Prediction of Energetic Electrons in the Inner Radiation Belt and Slot Region With a Double‐Layer LSTM Neural Network Model by Ling Yang, Liuyuan Li, Jinbin Cao

“…Here, we trained a double‐layer long short‐term memory (LSTM) neural network model and successfully predicted the spatial and temporal variations of the 108–749 keV electrons in the inner radiation belt (L ∼ 1.2–2.2) and slot region (L ∼ 2.2–3.2). …”
Get full text

A general methodological framework for predicting and assessing heavy metal pollution in paddy soils using machine learning models by Unurnyam Jugnee, Le Jiao, Sainbayar Dalantai, Lili Huo, Yi An, Bayartungalag Batsaikhan, Undrakhtsetseg Tsogtbaatar, Munguntuul Ulziibaatar, Boldbaatar Natsagdorj

“…Current researches about heavy metal pollution mainly focus on source apportionment, while robust and accurate predictions on its spatial distribution and driving mechanisms is still lacking. …”
Get full text

An equivalent and simplified approach for acoustic noise prediction in a PM synchronous motor based on the semi‐analytical‐FEM model by Armin Saki, Arash Kiyoumarsi, Alireza Ariaei

“…Based on this approach, the simplest and most adequate semi‐analytical‐FEM model for noise prediction in PMSMs is proposed. …”
Get full text

Decoding lake water eutrophication using an innovative dynamic model pool framework in Erhai Lake by Wei Si, Zhixiong Chen, Chi Yung Jim, Ngai Weng Chan, Mou Leong Tan, Bingbing Liu, Dong Liu, Lifei Wei, Shaoyong Wang, Fei Zhang

Get full text

Multi‑omics identification of a novel signature for serous ovarian carcinoma in the context of 3P medicine and based on twelve programmed cell death patterns: a multi-cohort machin... by Lele Ye, Chunhao Long, Binbing Xu, Xuyang Yao, Jiaye Yu, Yunhui Luo, Yuan Xu, Zhuofeng Jiang, Zekai Nian, Yawen Zheng, Yaoyao Cai, Xiangyang Xue, Gangqiang Guo

“…Subsequently, 14 PCD-related genes were included in the PCD-gene-based CDI model. Genomics, single-cell transcriptomes, bulk transcriptomes, spatial transcriptomes, and clinical information from TCGA-OV, GSE26193, GSE63885, and GSE140082 were collected and analyzed to verify the prediction model. …”
Get full text

Life strategies and the long-term climate-driven dynamics of the endemic Caucasian plant Fritillaria latifolia Willd. by R.H. Pshegusov, V.A. Chadaeva, I.V. Taniya, L.M. Abramova, A.N. Mustafina

Get full text

SD-LSTM: A Dynamic Time Series Model for Predicting the Coupling Coordination of Smart Agro-Rural Development in China by Chunlin Xiong, Yilin Zhang, Weijie Wang

Get full text

Temperature Prediction and Fault Warning of High-Speed Shaft of Wind Turbine Gearbox Based on Hybrid Deep Learning Model by Min Zhang, Jijie Wei, Zhenli Sui, Kun Xu, Wenyong Yuan

“…This comprehensive architecture involves five modules: data preprocessing, multi-dimensional spatial feature extraction, temporal dependency modeling, global relationship learning, and hyperparameter optimization. …”
Get full text

High-fidelity surrogate modelling for geometric deviation prediction in laser powder bed fusion using in-process monitoring data by Zhengrui Tao, Mirko Sinico, Bey Vrancken, Wim Dewulf

“…This study targets actual-to-nominal errors within dimensional tolerance, proposing a high-fidelity surrogate model to predict deviations using melt pool monitoring data. …”
Get full text

A quantitative systems pharmacology approach, incorporating a novel liver model, for predicting pharmacokinetic drug-drug interactions. by Mohammed H Cherkaoui-Rbati, Stuart W Paine, Peter Littlewood, Cyril Rauch

“…The overall PBPK model predicted the pharmacokinetics of midazolam and the magnitude of the clinical DDI with perpetrator drug(s) including spatial and temporal enzyme levels changes. …”
Get full text

