Results 21 to 30 of about 144,133 (245)
A Multiobjective Optimization Problem (MOP) requires the optimization of several objective functions simultaneously, usually in conflict with each other.
André O. Martins +3 more
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METHOD OF ARTIFICIAL FITNESS LEVELS FOR DYNAMICS ANALYSIS OF EVOLUTIONARY ALGORITHMS [PDF]
Subject of Research. Currently, in the theory of evolutionary computation, it becomes relevant to analyze not just the runtime of evolutionary algorithms, but also their dynamics.
Maxim V. Buzdalov, Dmitry V. Vinokurov
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A new evolutionary algorithm: Learner performance based behavior algorithm
A novel evolutionary algorithm called learner performance based behavior algorithm (LPB) is proposed in this article. The basic inspiration of LPB originates from the process of accepting graduated learners from high school in different departments at ...
Chnoor M. Rahman, Tarik A. Rashid
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Autonomous Evolutionary Algorithm [PDF]
Evolutionary algorithms (EA) are randomized heuristic search methods based on the principles of natural evolution (Banzhaf et al., 1998; Goldberg, 1989; Holland, 1975; Back, 1996; Koza, 1992). If we know how to describe the problem using the terminology of artificial evolution, the EAs are quite easy to apply.
openaire +3 more sources
Ameliorated Ensemble Strategy-Based Evolutionary Algorithm with Dynamic Resources Allocations
In the last two decades, evolutionary computing has become the mainstream to attract the attention of the experts in both academia and industrial applications due to the advent of the fast computer with multi-core GHz processors have had a capacity of ...
Wali Khan Mashwani +3 more
doaj +1 more source
An Experimental Study on Competitive Coevolution of MLP Classifiers
This paper investigates the effectiveness and efficiency of two competitive (predator-prey) evolutionary procedures for training multi-layer perceptron classifiers: Co-Adaptive Neural Network Training, and a modified version of Co-Evolutionary Neural ...
Marco Castellani, Rahul Lalchandani
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A Customized Differential Evolutionary Algorithm for Bounded Constrained Optimization Problems
Bound-constrained optimization has wide applications in science and engineering. In the last two decades, various evolutionary algorithms (EAs) were developed under the umbrella of evolutionary computation for solving various bound-constrained benchmark ...
Wali Khan Mashwani +4 more
doaj +1 more source
Personalized-Template-Guided Intelligent Evolutionary Algorithm
Existing heuristic algorithms are based on inspiration sources and have not yet done a good job of basing themselves on optimization principles to minimize and utilize historical information, which may lead to low efficiency, accuracy, and stability of ...
Dongni Hu +4 more
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Tumor mutational burden as a determinant of metastatic dissemination patterns
This study performed a comprehensive analysis of genomic data to elucidate whether metastasis in certain organs share genetic characteristics regardless of cancer type. No robust mutational patterns were identified across different metastatic locations and cancer types.
Eduardo Candeal +4 more
wiley +1 more source
Aldehyde dehydrogenase 1A1 (ALDH1A1) is a cancer stem cell marker in several malignancies. We established a novel epithelial cell line from rectal adenocarcinoma with unique overexpression of this enzyme. Genetic attenuation of ALDH1A1 led to increased invasive capacity and metastatic potential, the inhibition of proliferation activity, and ultimately ...
Martina Poturnajova +25 more
wiley +1 more source

