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The goal of this research is to identify the significant factors affecting the firm performance and estimate the system behavior in different operating conditions. By determining the statistical relations of the productivity and effectiveness of the firm with these factors, a decision-making framework can be provided to improve the system performance within the competitive strategy of the whole supply...
Evaluation of construction projects is an important task for management of construction projects. An accurate forecast is required to enable supporting the investment decision and to ensure the project's feasible at the minimal cost. So controlling and rationally determining the construction cost plays the most important roles in the budget management of the construction project. Ways and means have...
In construction cost forecasting system, a great many uncertain factors effect the cost decision-making, so it is difficult to do effective forecasting by using traditional methods such as time series approach, regression analysis. In this paper, a nonlinear model based on RBF neural network is presented. There are some ameliorated measures in leaning algorithm of radial basis function (RBF) neural...
With the deterioration of primary energy market supply, it is important to optimize the raw material buying and dispatching. The annual electric power consumption is one of the most important decision making basis to realize this. Because of the characters of observations, OLS method and neural network model are all not suit for this. PLS extract variables one by one from few historical data. Under...
To improve the predictive ability of a fuzzy neural network prediction model, the re-selection is made, by means the rough set attribute reduction, of the correlated prognostic factors that have been chosen and the re-selected factors are treated by blurring as model input, thereby establishing a new-type fuzzy neural network predictive model. Experiments are conducted for approximately two months...
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