Greediness Characterization of Genetic Algorithms

2018 ◽  
Author(s):  
Tri Asih Budiono
Keyword(s):  
Genetic Algorithms

Viscometric characterization of cobalt nanoparticle-based magnetorheological fluids using genetic algorithms

2005 ◽  
Vol 293 (1) ◽  
pp. 206-214 ◽  
Author(s):  
Anirban Chaudhuri ◽  
Norman M. Wereley ◽  
Sanjay Kotha ◽  
Ramachandran Radhakrishnan ◽  
Tirumalai S. Sudarshan
Keyword(s):  
Genetic Algorithms ◽  
Magnetorheological Fluids ◽  
Cobalt Nanoparticle

Characterization of structures from X-ray scattering data using genetic algorithms

1999 ◽  
Vol 357 (1761) ◽  
pp. 2827-2848 ◽  
Author(s):  
Matthew Wormington ◽  
Charles Panaccione ◽  
Kevin M. Matney ◽  
D. Keith Bowen
Keyword(s):  
Genetic Algorithms ◽  
Scattering Data ◽  
X Ray ◽  
X Ray Scattering ◽  
Ray Scattering

scholarly journals Applying Probability Theory for the Quality Assessment of a Wildfire Spread Prediction Framework Based on Genetic Algorithms

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Andrés Cencerrado ◽  
Ana Cortés ◽  
Tomàs Margalef
Keyword(s):  
Probability Theory ◽  
Genetic Algorithms ◽  
Forest Fires ◽  
Statistical Study ◽  
Computational Power ◽  
The Core ◽  
Evolutionary Technique ◽  
Wildfire Spread

This work presents a framework for assessing how the existing constraints at the time of attending an ongoing forest fire affect simulation results, both in terms of quality (accuracy) obtained and the time needed to make a decision. In the wildfire spread simulation and prediction area, it is essential to properly exploit the computational power offered by new computing advances. For this purpose, we rely on a two-stage prediction process to enhance the quality oftraditionalpredictions, taking advantage of parallel computing. This strategy is based on an adjustment stage which is carried out by a well-known evolutionary technique: Genetic Algorithms. The core of this framework is evaluated according to the probability theory principles. Thus, a strong statistical study is presented and oriented towards the characterization of such an adjustment technique in order to help the operation managers deal with the two aspects previously mentioned: time and quality. The experimental work in this paper is based on a region in Spain which is one of the most prone to forest fires:El Cap de Creus.

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