Study Of Analysis Method For Spectroscopic Data Based On Grey Relational Analysis

Currently,in order to improve performance,the new energy related devices already evolve as complex 2-dimensional systems,which consist of multiple function materials with thickness in the range of nanometers to micrometers.This poses a great challenge in device optimization,and render the traditional try-and-error method inefficientective.The optimization process based on understanding of the underlying physical mechanisms requires efficiently evaluating the spectroscopic data of such complex systems.In this thesis,after carefully inspecting a new grey relational analysis model is proposed to overcome the existing problems of the traditional models,a new grey analysis model based on dynamic selection method of the grey coefficient and optimized dimensionless method is proposed,then applied to study the spectroscopic data of a complex material system.The new model yields promising results are promising,and provides a new aspect perspective in related data analysis.The main work of the dissertation is as follows:Firstly,the disadvantages of the traditional grey relational analysis model are studied,and several other commonly used grey relational models are discussed in details.The deficiencies of existing models indicate suggest that the need of a new model is urgently needed.Second,to overcome the problem of induced by the fixed coefficient in the traditional model,a concept method of dynamically selecting the coefficient is proposed.The criteria for using different coefficient is studied,and tested using with several examples,which all show reasonable and reliable results.Furthermore,several dimensionless methods are compared to obtain develop the most suitable one for the grey relational analysis model.Then,a new gray relational model accommodating the above mentioned improvementadopting the dynamic resolution coefficients is developedproposed.Third,the proposed model is proved to satisfy the requirements of beingas a grey relational analysis model.Two cases are used to show it produces consistent results in both fluctuated and stable scenarios.At some circumstance,the new model yields better results than those of the traditional model.A calculation software of the grey relational analysis method is developed using C language and Matlab,which provide convenience for other researchers.Finally,the grey analysis model is used to study spectroscopic data of a complex material system.First the disadvantages of the current analysis methods are studied。Then,The new model is proved to be more suitable than traditional methods,into analyzinge spectroscopic data of complex systems,which consists of more than two chemical species.The resultsA simulation shows that,even with additional Poisson noise in the simulation data,there is a linear relationship between the grey correlation factor and the composition ratio of individual chemical species.The error of estimated ratio is less than 1%.Furthermore,the influence of data transformation on the results is also discussed.