High Temperature Deformation Behavior of Duplex Stainless Steel

Maste

시계열 모형을 이용한 일일 전력 피크 예측

학위논문 (석사)-- 서울대학교 대학원 : 통계학과, 2015. 2. 조신섭.Many forecast models such as regression, exponential smoothing method, fuzzy regression, multilayer perception and extreme learning machine have been proposed to forecast daily electrical load. But some of the models do not incorporate the autocorrelation structure and they are not easy to interpret the forecast results. In this paper, we introduced transfer function and intervention model using discomfort index, sensory temperature index as input time series and seasonal eect, sandwich day(the day is between two holidays) eect as intervention. This model allows us to interpret predictive value and to forecast more accurately. This model might be quite useful to save power cost and to supply electricity smoothly1 Introduction 1 2 Models 3 2.1 Related research . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 2.2 Transfer function model . . . . . . . . . . . . . . . . . . . . . . 5 2.3 Intervention analysis . . . . . . . . . . . . . . . . . . . . . . . . 9 3 Real data analysis 11 3.1 Data description . . . . . . . . . . . . . . . . . . . . . . . . . . 11 3.2 Model tting . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 3.3 Forecast result . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 4 Conclusion and further discussion 22 Reference 24 iiMaste

Variation of the lattice parameters and its effects on the critical resolved shear stress and mechanical properties of Mg-Al, Mg-Zn and Mg-Li solid solutions

Docto

Effect of alloying elements on the c/a ratio of Mg binary solid solutions

1

순수 마그네슘 단결정 및 다결정을 이용한 크립 천이거동에 대한 연구

2

An internal variable approach to high temperature deformation and superplasticity of Mg alloys

1

Unified internal variable approach for creep and plasticity (invited)

2