Results 21 to 30 of about 123,558 (314)
Application of symbolic regression for constitutive modeling of plastic deformation
In numerical process simulations, in-depth knowledge about material behavior during processing in the form of trustworthy material models is crucial.
Evgeniya Kabliman +4 more
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A Transfer Learning Approach to Breast Cancer Classification in a Federated Learning Framework
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
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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Parallelism and evolutionary algorithms [PDF]
This paper contains a modern vision of the parallelization techniques used for evolutionary algorithms (EAs). The work is motivated by two fundamental facts: 1) the different families of EAs have naturally converged in the last decade while parallel EAs (PEAs) are still lack of unified studies; and 2) there is a large number of improvements in these ...
Enrique Alba 0001, Marco Tomassini
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Signal synthesis by means of evolutionary algorithms [PDF]
In this article, we investigate a procedure for generating signals with genetic algorithms. Signals are obtained from elementary patterns characterized by different degrees of freedom.
B. Sareni +5 more
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New observer-based control design for mismatched uncertain systems with time-delay
In this paper, the state estimation problem for a class of mismatched uncertain time-delay systems is addressed. The estimation uses observer-based control techniques.
Huynh Van Van
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This paper proposes a new evolutionary algorithm namely Evolutionary Mating Algorithm (EMA) to solve constrained optimization problems. The algorithm is based on the adoption of random mating concept from Hardy–Weinberg equilibrium and crossover index in order to produce new offspring. In this algorithm, effect of the environmental factor (i.e.
Mohd Herwan Sulaiman +4 more
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Predictive models are increasingly deployed within smart manufacturing for the control of industrial plants. With this arises, the need for long‐term monitoring of model performance and adaptation of models if surrounding conditions change and the ...
Florian Bachinger +2 more
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Hybridization of Evolutionary Algorithms [PDF]
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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Bias and Variance Analysis of Contemporary Symbolic Regression Methods
Symbolic regression is commonly used in domains where both high accuracy and interpretability of models is required. While symbolic regression is capable to produce highly accurate models, small changes in the training data might cause highly dissimilar ...
Lukas Kammerer +2 more
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