Results 51 to 60 of about 4,028 (199)

Interpretable Machine Learning for Bandgap Prediction and Descriptor‐Guided Design Rules of Phosphates

Advanced Intelligent Discovery, EarlyView.
An explainable CatBoost model was trained to predict the bandgaps of 474 phosphate crystals based on composition and density descriptors. SHAP analysis identified two key variables—d‐electron‐count dispersion and atomic‐density dispersion—as the primary drivers of the model's predictions.
Wenhu Wang, Abudukadi Tudi, Ran An, Zhihua Yang   +3 more
wiley   +1 more source

Optuna-Optimized Machine Learning for Traffic Accident Severity Prediction in Jordan under Class Imbalance Conditions

Communications
A machine learning framework for predicting the traffic accident severity under class imbalance conditions is predented in Amman, Jordan. The methodology began with a preprocessing pipeline consisting of IQR-based (Interquartile range) outlier removal ...
Maen Qaseem Ghadi
doaj   +1 more source

Classification of Infected Salmon Using CNN Deep Features and Optuna-Optimized SVM [PDF]

Fish diseases are a major challenge in the aquaculture industry, impacting productivity and the economy, particularly in salmon farming. This study aims to develop an image classification system for infected salmon using Convolution Neural Network (CNN ...
Ayu, Putu Desiana Wulaning, Pradita, Agus Hendra, Hostiadi, Dandy Pramana   +2 more
core   +2 more sources

Catalyst‐Specialized Chemical Language Model Based on Transformer Variational Autoencoder for Catalyst Design and Discovery

Advanced Intelligent Discovery, EarlyView.
We present CatTransVAE, a catalyst‐specialized chemical language model (CLM) built on a transformer variational autoencoder (VAE), developed through pretraining on general compounds followed by fine‐tuning on diverse catalyst databases. A template‐guided generation framework is introduced to enable controlled catalyst design under structural ...
Apakorn Kengkanna, Masahito Ohue
wiley   +1 more source

Analysis of Ruddlesden‐Popper and Dion‐Jacobson 2D Lead Halide Perovskites Through Integrated Experimental and Computational Analysis

Battery Energy, Volume 4, Issue 2, March 2025.
Optimized ML framework for predicting RP and Dj phases in perovskite solar cells. ABSTRACT Two‐dimensional (2D) lead halide perovskites (LHPs) have captured a range of interest for the advancement of state‐of‐the‐art optoelectronic devices, highly efficient solar cells, next‐generation energy harvesting technologies owing to their hydrophobic nature ...
Basir Akbar, Kil To Chong, Hilal Tayara
wiley   +1 more source

Optuna-Optimized Ensemble and Neural Network Models for Static Characteristics Prediction of Active Bearings with Geometric Adjustments

Modelling
Active vibration control designs for journal bearings have improved rotordynamic stability and led to advancements in adjustable bearing types that enable precise control of bearing geometry. In this study, optimized machine learning (ML) algorithms were
Girish Hariharan, Ravindra Mallya, Nitesh Kumar, Deepak Doreswamy, Gowrishankar Mandya Chennegowda, Subraya Krishna Bhat   +5 more
doaj   +1 more source

A Semi‐Automated Microfluidic Platform Employing Machine Learning Analysis to Study Adhesion Kinetics in Acute Myeloid Leukemia

Microscopy Research and Technique, EarlyView.
We have developed a semi‐automated shear flow platform using bright‐field optics and a machine‐learning analysis algorithm to dissect tumor‐microenvironment interactions. The algorithm quantifies the extent of adhesion at the single‐cell level and delivers consistent results within minutes instead of hours, facilitating high‐throughput analysis ...
Driti Ashok, Dennis Raith, Gabriel Kalweit, Maria Kalweit, Anusha Klett, Justus Duyster, Jonas Bermeitinger, Tanja Nicole Hartmann   +7 more
wiley   +1 more source

Prediksi Inflasi Bulanan Menggunakan LightGBM dan Optimasi Hyperparameter Berbasis Optuna

Inflasi merupakan indikator makroekonomi penting yang mencerminkan perubahan tingkat harga barang dan jasa serta berpengaruh terhadap stabilitas ekonomi dan pengambilan kebijakan.
Dian Maharani, Muhammad Muharrom Al Haromainy, Anggraini Puspita Sari   +2 more
core   +1 more source

Time Series Extrinsic Regression for Smart Agriculture: Field‐Level Crop Yield Prediction From Multisource Agricultural Time Series

Quality and Reliability Engineering International, EarlyView.
ABSTRACT The growing availability of temporal data in agriculture has created new opportunities for data‐driven decision support systems aimed at improving the efficiency, sustainability, and adaptability of agricultural systems. Remote sensing platforms, weather‐related datasets, and field‐management records provide information on crop development and
Amalia Vanacore, Armando Ciardiello, Gennaro Pio Auricchio, Luigi Uccello, Annalisa Izzo   +4 more
wiley   +1 more source

BayesianKAN: A reaction condition optimization framework integrating Kolmogorov‐Arnold network and Bayesian optimization

Smart Molecules, EarlyView.
A novel BayesianKAN framework integrates Kolmogorov‐Arnold networks with Bayesian optimization to efficiently navigate complex factor spaces, accelerating the discovery of optimal reaction conditions for chemical synthesis. Abstract Efficient optimization of chemical reaction conditions is crucial for enhancing reaction yield and selectivity, yet ...
Juntao Wang, Yujing Zhao, Peiyu Yi, Liyuan Duan, Qingwei Meng, Qilei Liu   +5 more
wiley   +1 more source