Beam Coefficient Prediction for Antenna Arrays Using Physics-Aware Convolutional Neural Networks by Glendyn D. King, Md Asaduzzaman Towfiq, Ali C. Gurbuz, Bedri A. Cetiner

“…This work introduces a novel approach for predicting the complex element weights of a rectangular planar phased array for a desired beam pattern using physics-aware convolutional neural networks (PA-CNN). …”
Get full text

Oilfield Production Prediction Method Based on Multi-Input CNN-LSTM With Attention Mechanism by Lihui Tang, Zhenpeng Wang, Yajun Gao, Hao Wu, Wenbo Zhang, Xiaoqing Xie

“…This model achieves prediction through two primary input paths: firstly, utilizing CNN to extract spatial dynamic features between wells to capture interwell production relationships and secondly, employing LSTM to extract temporal dynamic features of the oilfield. …”
Get full text

Multi-objective federated learning traffic prediction in vehicular network for intelligent transportation system by Arulmurgan Aalavanthar, Famila S., Shanmugam Sundaramurthy, Stefano Cirillo, Giandomenico Solimando, Giuseppe Polese

“…This work introduces a new approach to traffic prediction using multi-objective federated learning. …”
Get full text

Improving the Prediction of GNSS Satellite Visibility in Urban Canyons Based on a Graph Transformer by Shaolong Zheng, Kungan Zeng, Zhenni Li, Qianming Wang, Kan Xie, Ming Liu, Shengli Xie

“…The second challenge is degradation in the generalization performance of the multipath/NLOS prediction model when using data collected from different locations and periods. …”
Get full text

Energy consumption prediction using modified deep CNN-Bi LSTM with attention mechanism by Adel Binbusayyis, Mohemmed Sha

“…Furthermore, this model demonstrates a training time of 692.12 s and a prediction time of just 1.87 s. …”
Get full text

Spatio-Temporal Aware Collaborative Service Ranking Prediction in IoT-Enabled Edge Computing by Yuze Huang, Xiao Chen, Wenhui Zhang, Qianxi Li, He Li

“…Specifically, a spatial-aware service partial ranking model is introduced to generate partial rankings. …”
Get full text

EPIMR: Prediction of Enhancer-Promoter Interactions by Multi-Scale ResNet on Image Representation by Qiaozhen Meng, Yinuo Lyu, Xiaoqing Peng, Junhai Xu, Jijun Tang, Fei Guo

“…Many EPI predictors have been developed, but their prediction accuracy still needs to be enhanced. Here, we design a new model named EPIMR to identify enhancer-promoter interactions. …”
Get full text

TBM Enclosure Rock Grade Prediction Method Based on Multi-Source Feature Fusion by Yong Huang, Xiewen Hu, Shilong Pang, Wei Fu, Shuaipeng Chang, Bin Gao, Weihua Hua

“…Aiming to mitigate engineering risks such as tunnel face collapse and equipment jamming caused by poor geological conditions during the construction of tunnel boring machines (TBMs), this study proposes a TBM surrounding rock grade prediction method based on multi-source feature fusion. …”
Get full text

Extreme Short-Term Prediction of Unmanned Surface Vessel Nonlinear Motion Under Waves by Yiwen Wang, Jian Li, Shan Wang, Hantao Zhang, Long Yang, Weiguo Wu

“…At a Prediction Advance Time (PAT) of 3.7 s, the VMD-CNN-LSTM model improves prediction accuracy by 13.3% for a wave height of 1.015 m (Case I) and 54.9% for a wave height of 1.998 m (Case II) compared to the CNN-LSTM model. …”
Get full text

A novel theoretical approach to predict the interannual variability of sulfur in Mercury’s exosphere and subsurface by S. Verkercke, J. Y. Chaufray, F. Leblanc, A. Georgiou, M. S. Phillips, G. Munaretto, J. Lewis, A. Ricketts, L. Morrissey