Analyses of crop yield dynamics and the development of a multimodal neural network prediction model with G×E×M interactions by Saiara Samira Sajid, Zahra Khalilzadeh, Lizhi Wang, Guiping Hu

“…We developed a yield prediction model capable of determining field-level outputs based on comprehensive data inputs, including genotype, spatial, temporal, environmental, and management factors. …”
Get full text

Prediction Model and Knowledge Discovery for Roof Stress in Mined-Out Areas Integrating 3D Scanning Image Features by Yong Yang, Kepeng Hou, Huafen Sun, Linning Guo, Yalei Zhe

“…However, existing study methods often overlook the increasingly available image data and fail to balance the model predictive capability with interpretability. …”
Get full text

Enhancing Emergency Response in Road Accidents: A Severity Prediction Framework Using RF-RFE and Deep Learning Model by Chaimaa Chaoura, Hajar Lazar, Zahi Jarir

“…The attention mechanism further refines predictions by emphasizing critical features. This deep learning model significantly outperforms traditional machine learning methods, achieving accuracy score of 94.99%. …”
Get full text

Remote Sensing and Machine Learning for Groundwater Spring Potential Assessment in Eastern and Northeastern Iran by Javad Momeni Damaneh, Samira Gerami, Mahboobeh Hajibigloo

Get full text

The Predictive Skill of a Remote Sensing-Based Machine Learning Model for Ice Wedge and Visible Ground Ice Identification in Western Arctic Canada by Qianyu Chang, Simon Zwieback, Aaron A. Berg

“…Here, we evaluate the predictive skill of XGBoost models for identifying (1) ice wedge and (2) top-5m visible ground ice in the Tuktoyaktuk Coastlands. …”
Get full text

Impact of sudden public crises on spatial distribution patterns and driving factors of the urban catering industry: a case study of Shanghai’s catering POI data before and after CO... by DanDan Shao, KyungJin Zoh, Yanzhao Xie

“…Through quantitative analysis of restaurant point-of-interest data and influencing factors in Shanghai’s main urban area from 2016 to 2022 using geographic information technology, machine learning, and spatial econometric models, this study predicts spatial changes in the catering industry. …”
Get full text

User Trajectory Prediction in Cellular Networks Using Multi-Step LSTM Approaches: Case Study and Performance Evaluation by Iskandar, Hajiar Yuliana, Hendrawan, Adriel Timoteo, Fabian Rafinanda Benyamin, Naufal Bhanu Anargyarahman

“…While LSTM excels in capturing sequential temporal patterns, Transformer introduces multi-head attention mechanisms to model complex spatial and temporal dependencies, filling a significant research gap in trajectory prediction. …”
Get full text

ARBOALVO: A Bayesian spatiotemporal learning and predictive model for dengue cases in the endemic Northeast city of Natal, Rio Grande do Norte, Brazil. by Mariane Branco Alves, Rafael Santos Erbisti, Aline Araújo Nobre, Taynãna César Simões, Alessandre de Medeiros Tavares, Márcia Cristina Melo, Rodrigo Moreira Pedreira, Jan Pierre Martins de Araújo, Marilia Sá Carvalho, Nildimar Alves Honório

“…These models also enable predictions to support timely interventions for arboviruses like dengue, chikungunya, and Zika.…”
Get full text

Daily soil moisture prediction during winter wheat growth season using an SCSSA-CNN-BiLSTM model by CUI Song, WU Jin, ZHANG Naifeng, LIU Meng, HU Yongsheng, HE Yanan, GU Yue, LONG Xinya, WANG Zhenlong

“…【Conclusion】The SCSSA-CNN- BiLSTM model is accurate for predicting soil moisture in the 0-20 cm root zone of winter wheat. …”
Get full text

Remote Sensing-Derived Environmental Variables to Estimate Transmission Risk and Predict Malaria Cases in Argentina: A Pre-Certification Study (1986–2005) by Ana C. Cuéllar, Roberto D. Coello-Peralta, Davis Calle-Atariguana, Martha Palacios-Macias, Paul L. Duque, Liliana M. Galindo, Mario O. Zaidenberg, María J. Dantur-Juri

“…Early warning systems rely on statistical prediction models, with environmental risks and remote sensing data serving as essential sources of information for their development. …”
Get full text