Results 21 to 30 of about 151,967 (341)
Sensors, 2021 Electrical resistivity is used to obtain various types of information for soil strata. Hence, the prediction of electrical resistivity is helpful to predict the future behavior of soil.
Seung-Jae Lee, Hyung-Koo Yoon
doaj +1 more source
Hyperparameter Optimization for AST Differencing
IEEE Transactions on Software Engineering, 2023 Computing the differences between two versions of the same program is an essential task for software development and software evolution research. AST differencing is the most advanced way of doing so, and an active research area. Yet, AST differencing algorithms rely on configuration parameters that may have a strong impact on their effectiveness.
Matias Martinez +2 more
openaire +5 more sources
kravitsjacob/multiobjective-hyperparameter: Update function names
, 2022 Updated function names PEP8 compliant What's Changed Update function names by @kravitsjacob in https://github.com/kravitsjacob/multiobjective-hyperparameter/pull/1 New Contributors @kravitsjacob made their first contribution in https://github.com ...
Jacob Kravits
core +1 more source
Hyperparameter Search for Machine Learning Algorithms for Optimizing the Computational Complexity
Processes, 2023 For machine learning algorithms, fine-tuning hyperparameters is a computational challenge due to the large size of the problem space. An efficient strategy for adjusting hyperparameters can be established with the use of the greedy search and Swarm ...
Yasser A. Ali +3 more
semanticscholar +1 more source
Diagnostics, 2022 Numerous research have demonstrated that Convolutional Neural Network (CNN) models are capable of classifying visual field (VF) defects with great accuracy.
Masyitah Abu +6 more
doaj +1 more source
This file contains hyperparameter tuning experiments.
Yiran Chen, Hai Li, Huanrui Yang
+6 more sources
Remote Sensing, 2022 Aflaj (plural of falaj) are tunnels or trenches built to deliver groundwater from its source to the point of consumption. Support vector machine (SVM) and extreme gradient boosting (XGB) machine learning models were used to predict groundwater aflaj ...
Khalifa M. Al-Kindi, Saeid Janizadeh
doaj +1 more source
Advanced hyperparameter optimization of deep learning models for wind power prediction
Renewable Energy, 2023 The uncertainty of wind power as the main obstacle of its integration into the power grid can be addressed by an accurate and efficient wind power forecast.
Shahram Hanifi +2 more
semanticscholar +1 more source
Hyperparameter search grids and selected hyperparameter values for each model.
, 2023 Hyperparameter search grids and selected hyperparameter values for each model.
Miguel Rocha (1426192) +2 more
core +1 more source
Deep Learning in Forest Structural Parameter Estimation Using Airborne LiDAR Data
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Accurately estimating and mapping forest structural parameters are essential for monitoring forest resources and understanding ecological processes. The novel deep learning algorithm has the potential to be a promising approach to improve the estimation ...
Hao Liu +7 more
doaj +1 more source