Get full text

SERPINA3 predicts long-term neurological outcomes and mortality in patients with intracerebral hemorrhage by Pei Zheng, Zhihui Qi, Bin Gao, Yang Yao, Jingshan Chen, Hengri Cong, Yue Huang, Fu-Dong Shi

Get full text

TransXLT: A novel ZTD prediction method with SASR-based data reconstruction by Shicheng Xie, Xuexiang Yu, Jiajia Yuan, Xu Yang, Mingfei Zhu, Yuchen Han, Min Wei, Zhongchen Guo

“…Summary: Traditional Zenith Tropospheric Delay (ZTD) models often face difficulties in maintaining prediction accuracy under complex meteorological conditions and data loss. …”
Get full text

Predicting Solar Flares Using a Convolutional Neural Network with Extreme-ultraviolet Images by Yun Yang, Yi Wei Ni, P. F. Chen, Xue Shang Feng

“…This information, which cannot be provided by the data from a single active region alone, is demonstrated to be crucial in predicting solar flares. The results show that our prediction model performs well in both short-term and long-term forecasting.…”
Get full text

Effects of Coverage Area Treatment, Spatial Analysis Unit, and Regression Model on the Results of Station-Level Demand Modeling of Urban Rail Transit by Hongtai Yang, Chaojing Li, Xuan Li, Jinghai Huo, Yi Wen, Emma G. P. Sexton, Yugang Liu

“…Direct ridership models can predict station-level urban rail transit ridership. …”
Get full text

Channel Path Loss Prediction Using Satellite Images: A Deep Learning Approach by Chenlong Wang, Bo Ai, Ruisi He, Mi Yang, Shun Zhou, Long Yu, Yuxin Zhang, Zhicheng Qiu, Zhangdui Zhong, Jianhua Fan

“…This paper proposes a novel deep learning-based path loss prediction model using satellite images. In order to efficiently extract environment features from satellite images, residual structure, attention mechanism, and spatial pyramid pooling layer are developed in the network based on expert knowledge. …”
Get full text

Predicting the distribution and abundance of bustards, storks, and harriers in Kenya using citizen science data by Frank Juma Ong’ondo, Frank Juma Ong’ondo, Rosie Trevelyan, Anthony Kuria, Peter Njoroge, Samuel Guchu, Colin Jackson

“…A linear mixed-effect model was used to predict grassland birds’ response. …”
Get full text

Hybrid machine learning for flood prediction: comparing CHIRPS satellite and ground station data by Agustina Rachmawardani, Budhy Kurniawan, Sastra Kusuma Wijaya, Ardhasena Sopaheluwakan, Marzuki Sinambela

“…While CHIRPS satellite data offers broader spatial coverage, its limitation in precision and higher susceptibility to errors reduce its effectiveness for accurate flood prediction.…”
Get full text

The effect of heterogeneity on invasion in spatial epidemics: from theory to experimental evidence in a model system. by Franco M Neri, Anne Bates, Winnie S Füchtbauer, Francisco J Pérez-Reche, Sergei N Taraskin, Wilfred Otten, Douglas J Bailey, Christopher A Gilligan

Get full text

EpiGeoPop: a tool for developing spatially accurate country-level epidemiological models by Lara Herriott, Henriette L. Capel, Isaac Ellmen, Nathan Schofield, Jiayuan Zhu, Ben Lambert, David Gavaghan, Ioana Bouros, Richard Creswell, Kit Gallagher

“…These models have aided pandemic preparedness by predicting outcomes under hypothetical scenarios and identifying weaknesses in existing frameworks; however, their accuracy, utility, and comparability are being scrutinised. …”
Get full text

Spatial modelling of soil-transmitted helminth infections in Kenya: a disease control planning tool. by Rachel L Pullan, Peter W Gething, Jennifer L Smith, Charles S Mwandawiro, Hugh J W Sturrock, Caroline W Gitonga, Simon I Hay, Simon Brooker

“…The model estimated that a total of 2.8 million school-age children live in districts which warrant mass treatment.…”
Get full text