A comprehensive assessing method based on the principle of the gray system theory and gray relational grade analysis was put forward to optimize water consumption forecasting models. The method provides a better accur...A comprehensive assessing method based on the principle of the gray system theory and gray relational grade analysis was put forward to optimize water consumption forecasting models. The method provides a better accuracy for the assessment and the optimal selection of the water consumption forecasting models. The results show that the forecasting model built on this comprehensive assessing method presents better self-adaptability and accuracy in forecasting.展开更多
It is difficult to establish the integrated method to assess the ambient air quality because the atmospheric environmental system is composed of several environmental elements, which contains many contanination factor...It is difficult to establish the integrated method to assess the ambient air quality because the atmospheric environmental system is composed of several environmental elements, which contains many contanination factors. In view of the typical grey system character of the monitored data in the ambient air, this paper introduces the weighted value to obtain related degree during applying the method of grey related degree analvsis to assess ambient air quality by each polluting factor producing different effects on the environment quality. This method could give more reasonable and reliable evaluating results. Taking the monitored data of Harbin, a provincial city of Heilongjiang, for example in this paper, the result of assessment by this method was coincide,It with the actual environmental quality of Harbin.展开更多
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
Non-contact measurements of machining temperatures were performed with optical pyrometer when drilling particle（B4C） reinforced metal matrix composites（MMCs） with different drills. The effect of particle content, ...Non-contact measurements of machining temperatures were performed with optical pyrometer when drilling particle（B4C） reinforced metal matrix composites（MMCs） with different drills. The effect of particle content, cutting speed, feed rate and tool material on the maximum drilling temperature was investigated. The drilling parameters were optimized based on multiple performance characteristics in terms of the maximum cutting temperature and tool wear. According to the results, the most influential control factors on the cutting temperatures are found to be particle fraction, feed rate and interaction between the cutting speed and particle content, respectively. The influences of the cutting speed and drill material on the drilling temperature are found to be relatively lower for the used range of parameters. Minimum cutting temperatures are obtained with lower particle fraction and cutting speed, with relatively higher feed rates and carbide tools. The results reveal that optimal combination of the drilling parameters can be used to obtain both minimum cutting temperature and tool wear.展开更多
基金Project(2003BA808A15-2-4) supported by the National Scientific and Technologies Key Task Program
文摘A comprehensive assessing method based on the principle of the gray system theory and gray relational grade analysis was put forward to optimize water consumption forecasting models. The method provides a better accuracy for the assessment and the optimal selection of the water consumption forecasting models. The results show that the forecasting model built on this comprehensive assessing method presents better self-adaptability and accuracy in forecasting.
文摘It is difficult to establish the integrated method to assess the ambient air quality because the atmospheric environmental system is composed of several environmental elements, which contains many contanination factors. In view of the typical grey system character of the monitored data in the ambient air, this paper introduces the weighted value to obtain related degree during applying the method of grey related degree analvsis to assess ambient air quality by each polluting factor producing different effects on the environment quality. This method could give more reasonable and reliable evaluating results. Taking the monitored data of Harbin, a provincial city of Heilongjiang, for example in this paper, the result of assessment by this method was coincide,It with the actual environmental quality of Harbin.
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Non-contact measurements of machining temperatures were performed with optical pyrometer when drilling particle（B4C） reinforced metal matrix composites（MMCs） with different drills. The effect of particle content, cutting speed, feed rate and tool material on the maximum drilling temperature was investigated. The drilling parameters were optimized based on multiple performance characteristics in terms of the maximum cutting temperature and tool wear. According to the results, the most influential control factors on the cutting temperatures are found to be particle fraction, feed rate and interaction between the cutting speed and particle content, respectively. The influences of the cutting speed and drill material on the drilling temperature are found to be relatively lower for the used range of parameters. Minimum cutting temperatures are obtained with lower particle fraction and cutting speed, with relatively higher feed rates and carbide tools. The results reveal that optimal combination of the drilling parameters can be used to obtain both minimum cutting temperature and tool wear.
