基因表达式编程在重金属形态预测建模中的应用研究
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摘要
提出一种改进的GEP(Gene Expression Programming)算法。根据重金属(HM)形态随时间变化(HMFT)的特点,建立基于跳跃基因表达式编程(JM-GEP)的重金属形态预测模型。跳跃算子是该模型的关键。为了保持种群多样性,研究最优保留策略GEP的收敛特性,跳跃算子采用自适应的跳跃概率。针对改进后的JM-GEP算法,提出一种基于GEP的重金属形态预测建模方法。仿真结果表明新模型更适合于HMFT的特性函数,找到全局最优解,且明显优于经典GEP算法及其他算法。该新模型方法还可广泛用于其他时间序列预测问题的研究。
In this paper,we proposed to use an improved GEP( gene expression programming) to build the heavy metal forms prediction model,which is based on jumping genes expression programming( JM-GEP),according to the characteristic of heavy metal forms changing along with the time( HMFT). Jumping operators are the key point of the model,in order to keep the diversity of population,we studied the convergence property of optimal retention strategy of GEP. The jumping operators use self-adaptive jumping probability. We put forward a JMGEP based heavy metals form prediction modelling method aimed at the improved GEP. Simulation results showed that the new model were more fit the characteristic function of HMFT,and found its global optimal solution,and was conspicuously superior to other algorithms. The method of new model could also be widely applied to the researches of other time sequences prediction problems.
In this paper,we proposed to use an improved GEP( gene expression programming) to build the heavy metal forms prediction model,which is based on jumping genes expression programming( JM-GEP),according to the characteristic of heavy metal forms changing along with the time( HMFT). Jumping operators are the key point of the model,in order to keep the diversity of population,we studied the convergence property of optimal retention strategy of GEP. The jumping operators use self-adaptive jumping probability. We put forward a JMGEP based heavy metals form prediction modelling method aimed at the improved GEP. Simulation results showed that the new model were more fit the characteristic function of HMFT,and found its global optimal solution,and was conspicuously superior to other algorithms. The method of new model could also be widely applied to the researches of other time sequences prediction problems.
引文
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[8]Yi Wai Chiang,karel Ghyselbrecht,Rafael M Santons.Sythesis of zeolitic-type adsorbent material from municipal solid waste incinerator bottom ash and its application in heavy metal adsorption[J].Catalysis Today,2012,190(1):23-30.
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[10]Ferreira C.Gene expression programming:A new adaptive algorithm for solving problems[J].Complex Systems,2002,12(2):87-129.
[11]Angeline P J.Adaptive and Self-Adaptive Evolutionary Computation[M].Piscataway:IEEE Press,1995:152-163.
[12]Hinterding R,Michalewicz Z,Eiben A E.Adaptation in Evolutionary Computation:A Survey[C]//Proceedings of the 4thIEEE Conference Evolutionary Computation,Indianapolis,USA:IEEE Press,1997:65-69.
[13]Eiben A E,Hinterding R,Michalewicz Z.Parameter Control in Evolutionary Algorithms[J].IEEE Transactions on Evolutionary Computation,1999,3(2):124-141.
[14]Ishibuchi H,Shibata Y.Mating Scheme for Controlling the DiversityConvergence Balance for Multiobjective Optimization[J].Lecture Notes in Computer Science,2004,3102(10):1259-1271.
[15]Shimodaira H.A Diversity Control-oriented-genetic Algorithm(DCGA):Performance in Function Optimization[C]//IEEE Congress on Evolutionary Computation(CEC’2001),Seoul,Korea:IEEE Press,44-51.
[16]浦黄忠,甄子洋,王道波,等.用于多峰函数优化的改进跳跃基因的遗传算法[J].南京航空航天大学学报,2007,39(6):829-832.
[17]陈安升,蔡之华,谷琼,等.一种新型的GEP算法及应用研究[J].计算机应用研究,2007,24(6):98-103.
[18]左劼.基因表达式编程核心技术研究[D].四川:四川大学,2004.
[2]Christl I,Metzger A,Heidmann I,et al.Effect of humic and fulvic acid concentrations and ionic strength on copper and lead binding[J].Environmental Science and Technology,2005,39(14):5319-5326.
[3]章骅,何品晶,吕凡,等.重金属在环境中的化学形态分析研究进展[J].环境化学,2011,30(1):130-137.
[4]Weng L,Temminghoff E J M,Van Riemsdijk W H.Contribution of individual sorbents to the control of heavy metal activity in sandy soil[J].Environmental Science and Technology,2001,35(22):4436-4443.
[5]Hiemstra T,van Riemsdijk W H.A surface structural approach to ion adsorption:the charge distribution(CD)model[J].Journal of Colloid and in Terface Science,1996,179(2):488-508.
[6]Dijkstra J J,Meeussen J C L,Comans R N J.Leaching of heavy metals from contaminated soils:an experimental and modeling study[J].Environmental Science and Technology,2004,38(16):4390-4395.
[7]Anirhomayoun Saffarzadeh,Takayuki Shimaoka.Impacts of natural weathering on the reansformation/neiformation processes in land filled MSW bottom ash:A geoenvironmental perspective[J].Waste Management,2011,31(12):2440-2454.
[8]Yi Wai Chiang,karel Ghyselbrecht,Rafael M Santons.Sythesis of zeolitic-type adsorbent material from municipal solid waste incinerator bottom ash and its application in heavy metal adsorption[J].Catalysis Today,2012,190(1):23-30.
[9]Gori M,Bergfeldt B,Pfrang-Stotz G.Effect of short-term natural weathering on MSWI and wood waste ash leaching behaviour[J].Waste Management,2011,189(1-2):435-443.
[10]Ferreira C.Gene expression programming:A new adaptive algorithm for solving problems[J].Complex Systems,2002,12(2):87-129.
[11]Angeline P J.Adaptive and Self-Adaptive Evolutionary Computation[M].Piscataway:IEEE Press,1995:152-163.
[12]Hinterding R,Michalewicz Z,Eiben A E.Adaptation in Evolutionary Computation:A Survey[C]//Proceedings of the 4thIEEE Conference Evolutionary Computation,Indianapolis,USA:IEEE Press,1997:65-69.
[13]Eiben A E,Hinterding R,Michalewicz Z.Parameter Control in Evolutionary Algorithms[J].IEEE Transactions on Evolutionary Computation,1999,3(2):124-141.
[14]Ishibuchi H,Shibata Y.Mating Scheme for Controlling the DiversityConvergence Balance for Multiobjective Optimization[J].Lecture Notes in Computer Science,2004,3102(10):1259-1271.
[15]Shimodaira H.A Diversity Control-oriented-genetic Algorithm(DCGA):Performance in Function Optimization[C]//IEEE Congress on Evolutionary Computation(CEC’2001),Seoul,Korea:IEEE Press,44-51.
[16]浦黄忠,甄子洋,王道波,等.用于多峰函数优化的改进跳跃基因的遗传算法[J].南京航空航天大学学报,2007,39(6):829-832.
[17]陈安升,蔡之华,谷琼,等.一种新型的GEP算法及应用研究[J].计算机应用研究,2007,24(6):98-103.
[18]左劼.基因表达式编程核心技术研究[D].四川:四川大学,2004.