Results 91 to 100 of about 13,208 (247)

A Machine Learning Method for Maximum Temperature Bias Correction in Complex Terrain

Gaoyuan qixiang
To enhance the prediction accuracy of the 2-meter maximum temperature in complex terrain areas， this study developed a gradient modeling approach based on the LightGBM （Light Gradient Boosting Machine， LGB） algorithm， applied to the Sichuan Basin and its
Qiuxue ZHOU, Liangmin FENG, Chaoping CHEN, Di HU   +3 more
doaj   +1 more source

How AI and Digital Technologies Can Enhance Sustainable Livestock Manure Management: An Overview From Treatment to Distribution

Sustainable Development, EarlyView.
ABSTRACT Sustainable livestock manure management sits at the nexus of climate, nutrient circularity and water quality. This review explores how artificial intelligence (AI) and digital platforms are used across four management stages, that is, treatment, storage, valorisation and distribution, and figures out where integration fails to deliver ...
Zhan Shi, Feihong Liang, Francesco Marinello, Andrea Pezzuolo   +3 more
wiley   +1 more source

Enhancing Fraud Detection in Financial Transactions using LightGBM and Random Forest

Journal of Informatics and Web Engineering
In recent years, the frequency and complexity of financial fraud have been rising and have become an urgent challenge for the global financial system. Traditional rule-based detection methods struggle to cope with new types of fraud, especially in terms ...
Wan-Ping Khor, Kah-Ong Michael Goh, Check-Yee Law, Connie Tee, Yong-Wee Sek, Riasat Khan   +5 more
doaj   +1 more source

From Prediction to Prevention: An Explainable GeoAI Framework for Flood Susceptibility and Urban Exposure Assessment Using Machine and Deep Learning Models

Sustainable Development, EarlyView.
ABSTRACT Rapid urbanisation and intensifying rainfall have increased cities' vulnerability to flooding, posing major challenges to sustainable development. Although machine learning models have improved flood prediction accuracy, most remain limited by their black‐box nature and lack of actionable insights.
Abdulwaheed Tella, Izni Zahidi, Chow Ming Fai, Chukwuma Okolie, Quoc Bao Pham   +4 more
wiley   +1 more source

Artificial intelligence empowers targeted protein degradation: Core technological innovations, multi‐scenario applications, and translational prospects

Smart Molecules, EarlyView.
AI is transforming TPD by improving the design, prediction, and optimization of degraders such as PROTACs, molecular glues, and LYTACs. This review summarizes key AI‐driven advances, highlights applications across drug discovery stages, and discusses remaining challenges and future directions for accelerating the development of therapies against ...
Shuanglin Qin, Rui Peng, Guangshuai Zhang, Si Yan, Jin Xiao, Zishu Liu, Ziyu Tan, Qingqing Xie, Shangjie Li, Wei Luo, Xiaohe Xiao   +10 more
wiley   +1 more source

Unveiling financial well-being: Insights from retired people in Third Age group in Poland, Spain and Denmark

Economics and Business Review
The study investigates the financial well-being of older people in Poland, Spain and Denmark, with a particular focus on their ability to make ends meet.
Jajko-Siwek Alicja
doaj   +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

Bath Vibration During Open Eye Formation in a Physical Model of a Steelmaking Ladle

steel research international, EarlyView.
Using a physical model, this study shows that vibration measurements reliably predict open eye size in steelmaking ladles, offering a practical alternative to visual monitoring. Vessel vibrations stabilize faster than the open eye, except at high frequencies near the bottom.
Mika Pylvänäinen, Juhani Nissilä, Ville‐Valtteri Visuri, Aki Sorsa, Matias Hauru, Jouni Laurila, Toni Liedes   +6 more
wiley   +1 more source

ОПТИМІЗАЦІЯ ГІБРИДНИХ МОДЕЛЕЙ НА ОСНОВІ TCN, LSTM, LIGHTGBM ДЛЯ ПРОГНОЗУВАННЯ ЕНЕРГОСПОЖИВАННЯ В РОЗУМНИХ БУДИНКАХ

Кібербезпека: освіта, наука, техніка
Точне короткострокове прогнозування навантаження є ключовим завданням для ефективного управління енергоресурсами в системах розумного будинку. Гібридні моделі, що поєднують архітектури глибокого навчання (DL) та ансамблі дерев рішень, є провідним ...
Дмитро Ніщеменко
doaj   +1 more source

Application of Intelligent Systems in CO2 Management: State of the Art and Future Prospects

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Machine learning (ML) integration is becoming increasingly popular in advancing the 4th industrial revolution, known as Industry 4.0. This review paper examines ML applications in CO2 management stages: emission, capture, and conversion. ML models, including multiple linear regression (MLR), multiple nonlinear regression (MNLR), and artificial
Muhammad Zulkefal, Iftikhar Ahmad, Asad Habib, Asad Ayub, Hamza Sethi, Ihsanullah Ihsanullah, Hakan Caliskan, Hiki Hong   +7 more
wiley   +1 more source