Results 21 to 30 of about 1,981,405 (253)
Effectiveness and limitations of parameter tuning in reducing biases of top-of-atmosphere radiation and clouds in MIROC version 5 [PDF]
Geoscientific Model Development, 2017 This study discusses how much of the biases in top-of-atmosphere (TOA) radiation and clouds can be removed by parameter tuning in the present-day simulation of a climate model in the Coupled Model Inter-comparison Project phase 5 (CMIP5) generation ...
T. Ogura +12 more
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Hierarchical Collaborative Hyper-parameter Tuning [PDF]
, 2022 Hyper-parameter Tuning is among the most critical stages in building machine learning solutions. This paper demonstrates how multi-agent systems can be utilized to develop a distributed technique for determining near-optimal values for any arbitrary set ...
Esmaeili, Ahmad +2 more
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High dimensional parameter tuning for event generators
European Physical Journal C: Particles and Fields, 2020 Monte Carlo Event Generators are important tools for the understanding of physics at particle colliders like the LHC. In order to best predict a wide variety of observables, the optimization of parameters in the Event Generators based on precision data ...
Johannes Bellm, Leif Gellersen
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Quadrature Signal Generator with Improved Dc Offset Compensation
Advances in Electrical and Computer Engineering, 2021 In this paper a second order generalized integrator (SOGI) based quadrature signal generator (QSG) is proposed with the improved DC offset compensation parameter tuning procedure.
STOJIC, D.
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Optimization of Neural Network-Based Self-Tuning PID Controllers for Second Order Mechanical Systems
Applied Sciences, 2021 The feasibility of a neural network method was discussed in terms of a self-tuning proportional–integral–derivative (PID) controller. The proposed method was configured with two neural networks to dramatically reduce the number of tuning attempts with a ...
Yong-Seok Lee, Dong-Won Jang
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Recent Development in Automatic Parameter Tuning for Metaheuristics
, 2010 Parameter tuning is an optimization problem with the objective of finding good static pa-rameter settings before the execution of a metaheuristic on a problem at hand.
Dobslaw, Felix,
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Optimizing Performance of Hadoop with Parameter Tuning
ITM Web of Conferences, 2017 Optimizing Hadoop with the parameter tuning is an effective way to greatly improve the performance, but it usually costs too much time to identify the optimal parameters configuration because there are many parameters. Users are always blindly adjust too
Chen Xiang +4 more
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A parameter-free learning automaton scheme
Frontiers in Neurorobotics, 2022 For a learning automaton, a proper configuration of the learning parameters is crucial. To ensure stable and reliable performance in stochastic environments, manual parameter tuning is necessary for existing LA schemes, but the tuning procedure is time ...
Xudie Ren, Shenghong Li, Hao Ge
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Calibrating the GAMIL3-1° climate model using a derivative-free optimization method [PDF]
Geoscientific Model DevelopmentParameterization in climate models often involves parameters that are poorly constrained by observations or theoretical understanding alone. Manual tuning by experts can be time-consuming, subjective, and prone to underestimating uncertainties. Automated
W. Liang +10 more
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Hyper-parameter Tuning for Quantum Support Vector Machine
Advances in Electrical and Computer Engineering, 2022 In recent years, the positive effect of quantum techniques on machine learning methods have been studied. Especially in training big data, quantum computing is beneficial in terms of speed.
DEMIRTAS, F., TANYILDIZI, E.
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