Results 41 to 50 of about 62,767 (259)

Automatic hyperparameter selection in Autodock [PDF]

2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2018
Autodock is a widely used molecular modeling tool which predicts how small molecules bind to a receptor of known 3D structure. The current version of AutoDock uses meta-heuristic algorithms in combination with local search methods for doing the conformation search.
Rakhshani, Hojjat, Idoumghar, Lhassane, Lepagnot, Julien, Brévilliers, Mathieu, Keedwell, Edward   +4 more
openaire   +4 more sources

Scaling Laws for Hyperparameter Optimization

Advances in Neural Information Processing Systems 36, 2023
Accepted at NeurIPS ...
Arlind Kadra, Maciej Janowski, Martin Wistuba, Josif Grabocka   +3 more
openaire   +3 more sources

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source

A Multi-Hyperparameter Prediction Framework for Distributed Energy Trading on Photovoltaic Network

Tsinghua Science and Technology
The rapid evolution of distributed energy resources, particularly photovoltaic systems, poses a formidable challenge in maintaining a delicate balance between energy supply and demand while minimizing costs.
Chun Chen, Yong Zhang, Boon Han Lim, Li Ning, Shengzhong Feng, Peng Xie   +5 more
doaj   +1 more source

Is an Apple an Orange? A Large Language Model Benchmark for Candidate Term Extraction and Subclass Decisions Against Upper Ontologies in Engineering and Materials Science

Advanced Engineering Materials, EarlyView.
Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch, Maximilian Holland, Klaus Drechsler, Johannes Schilp   +3 more
wiley   +1 more source

Comprehensive Performance Assessment of Multi-Neural Ensemble Model for Mortality Prediction in ICU

IEEE Access
The development of models to estimate the mortality rate of critically ill patients in the intensive care unit(ICU) is significantly enhanced by technologies based on artificial intelligence.
M. Fathima Begum, Subhashini Narayan
doaj   +1 more source

Multimodal Data‐Driven Microstructure Characterization

Advanced Engineering Materials, EarlyView.
A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang, Santiago Benito, Özge Özgün, Sebastian Weber, Markus Stricker   +4 more
wiley   +1 more source

Optimizing SVM for argan tree classification using Sentinel-2 data: A case study in the Sous-Massa Region, Morocco

Revista de Teledetección
The development of efficient classifiers for land cover remains challenging due to the presence of hyperparameters in the model. Conventional approaches rely on manual tuning, which is both time-consuming and impractical, often leading to suboptimal ...
Abdelhak El Kharki, Jamila Mechbouh, Miriam Wahbi, Otmane Yazidi Alaoui, Hakim Boulaassal, Mustapha Maatouk, Omar El Kharki   +6 more
doaj   +1 more source

SHAP-Backed Hybrid Ensemble Model for Rice and Wheat Forecasting in Data-Scarce Environments [PDF]

International Journal of Mathematical, Engineering and Management Sciences
As the issue of agricultural sustainability has continued to increase, there has been a need to use data based solutions to improve agricultural productivity.
Harendra Singh Negi, Sushil Chandra Dimri   +1 more
doaj   +1 more source

Symbolic Regression and Multi‐Objective Optimization of the Flory–Huggins Interaction Parameter for Hydrogels

Advanced Engineering Materials, EarlyView.
We develop a data‐driven method to derive the mathematical expressions of the Flory–Huggins interaction parameter χ for the swelling behavior of temperature–responsive hydrogels. Starting from initial assumptions of χ, our workflow combines Bayesian optimization, Flory–Rehner theory, and symbolic regression to generate candidate χ expressions.
Yawen Wang, Adrian Ehrenhofer, Thomas Wallmersperger   +2 more
wiley   +1 more source