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| Engineering Cost Forecasting of Electric Power Construction Projects Based on Grey Model Optimized by Genetic Algorithm |
| Wei Li, Yanan Yuan, Dongxiao Niu |
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Abstract In view of engineering cost forecasting of electric power
construction projects, a new forecasting approach based on gray
forecasting model (GM (1, 1)) optimized by genetic algorithm is
proposed in this paper. Namely, with minimum Mean Absolute
Percentage Error (MAPE) between grey forecasting sequence and the
original data sequence as constraint condition and in the software
of MATLAB, genetic algorithm is used to seek the optimal solution
of parameter c. And then we take the final optimal solution of
parameter into the GM (1, 1), getting the optimized GM (1, 1)
model. In the meantime, the optimized GM (1, 1) model is applied to
the main cost index prediction of electric power construction
projects, and the comparison between the forecasting approach
proposed in this paper and the traditional GM~(1, 1) is also given
in this paper. Therefore, it proves that the prediction precision
of this approach is better than that of the traditional one. The
optimized GM (1, 1) model has overcome the defect of determining
parameter C in GM (1, 1), and the result demonstrates that the
forecasting approach based on the optimized GM (1, 1) model is
effective and feasible.
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