Results 11 to 20 of about 1,087,874 (283)
Research on gas emission quantity prediction model based on EDA-IGA
Heliyon, 2023 In order to accurately predict the possible gas emission quantity in coal mines, it is proposed to use the multi-thread calculation of the Immune Genetic Algorithm (IGA) and injection of vaccines to improve the accuracy of prediction and combine the ...
Peng Ji, Shiliang Shi, Xingyu Shi
doaj +1 more source
Easy estimation by a new parameterization for the three-parameter lognormal distribution [PDF]
, 2013 A new parameterization and algorithm are proposed for seeking the primary relative maximum of the likelihood function in the three-parameter lognormal distribution.
Hirose, Hideo, Komori, Yoshio
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Variational semi-blind sparse deconvolution with orthogonal kernel bases and its application to MRFM [PDF]
, 2013 We present a variational Bayesian method of joint image reconstruction and point spread function (PSF) estimation when the PSF of the imaging device is only partially known.
Almeida +39 more
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Variational Quantum Algorithm Parameter Tuning with Estimation of Distribution Algorithms
2023 IEEE Congress on Evolutionary Computation (CEC), 2023 Variational quantum algorithms (VQAs) are hybrid approaches between classical and quantum computation, where a classical optimizer proposes parameter configurations for a quantum parametric circuit which is iteratively sampled. The overall performance of the algorithm depends on how the classical optimizer tunes the parameters of the quantum circuit ...
Soloviev, Vicente P. +2 more
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An Estimation of Distribution Algorithm With Multi-Leader Search
IEEE Access, 2020 The estimation of distribution algorithm (EDA) is a well-known stochastic search method but is easily affected by the ill-shaped distribution of solutions and can thus become trapped in stagnation.
Xiaofei Wang, Tong Han, Hui Zhao
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Bayesian Inference in Estimation of Distribution Algorithms [PDF]
, 2007 Metaheuristics such as Estimation of Distribution Algorithms and the Cross-Entropy method use probabilistic modelling and inference to generate candidate solutions in optimization problems.
Gallagher, Marcus +3 more
core +3 more sources
IEEE Access, 2019 According to the Karush-Kuhn-Tucker condition, the Pareto set (PS) of a continuous m-objective optimization problem is a continuous (m-1)-D piecewise manifold.
Guanjun Du, Guoxiang Tong, Naixue Xiong
doaj +1 more source
Journal of Low Frequency Noise, Vibration and Active Control, 2021 This paper proposes a direction of arrival estimation based on sparse signal reconstruction in the presence of alpha noise by the off-grid orthogonal matching pursuit algorithm.
LongKai Liang +3 more
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Collaborative Optimization Design for Centralized Networked Control System
IEEE Access, 2021 This paper proposes a collaborative optimization design for a kind of centralized networked control system based on jitter. After the analysis of the network delay and jitter on the performance of the Train Networked Control System (TNCS) based on the ...
Xiang Yan, Jun Li, Bizhou Mei
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Adaptive Estimation of Distribution Algorithms
, 2008 Estimation of distribution algorithms (EDAs) are evolutionary methods that use probabilistic models instead of genetic operators to lead the search. Most of current proposals on EDAs do not incorporate adaptive techniques. Usually, the class of probabilistic model employed as well as the learning and sampling methods are static.
Santana Hermida, Roberto +2 more
openaire +2 more sources