Results 51 to 60 of about 4,344 (219)

LLMs as Representation Generators for Gradient‐Free Scientific Optimization: A Case Study in Battery Fast Charging

Advanced Science, EarlyView.
Large language models serve as representation generators for gradient‐free scientific optimization. Two complementary approaches produce executable battery‐charging policies either directly or through LLM‐designed neural representations coupled to Bayesian optimization.
Ge Lei, Ferran Brosa Planella, Sterling G. Baird, Samuel J. Cooper   +3 more
wiley   +1 more source

Comparative Analysis of Automated Machine Learning for Hyperparameter Optimization and Explainable Artificial Intelligence Models

IEEE Access
Artificial intelligence (AI) has been increasingly applied to solve complex real-world problems. One of the most significant challenges in AI lies in selecting and fine-tuning the optimal algorithm for a given task.
Muhammad Salman Khan, Tianbo Peng, Hanzlah Akhlaq, Muhammad Adeel Khan   +3 more
doaj   +1 more source

Assessing Mesoscale Heterogeneities in Hard Carbon Electrodes Through Deep Learning‐Assisted FIB‐SEM Characterization, Manufacturing and Electrochemical Modeling

Advanced Energy Materials, EarlyView.
A combination of discrete and finite element method models for the current collector deformation and electrochemical performance analysis, respectively. The models are calibrated and validated with electrochemical and imaging data of hard carbon electrodes. These electrodes were manufactured with different parameters (slurry solid contents of 35 and 40
Soorya Saravanan, Imelda Cardenas‐Sierra, Pei Sun, Hari Raj, Daniele Duranti, Mahnoor Nafees, Edoardo Rossi, Marco Sebastiani, Paul Vigneaux, Martin Petit, Maxime Moreaud, Francisco Fernandez, Alejandro A. Franco   +12 more
wiley   +1 more source

Optimizing XGBoost for Heart Disease Risk Classification Using Optuna and Random Search on the Behavioral Risk Factor Surveillance System (BRFSS) 2023 Dataset

Journal of Applied Informatics and Computing
Heart disease is a critical public health issue in Indonesia, contributing to approximately 1,5 million deaths annually. Although machine learning methods, particularly Extreme Gradient Boosting (XGBoost), have demonstrated strong performance in medical ...
Muhammad Dzaky, Adam Prayogo Kuncoro, Riyanto Riyanto   +2 more
doaj   +1 more source

Embedded Morgan Fingerprints for More Efficient Molecular Property Predictions With Machine Learning

Advanced Intelligent Discovery, EarlyView.
High dimensionality of Morgan fingerprints causes overfitting and slow training. Embedded Morgan Fingerprint (eMFP) compresses this encoding while keeping key structural information intact. Tested on five regression models across three databases for HOMO–LUMO gap prediction, eMFP outperforms standard fingerprints, training faster on large, high ...
Emilio Nuñez‐Andrade, Isaac Vidal‐Daza, Rafael Gómez‐Bombarelli, James W. Ryan, Francisco J. Martin‐Martinez   +4 more
wiley   +1 more source

Forecasting Topic, Word, and Hashtag Popularity on X (Twitter) Using LightGBM for Digital Marketing Optimization

Journal of Applied Informatics and Computing
This study presents a machine learning, based framework to forecast the popularity of topics, words, and hashtags on platform X (Twitter) for data-driven digital marketing optimization.
Deannisa Syafira Putri, Amri Muhaimin, Mohammad Idhom   +2 more
doaj   +1 more source

Overcoming the Nyquist Limit in Molecular Hyperspectral Imaging by Reinforcement Learning

Advanced Intelligent Discovery, EarlyView.
Explorative spectral acquisition guide automatically selects informative spectral bands to optimize downstream tasks, outperforming full‐spectrum acquisition. The selected hyperspectral data are used for tasks such as unmixing and segmentation. BandOptiNet encodes selection states and outputs optimal bands to guide spectral acquisition. Recent advances
Xiaobin Tang, Yongqing Zhang, Xinyu Deng, Hyeon Jeong Lee, Delong Zhang   +4 more
wiley   +1 more source

Anti-Data Leakage Pipeline for Differentiated Thyroid Cancer Recurrence Prediction: Integrating SMOTE, Optuna-based Optimization, and Bootstrap BCa Validation

Journal of Applied Informatics and Computing
Thyroid cancer recurrence prediction remains a critical clinical challenge, as early identification of high-risk patients enables targeted monitoring and intervention.
Deri Rosadi, Sindhu Rakasiwi
doaj   +1 more source

Multi‐Property Machine Learning Models to Accelerate the Transition Toward Bio‐Based Emulsion Polymers

Advanced Intelligent Discovery, EarlyView.
A machine learning framework simultaneously predicts four critical properties of monomers for emulsion polymerization: propagation rate constant, reactivity ratios, glass transition temperature, and water solubility. These tools can be used to systematically identify viable bio‐based monomer pairs as replacements for conventional formulations, with ...
Kiarash Farajzadehahary, Nicholas Ballard   +1 more
wiley   +1 more source

LightGBM for Liver Disease Detection with Hybrid Hyperparameter Optimization

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
In response to the growing burden of liver-related disorders, this research develops a supervised learning approach using the Light Gradient Boosting Machine (LightGBM) algorithm to support the early identification of Non-Alcoholic Fatty Liver Disease ...
Fajar Ratnawati, Agus Tedyyana, Johny Custer   +2 more
doaj   +1 more source