A novel thickness measurement method for surface insulation coating of silicon steel based on NIR spectrometry is explored.The NIR spectra of insulation coating of silicon steel were collected by acousto-optic tunable...A novel thickness measurement method for surface insulation coating of silicon steel based on NIR spectrometry is explored.The NIR spectra of insulation coating of silicon steel were collected by acousto-optic tunable filter(AOTF) NIR spectrometer.To make full use of the effective information of NIR spectral data,discrete binary particle swarm optimization(DBPSO) algorithm was used to select the optimal wavelength variates.The new spectral data,composed of absorbance at selected wavelengths,were used to create the thickness quantitative analysis model by kernel partial least squares(KPLS) algorithm coupled with Boosting.The results of contrast experiments showed that the Boosting-KPLS model could efficiently improve the analysis accuracy and speed.It indicates that Boosting-KPLS is a more accurate and robust analysis method than KPLS for NIR spectral analysis.The maximal and minimal absolute error of 30 testing samples is respectively-0.02 μm and 0.19 μm,and the maximal relative error is 14.23%.These analysis results completely meet the practical measurement need.展开更多
The aim of this article is an effort to initiate the cloudy fuzzy number in developing classical economic production lot-size model of an item produced in scrappy production process with fixed ordering cost and withou...The aim of this article is an effort to initiate the cloudy fuzzy number in developing classical economic production lot-size model of an item produced in scrappy production process with fixed ordering cost and without shortages.Here,the market value of an item is cloudy fuzzy number and the production rate is demand dependent.In general,fuzziness of any parameter remains fixed over time,but in practice,fuzziness of parameter begins to reduce as time progresses because of collected experience and knowledge that motivates to take cloudy fuzzy number.The model is solved in a crisp,general fuzzy and cloudy fuzzy environment using Yager’s index method and De and Beg’s ranking index method and comparisons are made for all cases and better results obtained in the cloudy fuzzy model.The model is solved by dominance based Particle Swarm Optimization algorithm to obtain optimal decision and numerical examples and sensitivity analyses are presented to justify the notion.展开更多
基金National High Technology Research and Development Program of China(2009AA04Z131)Natural Science Foundation of China (50877056)
文摘A novel thickness measurement method for surface insulation coating of silicon steel based on NIR spectrometry is explored.The NIR spectra of insulation coating of silicon steel were collected by acousto-optic tunable filter(AOTF) NIR spectrometer.To make full use of the effective information of NIR spectral data,discrete binary particle swarm optimization(DBPSO) algorithm was used to select the optimal wavelength variates.The new spectral data,composed of absorbance at selected wavelengths,were used to create the thickness quantitative analysis model by kernel partial least squares(KPLS) algorithm coupled with Boosting.The results of contrast experiments showed that the Boosting-KPLS model could efficiently improve the analysis accuracy and speed.It indicates that Boosting-KPLS is a more accurate and robust analysis method than KPLS for NIR spectral analysis.The maximal and minimal absolute error of 30 testing samples is respectively-0.02 μm and 0.19 μm,and the maximal relative error is 14.23%.These analysis results completely meet the practical measurement need.
基金supported by the University Grant Commission(UGC),New Delhi,India under the research grant[grant number PSW-132/14-15(ERO)].
文摘The aim of this article is an effort to initiate the cloudy fuzzy number in developing classical economic production lot-size model of an item produced in scrappy production process with fixed ordering cost and without shortages.Here,the market value of an item is cloudy fuzzy number and the production rate is demand dependent.In general,fuzziness of any parameter remains fixed over time,but in practice,fuzziness of parameter begins to reduce as time progresses because of collected experience and knowledge that motivates to take cloudy fuzzy number.The model is solved in a crisp,general fuzzy and cloudy fuzzy environment using Yager’s index method and De and Beg’s ranking index method and comparisons are made for all cases and better results obtained in the cloudy fuzzy model.The model is solved by dominance based Particle Swarm Optimization algorithm to obtain optimal decision and numerical examples and sensitivity analyses are presented to justify the notion.
