<p> <span style="font-family:Verdana;">To address the drawbacks of the traditional Parker test in multivariate linear</span><span style="font-family:;" "=""> ...<p> <span style="font-family:Verdana;">To address the drawbacks of the traditional Parker test in multivariate linear</span><span style="font-family:;" "=""> </span><span style="font-family:Verdana;">models:</span><span style="font-family:;" "=""> </span><span style="font-family:Verdana;">the process is cumbersome and computationally intensive,</span><span style="font-family:;" "=""> </span><span style="font-family:Verdana;">we propose a new heteroscedasticity test.</span><span style="font-family:;" "=""> </span><span style="font-family:Verdana;">A new heteroskedasticity test is proposed using the fitted values of the samples as new explanatory variables, reconstructing the regression model, and giving a new heteroskedasticity test based on the significance test of the coefficients, it is also compared with the existing Parker test which is improved using the principal component idea. Numerical simulations and empirical analyses show that the improved Parker test with the fitted values of the samples proposed in this paper is superior.</span> </p>展开更多
For entire roller embedded shapemeter roll, the relationship between the value of interference fit and the sensor pre-pressure, and the pressure transfer performance of shapemeter roll were analyzed by elasticity theo...For entire roller embedded shapemeter roll, the relationship between the value of interference fit and the sensor pre-pressure, and the pressure transfer performance of shapemeter roll were analyzed by elasticity theory during the cold reversible rolling process. Considering the influence of strip temperature on the interference fit, the distributions of contact pressure of the framework's top surface and the sensor pre-pressure on different values of interference fit were analyzed by the finite element technology. The results show that the contact pressure of the framework's top surface and the sensor pre-pressure increase with the increase of the value of interference fit. When the value of interference fit is between 0.05 mm and 0.09 mm, roll body's inner hole surface, the framework and pressure magnetic sensitive component don't separate from each other, and the sensor works in the linear segment of characteristic curve, so the normal operation of shapemeter roll is guaranteed.展开更多
In this paper we discuss, an initial-boundary value problem of hyperbolic type with first derivative with respect to x. The asymptotic solution is constructed and its uniform validity is proved under weader compatibil...In this paper we discuss, an initial-boundary value problem of hyperbolic type with first derivative with respect to x. The asymptotic solution is constructed and its uniform validity is proved under weader compatibility conditions. Then we develop an exponentially fitted difference scheme and establish discrete energy inequality. Finally, we prove that the solution of difference problem uniformly converges to the solution of the original problem.展开更多
To overcome the deficiencies of the existing Verhulst GM(1,1) model, based on the existing grey theory, a non-equal-interval direct optimum Verhulst GM(1,1) model is built which chooses a modified n-th component x(n) ...To overcome the deficiencies of the existing Verhulst GM(1,1) model, based on the existing grey theory, a non-equal-interval direct optimum Verhulst GM(1,1) model is built which chooses a modified n-th component x(n) of X(0) as the starting condition of the grey differential model. It optimizes a modified β value and the background value, and takes two times fitting optimization. The new model extends equal intervals to non-equal-intervals and is suitable for general data modelling and estimating parameters of the direct Verhulst GM(1,1). The new model does not need to pre-process the primitive data, nor accumulate generating operation (AGO) and inverse accumulated generating operation (IAGO). It is not only suitable for equal interval data modelling, but also for non-equal interval data modelling. As the new information is fully used and two times fitting optimization is taken, the fitting accuracy is the highest in all existing models. The example shows that the new model is simple and practical. The new model is worth expanding on and applying in data processing or on-line monitoring for tests, social sciences and other engineering sciences.展开更多
Grey Wolf Optimization (GWO) is a nature-inspired metaheuristic algorithm that has gained popularity for solving optimization problems. In GWO, the success of the algorithm heavily relies on the efficient updating of ...Grey Wolf Optimization (GWO) is a nature-inspired metaheuristic algorithm that has gained popularity for solving optimization problems. In GWO, the success of the algorithm heavily relies on the efficient updating of the agents’ positions relative to the leader wolves. In this paper, we provide a brief overview of the Grey Wolf Optimization technique and its significance in solving complex optimization problems. Building upon the foundation of GWO, we introduce a novel technique for updating agents’ positions, which aims to enhance the algorithm’s effectiveness and efficiency. To evaluate the performance of our proposed approach, we conduct comprehensive experiments and compare the results with the original Grey Wolf Optimization technique. Our comparative analysis demonstrates that the proposed technique achieves superior optimization outcomes. These findings underscore the potential of our approach in addressing optimization challenges effectively and efficiently, making it a valuable contribution to the field of optimization algorithms.展开更多
