SHAP-enhanced interpretive MGTWR-CNN-BILSTM-AM framework for predicting surface subsidence: a case study of Shanghai municipality by Long Wen-Jiang, Yu Xue-Xiang, Zhu Ming-Fei, Xue Li, Zhang Guang-Hui, Wang Lin-Lin

Get full text

Development of Laser Underwater Transmission Model from Maximum Water Depth Perspective by Guoqing Zhou, Kun Li, Jian Gao, Junyun Ma, Ertao Gao, Yanling Lu, Jiasheng Xu, Xiao Zhou

Get full text

Generalizable Storm Surge Risk Modeling by Mahlon Scott, Hsin-Hsiung Huang

“…Inspired by principles of robust statistical modeling, this paper introduces a Bayesian hierarchical model integrated with Gaussian processes to account for spatial random effects. …”
Get full text

Optimizing the Portuguese wildfire fuel reduction program by Alan Ager, Bruno A. Aparício, José M.C. Pereira

“…In this study, we employed a scenario planning model to optimize the implementation of a national fuel management plan in Portugal and to understand tradeoffs among specific risk reduction objectives. …”
Get full text

The impact of spatiotemporal variability of environmental conditions on wheat yield forecasting using remote sensing data and machine learning by Keltoum Khechba, Mariana Belgiu, Ahmed Laamrani, Alfred Stein, Abdelhakim Amazirh, Abdelghani Chehbouni

“…This study aims to assess the impact of spatial and temporal heterogeneity of environmental conditions on wheat yield forecasting using machine learning models. …”
Get full text

A novel telomere-associated genes signature for the prediction of prognosis and treatment responsiveness of hepatocellular carcinoma by Kuo Kang, Hui Nie, Weilu Kuang, Xuanxuan Li, Yangying Zhou

“…Conclusion In this study, we developed a novel prognostic model comprising 18 TRGs for HCC, which exhibited remarkable accuracy in predicting HCC patients’ prognosis. …”
Get full text

Prediction of spatiotemporal evolution and zoning of ecological sensitivity in the upper reaches of Minjiang river, sichuan, China by Lingfan Ju, Yan Liu, Shunduo Liu, Qing Xiang, Wenkai Hu, Peng Yu

“…In this study, an ecological sensitivity index system is established to quantitatively analyze the interrelationships of ecological factors. The CA-MC model and center of gravity migration are used to investigate the spatial and temporal evolution of ecological sensitivity in the upper Minjiang River basin from 2000 to 2020 and to predict the ecological sensitivity in 2040. …”
Get full text

Short-term displacement prediction for newly established monitoring slopes based on transfer learning by Yuan Tian, Yang-landuo Deng, Ming-zhi Zhang, Xiao Pang, Rui-ping Ma, Jian-xue Zhang

Get full text

Spatial Association Network of Land-Use Carbon Emissions in Hubei Province: Network Characteristics, Carbon Balance Zoning, and Influencing Factors by Yong Huang, Zhong Wang, Heng Zhao, Di You, Wei Wang, Yanran Peng

“…This study constructs a LUCE spatial association network for Hubei Province using a modified gravity model to uncover the spatial linkages in carbon emissions. …”
Get full text

Suitable habitat prediction and desertified landscape remediation potential of three medicinal Glycyrrhiza species in China by Fanyan Ma, Xiang Huang, Zhenan Yang, Panxin Niu, Keyao Pang, Mei Wang, Guangming Chu

“…This study employed the MaxEnt model to predict the potential habitats of these three species in China under climate change, and examined the relationship between their distribution and desert ecosystems. …”
Get full text

From Domain Decomposition to Model Reduction for Large Nonlinear Structures by Leturcq, Bertrand, Le Tallec, Patrick

“…The numerical simulation of multiscale and multiphysics problems requires efficient tools for spatial localization and model reduction. A general strategy combining Domain Decomposition and Nonuniform Transformation Field Analysis (NTFA) is proposed herein for the simulation of nuclear fuel assemblies at the scale of a full nuclear reactor. …”
Get full text

