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Uncontrolled project investment attracts more and more public attention. The inaccuracy of cost estimation is one of main reasons that make the government investment out of control. Cost estimation is affected by many uncertain factors, and the relationship between these factors are nonlinear, and the traditional model is hard to solve. This paper brings forward a model based on rough set and neural...
In order to increase the accuracy of the cost estimates in government investment, a method based on the PSO trained neural network to estimate the cost is proposed. First the neural network model of a project cost estimate is created, and then PSO is introduced to optimize the weight and threshold of the neural network, at last the neural network trained is used to estimate cost of the project. The...
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