Results 71 to 80 of about 101,601 (232)

Harnessing Machine Learning to Understand and Design Disordered Solids

Advanced Intelligent Discovery, EarlyView.
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley   +1 more source

Generating Spatial Distribution and Forecasting the Rainfall by Suitable ML Models-A Case Study of Aiyar River Basin, Tiruchirappalli District [PDF]

MATEC Web of Conferences
Rainfall plays a prominent role in managing of water resources. The accurate prediction of rainfall is the greatest challenge in the field of hydrologic studies. The prediction of rainfall is necessary to overcome natural disasters like flood and drought.
Natarajan Surendar, Jegan Bharath Kumar A.   +1 more
doaj   +1 more source

Peramalan Jumlah Penumpang Berangkat Melalui Transportasi Udara di Sulawesi Tengah Menggunakan Support Vector Regression (SVR)

Jambura Journal of Mathematics, 2020
Sulawesi Tengah memiliki tujuh bandara sebagai akses transportasi udara keluar atau masuk. Jumlah penumpang berangkat menggunakan transportasi udara melalui ketujuh bandara tersebut mengalami fluktuasi setiap bulannya.
Drajat Indra Purnama, Oki Prasetia Hendarsin   +1 more
doaj   +1 more source

Support Vector Regression Based S-transform for Prediction of Single and Multiple Power Quality Disturbances [PDF]

, 2009
This paper presents a novel approach using Support Vector Regression (SVR) based S-transform to predict the classes of single and multiple power quality disturbances in a three-phase industrial power system.
Faisal , M. F., Hussain, Aini, Mohamed , Azah, Nizam , Muhammad   +3 more
core  

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

Three Synchronized, Miniaturized, Wireless Inertial Measurement Unit Sensors for Automated Gait and Balance Analysis System

Advanced Intelligent Systems, EarlyView.
This study presents a compact, three IMU wearable system that enables accurate motion capture and robust gait‐feature extraction, thereby supporting reliable machine learning‐based balance evaluation. Accurate assessment of balance is critical for fall prevention and targeted rehabilitation, particularly in older adults and individuals with ...
Seok‐Hoon Choi, Ki‐Hoon Kim, Heung Jin Park, Yuna Kim, Hyunjin Lee, Yu Bin Lee, Youn Joung Kang, Sungchul Huh, Min‐Ho Seo   +8 more
wiley   +1 more source

Data‐Driven Design of Bimodal Networked Dielectric Elastomers for High‐Performance Artificial Muscles

Advanced Intelligent Systems, EarlyView.
A data‐efficient artificial intelligence‐assisted framework, which integrates experimental data with machine learning, is developed for the design of bimodal networked dielectric elastomers (DEs) as advanced artificial muscles. It adopts neural networks to predict DEs’ mechanical properties and support vector machines to classify electromechanical ...
Ofoq Normahmedov, Hanzhi Ma, Junbo Peng, Huifeng Dong, Jiangshan Zhuo, Mengke Shi, Lvting Wang, Shengchao Jiang, Ye Shi   +8 more
wiley   +1 more source

Metalearning‐Driven Inverse Optimization for Precision Microstructure Fabrication in Digital Light Processing Three‐Dimensional Printing

Advanced Intelligent Systems, EarlyView.
Metalearning‐based inverse optimization enables precise microscale three‐dimensional printing using a DLP system. Distorted structures from conventional printing are analyzed via neural network regression, which predicts optimal exposure time and mask design.
Jae Won Choi, Suhyeong Lim, Jeongsu Lee, Cheol Woo Ha   +3 more
wiley   +1 more source

HKF-SVR Optimized by Krill Herd Algorithm for Coaxial Bearings Performance Degradation Prediction

Sensors, 2020
In real industrial applications, bearings in pairs or even more are often mounted on the same shaft. So the collected vibration signal is actually a mixed signal from multiple bearings.
Fang Liu, Liubin Li, Yongbin Liu, Zheng Cao, Hui Yang, Siliang Lu   +5 more
doaj   +1 more source

Integrating Artificial Intelligence With Droplet‐Based Microfluidics: Advances, Challenges, and Emerging Opportunities

Advanced Intelligent Systems, EarlyView.
Droplet‐based microfluidics enables precise, high‐throughput microscale reactions but continues to face challenges in scalability, reproducibility, and data complexity. This review examines how artificial intelligence enhances droplet generation, detection, sorting, and adaptive control and discusses emerging opportunities for clinical and industrial ...
Junyan Lai, Sukrit Gaira, Rongfeng Wang, Qingtian Zhang, Ming Li, Liao Wu, Diangeng Li, Yi Li, Chengchen Zhang, Jinhong Guo, Shi‐Yang Tang   +10 more
wiley   +1 more source