Results 211 to 220 of about 151,552 (262)

Video-based detection of Delirium in hospitalized adults. [PDF]

PLOS Digit Health
Mendu M, Tesh RA, Pellerin K, Steward GE, Cerda IH, Williams M, Colman M, Shah S, Lam AD, Cash SS, Westover MB, Kimchi EY.   +11 more
europepmc   +1 more source

Evaluation of Sex-Related Morphometry of the Sella Turcica in Autopsy Using Machine Learning. [PDF]

Diagnostics (Basel)
Depreli A, Ozturk MF, Nasip OF, Yılmaz H, Bakan HU, Sahin NE.   +5 more
europepmc   +1 more source

Strain-level transmission inference across multi-kingdom metagenomic data using TRACS. [PDF]

Nat Microbiol
Tonkin-Hill G, Shao Y, Zarebski AE, Mallawaarachchi S, Xie O, Mäklin T, Thorpe HA, Davies MR, Bentley SD, Lawley TD, Corander J.   +10 more
europepmc   +1 more source

Research progress on precision orchard yield estimation based on multi-source information perception sensors. [PDF]

Front Plant Sci
Rong Z, Ru Y, Zhang X, Fang S, Zhou H, Jiang X.   +5 more
europepmc   +1 more source

A Joint Framework of IMM-LSTM-C Tracking and IBPDO-Based Node Selection for Energy-Efficient Cooperative Tracking in Underwater Acoustic Sensor Networks. [PDF]

Sensors (Basel)
Zhang W, Hou Y, Zhu H.
europepmc   +1 more source

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Subspace estimation of distribution algorithms: To perturb part of all variables in estimation of distribution algorithms

Applied Soft Computing Journal, 2011
Abstract: In the traditional estimation of distribution algorithms (EDAs), all the variables of candidate individuals are perturbed through sampling from a probability distribution of promising individuals. However, it may be unnecessary for the EDAs to perturb all variables of candidate individuals at each generation.
Yi Hong, Sam Kwong
exaly   +2 more sources

An introduction and survey of estimation of distribution algorithms

Swarm and Evolutionary Computation, 2011
Abstract Estimation of distribution algorithms (EDAs) are stochastic optimization techniques that explore the space of potential solutions by building and sampling explicit probabilistic models of promising candidate solutions. This explicit use of probabilistic models in optimization offers some significant advantages over other types of ...
Mark Hauschild, Martin Pelikan
exaly   +2 more sources

On the convergence of a class of estimation of distribution algorithms

IEEE Transactions on Evolutionary Computation, 2004
We investigate the global convergence of estimation of distribution algorithms (EDAs). In EDAs, the distribution is estimated from a set of selected elements, i.e., the parent set, and then the estimated distribution model is used to generate new elements.
Qingfu Zhang
exaly   +2 more sources

Unbiasedness of estimation-of-distribution algorithms

Theoretical Computer Science, 2019
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Tobias Friedrich 0001, Timo Kötzing, Martin S. Krejca   +2 more
openaire   +1 more source

Space Complexity of Estimation of Distribution Algorithms

Evolutionary Computation, 2005
In this paper, we investigate the space complexity of the Estimation of Distribution Algorithms (EDAs), a class of sampling-based variants of the genetic algorithm. By analyzing the nature of EDAs, we identify criteria that characterize the space complexity of two typical implementation schemes of EDAs, the factorized distribution algorithm and ...
Yong Gao 0001, Joseph C. Culberson
openaire   +2 more sources