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A heavy Metals Morphology Prediction Modelling Method based on JM-GEP |
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PP: 1881-1891 |
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Author(s) |
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Yongqiang ZHANG,
Junxia LI,
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Abstract |
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In this paper, an improved GEP (Gene Expression Programming based on Jumping Genes, JM-GEP) is proposed in
consideration of the morphology of heavy metals (HM) changed over time, on which a new heavy metal prediction method has been put
forward. Jumping operator is the key point to JM-GEP, in which the jumping operators use self-adaptive jumping probability to keep
population diversity and study the convergence property of the optimal retention strategy. Aiming at the improved GEP, we raised a
heavy metals modelling method based on JM-GEP. The simulation results show that the new model, compared with traditional methods,
has excellent goodness of fit to HMFT characteristic function, and find out its global optimal. The new method proved to be widely
used for researching other time sequences problems. |
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