Assessment of Temperature Sensitivity Analysis and Temperature Regression Model for Predicting Seasonal Bank Load Patterns

2008 ◽  
Author(s):  
Minghao Piao ◽  
Jin Hyoung Park ◽  
Heon Gyu Lee ◽  
Jin-ho Shin ◽  
Duck Jin Chai ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Regression Model ◽  
Temperature Sensitivity

A Simulation Model for Multi-Factor Sensitivity Analysis on Energy Demand

2012 ◽  
Vol 621 ◽  
pp. 352-355
Author(s):  
Zhong Fu Tan ◽  
Shu Xiang Wang ◽  
Chen Zhang ◽  
Li Qiong Lin ◽  
Yin Hui Zhao
Keyword(s):  
Sensitivity Analysis ◽  
Energy Efficiency ◽  
Regression Model ◽  
Simulation Model ◽  
Influencing Factors ◽  
Energy Demand ◽  
Analysis Model ◽  
Demand Forecast ◽  
Population Urbanization

This paper analyses multi influencing factors of energy demand, using energy demand forecast regression model reveals inner relations between each factor and energy demand. Establish simulation model of the relation between GDP, energy intense and energy demand. Under the change in population, urbanization and energy efficiency, this paper gives analysis model of energy demand change.

scholarly journals Sensitivity analysis of a data-driven model of ocean temperature

2021 ◽  
Author(s):  
Rachel Furner ◽  
Peter Haynes ◽  
Dave Munday ◽  
Brooks Paige ◽  
Daniel C. Jones ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Regression Model ◽  
Data Driven ◽  
Ocean Temperature ◽  
Physical Knowledge ◽  
Predictive Skill ◽  
Model Interpretation ◽  
Highly Nonlinear ◽  
Simple Regression Model ◽  
Simple Regression

Abstract. There has been much recent interest in developing data-driven models for weather and climate predictions. These have shown reasonable success in modelling atmospheric dynamics over short time scales, however there are open questions regarding the sensitivity and robustness of these models. Using model interpretation techniques to better understand how data-driven models are making predictions is critical to developing trust in these alternative prediction systems. We develop a simple regression model of ocean temperature evolution, Ocean Temperature Regressor v1.0, and investigate its sensitivity to improve understanding of whether data-driven models are capable of learning the complex underlying dynamics of the systems being modelled. We investigate model sensitivity in a variety of ways and find that Ocean Temperature Regressor v1.0 behaves in ways which are, for the most part, in line with our knowledge of the ocean system being modelled. Specifically we see that the regressor heavily bases its forecasts on, and is dependent on, variables which we know are key to the physical dynamics inherent in the system, such as the currents and density. By contrast, inputs to the regressor which have limited direct dynamic impact, such as location, are not heavily used by the regressor. We also find that the regression model requires non-linear interactions between inputs in order to show any meaningful predictive skill – in line with out knowledge of the highly nonlinear dynamics of the ocean. Further sensitivity analysis is carried out to interpret that the ways in which certain variables are used by the regression model. Results here are again mostly in line with our physical knowledge of the system, for example, we see that information about the vertical profile of the water column reduces errors in areas associated with convective activity, and information about the currents is used by the regressor to reduce errors in regions dominated by advective processes. Our results show that even a simple regression model is capable of “learning” much of the physical dynamics inherent in the ocean system being modelled, which gives promise for the sensitivity and generalisability of data-driven models more generally.

scholarly journals Temperature sensitivity analysis on mass-spring potential with electrostatic frequency reduction for lunar seismometers

AIP Advances ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 125019
Author(s):  
L. A. N. de Paula ◽  
H. J. Paik ◽  
N. C. Schmerr ◽  
A. Erwin ◽  
T. C. P. Chui ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Temperature Sensitivity ◽  
Mass Spring
Sign in / Sign up

Export Citation Format

Share Document