A global optimization method for the stackelberg problem with convex functions via problem transformation and concave programming

1995 ◽  
Vol 25 (12) ◽  
pp. 1635-1640 ◽  
Author(s):  
Kiyotaka Shimizu ◽  
Min Lu
Keyword(s):  
Global Optimization ◽  
Convex Functions ◽  
Optimization Method ◽  
Global Optimization Method ◽  
Concave Programming ◽  
Problem Transformation ◽  
Stackelberg Problem

scholarly journals The Coplane Analysis Technique for Three-Dimensional Wind Retrieval Using the HIWRAP Airborne Doppler Radar

2015 ◽  
Vol 54 (3) ◽  
pp. 605-623 ◽  
Author(s):  
Anthony C. Didlake ◽  
Gerald M. Heymsfield ◽  
Lin Tian ◽  
Stephen R. Guimond
Keyword(s):  
Global Optimization ◽  
Doppler Radar ◽  
Three Dimensional ◽  
Optimization Method ◽  
Vertical Wind ◽  
Wind Component ◽  
Global Optimization Method ◽  
Analysis Technique ◽  
Radar Measurements ◽  
Cross Track

AbstractThe coplane analysis technique for mapping the three-dimensional wind field of precipitating systems is applied to the NASA High-Altitude Wind and Rain Airborne Profiler (HIWRAP). HIWRAP is a dual-frequency Doppler radar system with two downward-pointing and conically scanning beams. The coplane technique interpolates radar measurements onto a natural coordinate frame, directly solves for two wind components, and integrates the mass continuity equation to retrieve the unobserved third wind component. This technique is tested using a model simulation of a hurricane and compared with a global optimization retrieval. The coplane method produced lower errors for the cross-track and vertical wind components, while the global optimization method produced lower errors for the along-track wind component. Cross-track and vertical wind errors were dependent upon the accuracy of the estimated boundary condition winds near the surface and at nadir, which were derived by making certain assumptions about the vertical velocity field. The coplane technique was then applied successfully to HIWRAP observations of Hurricane Ingrid (2013). Unlike the global optimization method, the coplane analysis allows for a transparent connection between the radar observations and specific analysis results. With this ability, small-scale features can be analyzed more adequately and erroneous radar measurements can be identified more easily.

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