Results 31 to 40 of about 3,003,352 (244)
An Experimental Study on Competitive Coevolution of MLP Classifiers
Mendel, 2017 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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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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Orbit Transfer Manoeuvres as a Test Benchmark for Comparison Metrics of Evolutionary Algorithms [PDF]
, 2009 In the present paper some metrics for evaluating the performance of evolutionary algorithms are considered. The capabilities of two different optimisation approaches are compared on three test cases, represented by the optimisation of orbital transfer ...
G. Avanzini +6 more
core +1 more source
Personalized-Template-Guided Intelligent Evolutionary Algorithm
Applied SciencesExisting 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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Ligand‐dependent transcriptional heterogeneity in cell cycle gene expression delays G1/S entry
FEBS Letters, EarlyView.EGF and HRG induce distinct G1/S progression programs in ErbB2‐amplified BT474 breast cancer cells. Despite activating the potent ErbB2–ErbB3 heterodimer, HRG does not accelerate cell‐cycle entry. Instead, EGF promotes earlier restriction‐point passage via ERK–FOS signaling, whereas HRG activates the AKT–MYC axis, driving transcriptional heterogeneity ...
Ririn Rahmala Febri +5 more
wiley +1 more source
CoRR, 2015 Outline of lectures course "Evolutionary Algorithms" (in Russian)
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Decomposition-Based Multi-Objective Evolutionary Algorithm Design Under Two Algorithm Frameworks
IEEE Access, 2020 The development of efficient and effective evolutionary multi-objective optimization (EMO) algorithms has been an active research topic in the evolutionary computation community. Over the years, many EMO algorithms have been proposed.
Lie Meng Pang, Hisao Ishibuchi, Ke Shang
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Emerging experimental and computational methods for studying redox‐regulated structural transitions
FEBS Letters, EarlyView.Redox reactions can reshape proteins and alter how they behave in cells, with important consequences for health and disease. This review explores emerging experimental and computational approaches for discovering these redox‐sensitive protein switches, revealing their structural effects, and predicting their behavior, opening new opportunities to ...
Tasneem Rass +2 more
wiley +1 more source
Parallelism and evolutionary algorithms [PDF]
IEEE Transactions on Evolutionary Computation, 2002 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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Applied Sciences, 2018 The friction interference in the pneumatic rotary actuator is the primary factor affecting the position accuracy of a pneumatic rotary actuator servo system.
Ke Li +3 more
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