Results 231 to 240 of about 6,256,599 (289)

Advances in Machine Learning and Deep Learning Algorithm-Assisted Hyperspectral Imaging for Food Quality and Safety Assessment. [PDF]

Foods
Hu L, Dong Y, Hu C, Chen M, Li J.
europepmc   +1 more source

Lung biopsy strategies for childhood interstitial lung disease: Indications and techniques. [PDF]

J Int Med Res
Deng K, Lin L, Zhou W, Peng J.
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Automated modeling of population pharmacokinetic models using nlmixr2auto: a clinical trial and real-world data study

Huang Z, Fidler M, Nyang’wa B, Standing JF, Kloprogge F.   +4 more
europepmc   +1 more source

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A genetic algorithm with disruptive selection

IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), 1996
Genetic algorithms are a class of adaptive search techniques based on the principles of population genetics. The metaphor underlying genetic algorithms is that of natural evolution. Applying the "survival-of-the-fittest" principle, traditional genetic algorithms allocate more trials to above-average schemata.
Ting Kuo, Shu-Yuen Hwang
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Sexual Selection for Genetic Algorithms

Artificial Intelligence Review, 2003
Genetic Algorithms (GA) have been widely used in operations research and optimization since first proposed. A typical GA comprises three stages, the encoding, the selection and the recombination stages. In this work, we focus our attention on the selection stage of GA, and review a few commonly employed selection schemes and their associated scaling ...
Kai Song Goh, Andrew Lim 0001, Brian Rodrigues   +2 more
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On the effect of selection in genetic algorithms

Random Structures and Algorithms, 2001
Summary: To study the effect of selection with respect to mutation and mating in genetic algorithms, we consider two simplified examples in the infinite population limit. Both algorithms are modeled as measure valued dynamical systems and are designed to maximize a linear fitness on the half line. Thus, they both trivially converge to infinity.
Christian Mazza, Didier Piau
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Selecting Simulation Algorithm Portfolios by Genetic Algorithms

2010 IEEE Workshop on Principles of Advanced and Distributed Simulation, 2010
An algorithm portfolio is a set of algorithms that are bundled together for increased overall performance. While being mostly applied to computationally hard problems so far, we investigate portfolio selection for simulation algorithms and focus on their application to adaptive simulation replication.
Roland Ewald, Rene Schulz, Adelinde M. Uhrmacher   +2 more
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Algorithm Selection on Adaptive Operator Selection: A Case Study on Genetic Algorithms

2021
The present study applies Algorithm Selection (AS) to Adaptive Operator Selection (AOS) for further improving the performance of the AOS methods. AOS aims at delivering high performance in solving a given problem through combining the strengths of multiple operators.
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Probabilistic selection in cellular genetic algorithm

2012 8th International Conference on Natural Computation, 2012
In this paper, we introduce a new selection operator, namely, a Probabilistic Selection operator which allows us to control the selection pressure in cellular genetic algorithms through reducing the effective neighborhood radius. One advantage for having probabilistic selection is that, once we have our probability density function in hand, we can ...
Hann-Huei Foong, Soo Kar Leow, Teong-Joo Ong   +2 more
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