Results 11 to 20 of about 5,786,914 (366)
Algorithmicity of Evolutionary Algorithms [PDF]
Studies in Logic, Grammar and Rhetoric, 2020 In the first part of our article we will refer the penetration of scientific terms into colloquial language, focusing on the sense in which the concept of an algorithm currently functions outside its original scope.
Leciejewski Sławomir +1 more
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Evaluating evolutionary algorithms
Artificial Intelligence, 1996 AbstractTest functions are commonly used to evaluate the effectiveness of different search algorithms. However, the results of evaluation are as dependent on the test problems as they are on the algorithms that are the subject of comparison. Unfortunately, developing a test suite for evaluating competing search algorithms is difficult without clearly ...
Darrell Whitley +3 more
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Evolutionary Algorithms in Intelligent Systems [PDF]
Mathematics, 2020 Evolutionary algorithms and metaheuristics are widely used to provide efficient and effective approximate solutions to computationally difficult optimization problems [...]
Alfredo Milani
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, 2018 Evolutionary algorithms (EAs) are population-based metaheuristics, originally inspired by aspects of natural evolution. Modern varieties incorporate a broad mixture of search mechanisms, and tend to blend inspiration from nature with pragmatic engineering concerns; however, all EAs essentially operate by maintaining a population of potential solutions ...
Michael A. Lones, David Corne
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Hybridization of Evolutionary Algorithms [PDF]
, 2011 Evolutionary algorithms are good general problem solver but suffer from a lack of domain specific knowledge. However, the problem specific knowledge can be added to evolutionary algorithms by hybridizing. Interestingly, all the elements of the evolutionary algorithms can be hybridized.
Fister, Iztok +2 more
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A Transfer Learning Approach to Breast Cancer Classification in a Federated Learning Framework
IEEE Access, 2023 Artificial intelligence (AI) technologies have seen strong development. Many applications now use AI to diagnose breast cancer. However, most new research has only been conducted in centralized learning (CL) environments, which entails the risk of ...
Y. Nguyen Tan +4 more
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Large-scale bound constrained optimization based on hybrid teaching learning optimization algorithm
Alexandria Engineering Journal, 2021 Evolutionary computing is an exciting sub-field of soft computing. Many evolutionary algorithm based on the Darwinian principles of natural selection are developed under the umbrella of EC in the last two decades.
Wali Khan Mashwani +4 more
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The evolutionary forest algorithm [PDF]
Bioinformatics, 2007 AbstractMotivation: Gene genealogies offer a powerful context for inferences about the evolutionary process based on presently segregating DNA variation. In many cases, it is the distribution of population parameters, marginalized over the effectively infinite-dimensional tree space, that is of interest.
Leman, Scotland C +3 more
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International Journal of Adaptive Control and Signal Processing, EarlyView., 2023 Summary In this contribution, we propose a detailed study of interpolation‐based data‐driven methods that are of relevance in the model reduction and also in the systems and control communities. The data are given by samples of the transfer function of the underlying (unknown) model, that is, we analyze frequency‐response data.
Quirin Aumann, Ion Victor Gosea
wiley +1 more source
Meta-heuristic algorithms in car engine design: a literature survey [PDF]
, 2015 Meta-heuristic algorithms are often inspired by natural phenomena, including the evolution of species in Darwinian natural selection theory, ant behaviors in biology, flock behaviors of some birds, and annealing in metallurgy.
Tayarani-N, Mohammad-H. +2 more
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