The least squares method is one of the most fundamental methods in Statistics to estimate correlations among various data. On the other hand, Deep Learning is the heart of Artificial Intelligence and it is a learning ...The least squares method is one of the most fundamental methods in Statistics to estimate correlations among various data. On the other hand, Deep Learning is the heart of Artificial Intelligence and it is a learning method based on the least squares method, in which a parameter called learning rate plays an important role. It is in general very hard to determine its value. In this paper we generalize the preceding paper [K. Fujii: Least squares method from the view point of Deep Learning: Advances in Pure Mathematics, 8, 485-493, 2018] and give an admissible value of the learning rate, which is easily obtained.展开更多
This paper is concerned with the convergence rates of the global solutions of the generalized Benjamin-Bona-Mahony-Burgers（BBM-Burgers） equation to the corresponding degenerate boundary layer solutions in the half-s...This paper is concerned with the convergence rates of the global solutions of the generalized Benjamin-Bona-Mahony-Burgers（BBM-Burgers） equation to the corresponding degenerate boundary layer solutions in the half-space.It is shown that the convergence rate is t-（α/4） as t →∞ provided that the initial perturbation lies in H α 1 for α 〈 α（q）：= 3 ＋（2/q）,where q is the degeneracy exponent of the flux function.Our analysis is based on the space-time weighted energy method combined with a Hardy type inequality with the best possible constant introduced in [1]展开更多
Parametric Polynomial Method is used to analyze the three dimensional viscous flow through multistage turbomachines. Three high pressure stages in a 20MW steam turbine are calculated at design flow rate and small llow...Parametric Polynomial Method is used to analyze the three dimensional viscous flow through multistage turbomachines. Three high pressure stages in a 20MW steam turbine are calculated at design flow rate and small llow rate (G/G0 = 0.3). Large separated flow is predicted in the passage at small flow rate. The result shows that the upstream flow has a conspicuous effect on the downstream flow, so the multbetage fiow calculating is展开更多
文摘The least squares method is one of the most fundamental methods in Statistics to estimate correlations among various data. On the other hand, Deep Learning is the heart of Artificial Intelligence and it is a learning method based on the least squares method, in which a parameter called learning rate plays an important role. It is in general very hard to determine its value. In this paper we generalize the preceding paper [K. Fujii: Least squares method from the view point of Deep Learning: Advances in Pure Mathematics, 8, 485-493, 2018] and give an admissible value of the learning rate, which is easily obtained.
基金supported by the "Fundamental Research Funds for the Central Universities"the National Natural Science Foundation of China (10871151)
文摘This paper is concerned with the convergence rates of the global solutions of the generalized Benjamin-Bona-Mahony-Burgers（BBM-Burgers） equation to the corresponding degenerate boundary layer solutions in the half-space.It is shown that the convergence rate is t-（α/4） as t →∞ provided that the initial perturbation lies in H α 1 for α 〈 α（q）：= 3 ＋（2/q）,where q is the degeneracy exponent of the flux function.Our analysis is based on the space-time weighted energy method combined with a Hardy type inequality with the best possible constant introduced in [1]
文摘Parametric Polynomial Method is used to analyze the three dimensional viscous flow through multistage turbomachines. Three high pressure stages in a 20MW steam turbine are calculated at design flow rate and small llow rate (G/G0 = 0.3). Large separated flow is predicted in the passage at small flow rate. The result shows that the upstream flow has a conspicuous effect on the downstream flow, so the multbetage fiow calculating is