Prediction of the Morphological Characteristics of Asymmetric Thaw Plate of Qinghai–Tibet Highway Using Remote Sensing and Large-Scale Geological Survey Data by Jianbin Hao, Zhenyang Zhao, Jianbing Chen, Zhiyun Liu, Fuqing Cui, Xiaona Liu, Wenting Lu, Jine Liu

“…Through integrating remote sensing data and large-scale geological survey results with an earth–atmosphere coupled numerical model and a random forest (RF) prediction framework, we assessed the spatial distribution of thaw asymmetry along the permafrost section of the QTH. …”
Get full text

Real-time prediction of port water levels based on EMD-PSO-RBFNN by Lijun Wang, Shenghao Liao, Sisi Wang, Jianchuan Yin, Ronghui Li, Jingyu Guan

“…Subsequently, PSO was applied to fine-tune the center and spread parameters of the RBFNN, thereby enhancing the model’s predictive performance. The optimized PSO-RBFNN model was employed to make predictions on the decomposed sub-series. …”
Get full text

Predicting the current potential and future world wide distribution of the onion maggot, Delia antiqua using maximum entropy ecological niche modeling. by Shuoying Ning, Jiufeng Wei, Jinian Feng

“…Onion maggot, Delia antiqua, larvae are subterranean pests with limited mobility, that directly feed on bulbs of Allium sp. and render them completely unmarketable. Modeling the spatial distribution of such a widespread and damaging pest is crucial not only to identify current potentially suitable climactic areas but also to predict where the pest is likely to spread in the future so that appropriate monitoring and management programs can be developed. …”
Get full text

IoT-Based Traffic Prediction for Smart Cities by Zhinong Miao, Qilong Liao

“…The primary objective was to develop a predictive model that improves traffic forecasting accuracy, reduces congestion, and optimizes real-time traffic management. …”
Get full text

Digital Mapping of Soil Equivalent Calcium Carbonate Using Landsat 8 Satellite Images and Environmental Data by Machine Learning Models in Badr Watershed, Kurdistan Province by M. Zarinibahador

“…The present study aimed to digitally map calcium carbonate equivalent using auxiliary environmental variables, Landsat 8 satellite images, and predictive models and to present the best models in the Badr watershed in the south of Qorveh district. …”
Get full text

A cluster-based local modeling paradigm for high spatiotemporal resolution VPD prediction using multi-source data and machine learning by Mi Wang, Zhuowei Hu, Xiangping Liu, Wenxing Hou

“…The results show that the local modeling significantly enhances prediction accuracy, with the XGBoost model outperforming others across all clusters and maintaining high precision across seasons scales and different land use types. …”
Get full text

Modeling robustness tradeoffs in yeast cell polarization induced by spatial gradients. by Ching-Shan Chou, Qing Nie, Tau-Mu Yi

“…In this work, we investigated the tradeoffs among these performance objectives using a generic model that captures the basic spatial dynamics of polarization in yeast cells, which are small. …”
Get full text

ELM2.1-XGBfire1.0: improving wildfire prediction by integrating a machine learning fire model in a land surface model by Y. Liu, H. Huang, S.-C. Wang, T. Zhang, D. Xu, Y. Chen

“…A Fortran–C–Python deep learning bridge is adapted to support online communication between ELM and the ML fire model. Specifically, the burned area predicted by the ML-based wildfire model is directly passed to ELM to adjust the carbon pool and vegetation dynamics after disturbance, which are then used as predictors in the ML-based fire model in the next time step. …”
Get full text

Unifying spatiotemporal and frequential attention for traffic prediction by Qi Guo, Qi Tan, Jun Tang, Benyun Shi

“…By leveraging deep learning to capture spatial correlations in traffic flow and applying spectral analysis to fuse time series data with underlying periodic correlations in both the time and frequency domains, we develop an innovative traffic prediction model called the Space-Time-Frequency Attention Network (STFAN). …”
Get full text