A heavy Metals Morphology Prediction Modelling Method based on JM-GEP

Authors

Yongqiang ZHANG, The information and electricity-engineering institute, Hebei University of Engineering, Handan, 056038, P. R. ChinaFollow
Junxia LI, The information and electricity-engineering institute, Hebei University of Engineering, Handan, 056038, P. R. ChinaFollow

Author Country (or Countries)

P. R. China

Abstract

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.

Recommended Citation

ZHANG, Yongqiang and LI, Junxia (2015) "A heavy Metals Morphology Prediction Modelling Method based on JM-GEP," Applied Mathematics & Information Sciences: Vol. 09: Iss. 4, Article 27.
Available at: https://digitalcommons.aaru.edu.jo/amis/vol09/iss4/27