Research Article
Grey Forecast Model with Aging Fractional Accumulation and Its Properties
Algorithm 1
Optimization algorithm of the optimal aging parameter
(solution to optimize the optimal aging parameter
). | Input: the sample set | | Output: the optimal value of | (1) | Initialize parameters in the PSO algorithm: | | Particle number N, dimension D, maximum generation T, learning factor , , inertia weight . | (2) | Initialize the position and velocity | (3) | for do | (4) | for do | (5) | Calculate by Definition 1; | (6) | Calculate by equation (10); | (7) | Compute using equation (13); | (8) | Compute the fitness function ; | (9) | Update the position and velocity of particles | | | | . | | where are random vectors and belong to [0, 10]; and represent the individual optimal position and the global optimal position, respectively. | (10) | end for | (11) | end for | (12) | return optimal value of |
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