction with the puterized system is required at the following instances: (1) relevant data extraction from the past project performance data (to be used in the DPM)。 (2) team member input for group decision (in the GDM)。 and (3) user input to establish threshold PWPCE value to isolate potential risk attributes by using the DAM and for developing a project cost control strategy. Several logical checks have been provided throughout the system to assist the user with data entry and analysis. MODULE。