Abstractthe model, predicting fatigue life of ductile iron, based on SVM (Support Vector Machine, SVM) has been established. For it is easy to fall into local optimum during parameter optimization of SVM, DE (Differential Evolution algorithm, DE) algorithm was adopted to optimize to improve prediction precision. Fatigue life of ductile iron is predicted combining with concrete examples, and simulation experiment to optimize SVM is conducted adopting GA (Genetic Algorithm), ACO (Ant Colony Optimization) and POS (Partial Swarm Optimization). Results reveal that DE-SVM algorithm is of a better prediction performance
Article first published online: 22 JUN 2011International audienceSystem reliability depends on inher...
Mechanical, physical and manufacturing properties of cast iron make it attractive for many fields of...
The aim of this research is to estimate the tool life using support vector machine method, that use...
Abstractthe model, predicting fatigue life of ductile iron, based on SVM (Support Vector Machine, SV...
Support vector machine is a new kind of learning method based on solid theoretical foundation, but t...
The fatigue life evaluation of metallic materials plays an important role in ensuring the safety and...
Ductile iron usage dates back some 5,000 years ago as forms of weapons and tools. During the industr...
A methodology is proposed to apply an endurance function model with a genetic algorithm to estimate ...
Abstract⎯Due to the lack of a structure way in determining the free parameters of support vector mac...
Remaining useful life (RUL) prediction of equipment has important significance for guaranteeing prod...
An effective approach is proposed to predict the remaining fatigue life (RFL) of structures with sto...
The accurate prediction of fatigue performance is of great engineering significance for the safe and...
The fatigue strength of ferritic, pearlitic, and solution strengthened ferritic ductile irons taken ...
In this article, high-cycle fatigue properties of the EN-GJS700-2 ductile cast iron were experimenta...
Support Vector Machine (SVM) is a new but prospective technique which has been used in pattern recog...
Article first published online: 22 JUN 2011International audienceSystem reliability depends on inher...
Mechanical, physical and manufacturing properties of cast iron make it attractive for many fields of...
The aim of this research is to estimate the tool life using support vector machine method, that use...
Abstractthe model, predicting fatigue life of ductile iron, based on SVM (Support Vector Machine, SV...
Support vector machine is a new kind of learning method based on solid theoretical foundation, but t...
The fatigue life evaluation of metallic materials plays an important role in ensuring the safety and...
Ductile iron usage dates back some 5,000 years ago as forms of weapons and tools. During the industr...
A methodology is proposed to apply an endurance function model with a genetic algorithm to estimate ...
Abstract⎯Due to the lack of a structure way in determining the free parameters of support vector mac...
Remaining useful life (RUL) prediction of equipment has important significance for guaranteeing prod...
An effective approach is proposed to predict the remaining fatigue life (RFL) of structures with sto...
The accurate prediction of fatigue performance is of great engineering significance for the safe and...
The fatigue strength of ferritic, pearlitic, and solution strengthened ferritic ductile irons taken ...
In this article, high-cycle fatigue properties of the EN-GJS700-2 ductile cast iron were experimenta...
Support Vector Machine (SVM) is a new but prospective technique which has been used in pattern recog...
Article first published online: 22 JUN 2011International audienceSystem reliability depends on inher...
Mechanical, physical and manufacturing properties of cast iron make it attractive for many fields of...
The aim of this research is to estimate the tool life using support vector machine method, that use...