Results 21 to 30 of about 151,552 (262)
A Survey of Machine Learning Assisted Continuous-Variable Quantum Key Distribution
Information, 2023 Continuous-variable quantum key distribution (CV-QKD) shows potential for the rapid development of an information-theoretic secure global communication network; however, the complexities of CV-QKD implementation remain a restrictive factor.
Nathan K. Long +2 more
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Distributed State Estimation for Multi-Feeder Distribution Grids
IEEE Open Journal of Instrumentation and Measurement, 2022 The real-time monitoring of electric distribution grids via state estimation is a fundamental requirement to deploy smart automation and control in the distribution system.
Marco Pau +4 more
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International Journal of Applied Earth Observations and Geoinformation, 2022 Leaf chlorophyll plays an important role in forest management and ecosystem balance. Hyperspectral images have been widely applied in leaf chlorophyll content (LCC) estimation.
Lu Xu +7 more
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A factor graph based genetic algorithm
International Journal of Applied Mathematics and Computer Science, 2014 We propose a new linkage learning genetic algorithm called the Factor Graph based Genetic Algorithm (FGGA). In the FGGA, a factor graph is used to encode the underlying dependencies between variables of the problem.
Helmi B. Hoda +2 more
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Distributed Phase Estimation Algorithm and Distributed Shor's Algorithm
, 2023 Shor's algorithm is one of the most significant quantum algorithms. Shor's algorithm can factor large integers with a certain success probability in polynomial time. However, Shor's algorithm requires an unbearable amount of qubits in the NISQ (Noisy Intermediate-scale Quantum) era.
Xiao, Ligang +3 more
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IEEE Access, 2019 Estimation of Distribution Algorithms (EDAs) maintain and iteratively update a probabilistic model to tackle optimization problems. The Boltzmann Probability Distribution Function (Boltzmann-PDF) provides advantages when used in energy based EDAs ...
Juan De Anda-Suarez +6 more
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Interactions and Dependencies in Estimation of Distribution Algorithms
2005 IEEE Congress on Evolutionary Computation, 2005 In this paper, we investigate two issues related to probabilistic modeling in Estimation of Distribution Algorithms (EDAs). First, we analyze the effect of selection in the arousal of probability dependencies in EDAs for random functions. We show that, for these functions, independence relationships not represented by the function structure are likely ...
Santana Hermida, Roberto +2 more
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IET Renewable Power Generation, 2022 Increasing the number of measurements in power distribution networks is crucial in improving the monitoring accuracy and operation quality. However, due to the large number of nodes in distribution networks, it is not economically possible to install ...
Mehdi Zeraati +3 more
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IEEE Access, 2021 We study the problem of semi-blind channel estimation and symbol detection in the uplink of multi-cell massive MIMO (multi-input multi-output) systems with spatially correlated time-varying channels.
Mort Naraghi-Pour +2 more
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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