期刊文献+

二次检索

题名
关键词
文摘
作者
第一作者
机构
刊名
分类号
参考文献
作者简介
基金资助
栏目信息

年份

共找到2篇文章
< 1 >
每页显示 20 50 100
MODELING AND OPTIMIZATION OF THE CUTTING FLUID FLOW AND PARAMETERS FOR INCREASING TOOL LIFE IN SLOT MILLING ON St52
1
作者 AMIR MAHYAR KHORASANI ALEX KOOTSOOKOS 《International Journal of Modeling, Simulation, and Scientific Computing》 EI 2013年第2期63-73,共11页
In this paper the CNC machining of St52 was modeled using an artificial neural network(ANN)in the form of a four-layer multi-layer perceptron(MLP).The cutting parameters used in the model were cutting fluid flow,feed ... In this paper the CNC machining of St52 was modeled using an artificial neural network(ANN)in the form of a four-layer multi-layer perceptron(MLP).The cutting parameters used in the model were cutting fluid flow,feed rate,spindle speed and the depth of cut and the model output was the tool life.For obtaining more accuracy and spending less time Taguchi design of experiment(DOE)has been used and correlation between the output of the ANN and the experimental results was 96%.Further optimization process has been done by use of a genetic algorithm(GA).After optimization process tool life was increased about 8%equal to 33 min and was corroborated by experimental tests.This demonstrates that the coupling of an ANN with the GA optimization technique is a valid and useful approach to use. 展开更多
关键词 Cutting fluid flow tool life optimization slot milling artificial neural networks.
原文传递
Simulating the evolution of a clonal trait in plants with sexual and vegetative reproduction
2
作者 Markus Fischer Eckart Winkler Bernhard Schmid 《Journal of Plant Ecology》 SCIE 2008年第3期161-171,共11页
Aims Phenotypic optimality models neglect genetics.However,especially when heterozygous genotypes are fittest,evolving allele,genotype and phenotype frequencies may not correspond to predicted optima.This was not prev... Aims Phenotypic optimality models neglect genetics.However,especially when heterozygous genotypes are fittest,evolving allele,genotype and phenotype frequencies may not correspond to predicted optima.This was not previously addressed for organisms with complex life histories.Methods Therefore,we modelled the evolution of a fitness-relevant trait of clonal plants,stolon internode length.We explored the likely case of an asymmetric unimodal fitness profile with three model types.In constant selection models(CSMs),which are gametic,but not spatially explicit,evolving allele frequencies in the one-locus and fiveloci cases did not correspond to optimum stolon internode length predicted by the spatially explicit,but not gametic,phenotypic model.This deviation was due to the asymmetry of the fitness profile.Gametic,spatially explicit individual-based(SEIB)modeling allowed us relaxing the CSM assumptions of constant selection with exclusively sexual reproduction.Important findings For entirely vegetative or sexual reproduction,predictions of the gametic SEIB model were close to the ones of spatially explicit nongametic phenotypic models,but for mixed modes of reproduction they approximated those of gametic,not spatially explicit CSMs.Thus,in contrast to gametic SEIB models,phenotypic models and,especially for few loci,also CSMs can be very misleading.We conclude that the evolution of traits governed by few quantitative trait loci appears hardly predictable by simple models,that genetic algorithms aiming at technical optimization may actually miss the optimum and that selection may lead to loci with smaller effects in derived compared with ancestral lines. 展开更多
关键词 clonal plants ecological and evolutionary modelling genetic variation life-history evolution optimal life histories simulation model
原文传递
上一页 1 下一页 到第
使用帮助 返回顶部