To improve prediction accuracy of strip thickness in hot rolling, a kind of Dempster/Shafer(D_S) information reconstitution prediction method(DSIRPM) was presented. DSIRPM basically consisted of three steps to impleme...To improve prediction accuracy of strip thickness in hot rolling, a kind of Dempster/Shafer(D_S) information reconstitution prediction method(DSIRPM) was presented. DSIRPM basically consisted of three steps to implement the prediction of strip thickness. Firstly, iba Analyzer was employed to analyze the periodicity of hot rolling and find three sensitive parameters to strip thickness, which were used to undertake polynomial curve fitting prediction based on least square respectively, and preliminary prediction results were obtained. Then, D_S evidence theory was used to reconstruct the prediction results under different parameters, in which basic probability assignment(BPA) was the key and the proposed contribution rate calculated using grey relational degree was regarded as BPA, which realizes BPA selection objectively. Finally, from this distribution, future strip thickness trend was inferred. Experimental results clearly show the improved prediction accuracy and stability compared with other prediction models, such as GM(1,1) and the weighted average prediction model.展开更多
This paper focuses on a series of quantitative an al ysis models, such as grey relational analysis model, hierarchical cluster an alysis model, principal component analysis model, linear regression model and elastic c...This paper focuses on a series of quantitative an al ysis models, such as grey relational analysis model, hierarchical cluster an alysis model, principal component analysis model, linear regression model and elastic coefficient model. These models are used to analyze the comprehensive function and effect of driving forces systemically, including analysis on featur es, analysis for differentiating the primary and the secondary, analysis on comp rehensive effects, analysis of elasticity, analysis of prediction. The primary a nd characteristic factors can be extracted by analysis of features and analysis for differentiating the primary and the secondary. Analysis on prediction an d elasticity can predict the area of cultivated land in the future and find out which factors exert great influence on the cultivated land supply.展开更多
基金Projects(61174115,51104044)supported by the National Natural Science Foundation of ChinaProject(L2010153)supported by Scientific Research Project of Liaoning Provincial Education Department,China
文摘To improve prediction accuracy of strip thickness in hot rolling, a kind of Dempster/Shafer(D_S) information reconstitution prediction method(DSIRPM) was presented. DSIRPM basically consisted of three steps to implement the prediction of strip thickness. Firstly, iba Analyzer was employed to analyze the periodicity of hot rolling and find three sensitive parameters to strip thickness, which were used to undertake polynomial curve fitting prediction based on least square respectively, and preliminary prediction results were obtained. Then, D_S evidence theory was used to reconstruct the prediction results under different parameters, in which basic probability assignment(BPA) was the key and the proposed contribution rate calculated using grey relational degree was regarded as BPA, which realizes BPA selection objectively. Finally, from this distribution, future strip thickness trend was inferred. Experimental results clearly show the improved prediction accuracy and stability compared with other prediction models, such as GM(1,1) and the weighted average prediction model.
文摘This paper focuses on a series of quantitative an al ysis models, such as grey relational analysis model, hierarchical cluster an alysis model, principal component analysis model, linear regression model and elastic coefficient model. These models are used to analyze the comprehensive function and effect of driving forces systemically, including analysis on featur es, analysis for differentiating the primary and the secondary, analysis on comp rehensive effects, analysis of elasticity, analysis of prediction. The primary a nd characteristic factors can be extracted by analysis of features and analysis for differentiating the primary and the secondary. Analysis on prediction an d elasticity can predict the area of cultivated land in the future and find out which factors exert great influence on the cultivated land supply.