文摘<p> <span style="font-family:Verdana;">To address the drawbacks of the traditional Parker test in multivariate linear</span><span style="font-family:;" "=""> </span><span style="font-family:Verdana;">models:</span><span style="font-family:;" "=""> </span><span style="font-family:Verdana;">the process is cumbersome and computationally intensive,</span><span style="font-family:;" "=""> </span><span style="font-family:Verdana;">we propose a new heteroscedasticity test.</span><span style="font-family:;" "=""> </span><span style="font-family:Verdana;">A new heteroskedasticity test is proposed using the fitted values of the samples as new explanatory variables, reconstructing the regression model, and giving a new heteroskedasticity test based on the significance test of the coefficients, it is also compared with the existing Parker test which is improved using the principal component idea. Numerical simulations and empirical analyses show that the improved Parker test with the fitted values of the samples proposed in this paper is superior.</span> </p>
基金Project(2011BAF15B00)supported by the National Science and Technology Support Plan of ChinaProject(E2011203004)supported by the Hebei Provincial Natural Science Iron and Steel Joint Research Fund Program,China
文摘For entire roller embedded shapemeter roll, the relationship between the value of interference fit and the sensor pre-pressure, and the pressure transfer performance of shapemeter roll were analyzed by elasticity theory during the cold reversible rolling process. Considering the influence of strip temperature on the interference fit, the distributions of contact pressure of the framework's top surface and the sensor pre-pressure on different values of interference fit were analyzed by the finite element technology. The results show that the contact pressure of the framework's top surface and the sensor pre-pressure increase with the increase of the value of interference fit. When the value of interference fit is between 0.05 mm and 0.09 mm, roll body's inner hole surface, the framework and pressure magnetic sensitive component don't separate from each other, and the sensor works in the linear segment of characteristic curve, so the normal operation of shapemeter roll is guaranteed.
文摘In this paper we discuss, an initial-boundary value problem of hyperbolic type with first derivative with respect to x. The asymptotic solution is constructed and its uniform validity is proved under weader compatibility conditions. Then we develop an exponentially fitted difference scheme and establish discrete energy inequality. Finally, we prove that the solution of difference problem uniformly converges to the solution of the original problem.
基金The 11th Five-Year Plan for Key Constructing Academic Subject of Hunan Province(No.XJT2006180)Natural Science Foundation of Hunan Province (No.07JJ3093)Hunan Province Foundation Research Program (No.2007FJ3030,2007GK3058)
文摘To overcome the deficiencies of the existing Verhulst GM(1,1) model, based on the existing grey theory, a non-equal-interval direct optimum Verhulst GM(1,1) model is built which chooses a modified n-th component x(n) of X(0) as the starting condition of the grey differential model. It optimizes a modified β value and the background value, and takes two times fitting optimization. The new model extends equal intervals to non-equal-intervals and is suitable for general data modelling and estimating parameters of the direct Verhulst GM(1,1). The new model does not need to pre-process the primitive data, nor accumulate generating operation (AGO) and inverse accumulated generating operation (IAGO). It is not only suitable for equal interval data modelling, but also for non-equal interval data modelling. As the new information is fully used and two times fitting optimization is taken, the fitting accuracy is the highest in all existing models. The example shows that the new model is simple and practical. The new model is worth expanding on and applying in data processing or on-line monitoring for tests, social sciences and other engineering sciences.
文摘Grey Wolf Optimization (GWO) is a nature-inspired metaheuristic algorithm that has gained popularity for solving optimization problems. In GWO, the success of the algorithm heavily relies on the efficient updating of the agents’ positions relative to the leader wolves. In this paper, we provide a brief overview of the Grey Wolf Optimization technique and its significance in solving complex optimization problems. Building upon the foundation of GWO, we introduce a novel technique for updating agents’ positions, which aims to enhance the algorithm’s effectiveness and efficiency. To evaluate the performance of our proposed approach, we conduct comprehensive experiments and compare the results with the original Grey Wolf Optimization technique. Our comparative analysis demonstrates that the proposed technique achieves superior optimization outcomes. These findings underscore the potential of our approach in addressing optimization challenges effectively and efficiently, making it a valuable contribution to the field of optimization algorithms.
