Spatial clustering analysis combined with ensemble modeling identified potential coastal conservation hotspots of White-eyed gulls in the Red Sea by Mohanad Abdelgadir, Monif AlRashidi, Randa Alharbi, Abdulaziz S. Alatawi

“…In this study, we used a spatial clustering analysis combined with an ensemble modeling approach to predict the coastal distribution and identify potential hotspots for the White-eyed gull. …”
Get full text

Application of fluid dynamics in modeling the spatial spread of infectious diseases with low mortality rate: A study using MUSCL scheme by Nnaji Daniel Ugochukwu, Kiogora Phineas Roy, Onah Ifeanyi Sunday, Mung’atu Joseph, Aguegboh Nnaemeka Stanley

“…This study presents a comprehensive mathematical framework that applies fluid dynamics to model the spatial spread of infectious diseases with low mortality rates. …”
Get full text

Identifying climate and environmental determinants of spatial disparities in wheat production using a geospatial machine learning model by Kai Ren, Yongze Song, Linchao Li, Francesco Mancini, Zhuoyao Xiao, Xueyuan Zhang, Rui Qu, Qiang Yu

“…Next, the geographically optimal zones-based heterogeneity (GOZH) model, an integration of spatial stratified heterogeneity and decision tree learning models, is used to identify determinants and their interactions on spatial disparities of wheat production. …”
Get full text

Monthly Arctic Sea‐Ice Prediction With a Linear Inverse Model by M. Kathleen Brennan, Gregory J. Hakim, Edward Blanchard‐Wrigglesworth

“…Abstract We evaluate Linear Inverse Models (LIMs) trained on last millennium model data to predict Arctic sea‐ice concentration, thickness, and other atmospheric and oceanic variables on monthly timescales. …”
Get full text

Hybrid approaches enhance hydrological model usability for local streamflow prediction by Yiheng Du, Ilias G. Pechlivanidis

“…Abstract Hydrological models are essential for predicting water flux dynamics, including extremes, and managing water resources, yet traditional process-based large-scale models often struggle with accuracy and process understanding due to their inability to represent complex, non-linear hydrometeorological processes, limiting their effectiveness in local conditions. …”
Get full text

RUL prediction method based on cross-view hybrid network model by Ai Yandi, Fang Dong, Tian Zhiping, Yan Kaiyang

“…To this end, this paper designs a RUL prediction framework based on a cross-view hybrid network model (CVHNet). …”
Get full text

Application of Machine Learning Models to Multi-Parameter Maximum Magnitude Prediction by Jingye Zhang, Ke Sun, Xiaoming Han, Ning Mao

“…Magnitude prediction is a key focus in earthquake science research, and using machine learning models to analyze seismic data, identify pre-seismic anomalies, and improve prediction accuracy is of great scientific and practical significance. …”
Get full text

Deciphering the Mechanism of Better Predictions of Regional LSTM Models in Ungauged Basins by Qiang Yu, Liguang Jiang, Raphael Schneider, Yi Zheng, Junguo Liu

“…The long short‐term memory (LSTM) model has gained popularity in rainfall‐runoff prediction in recent years and has proven applicable in PUB. …”
Get full text

An improved machine-learning model for lightning-ignited wildfire prediction in Texas by Qi Zhang, Cong Gao, Chunming Shi

“…Using this dataset, we developed an eXtreme gradient boosting-based machine learning model that integrates meteorological, soil, vegetative, lightning, topographic, and human activity variables to predict LIW probability. …”
Get full text

A Meteorology Based Particulate Matter Prediction Model for Megacity Dhaka by Sadia Afrin, Mohammad Maksimul Islam, Tanvir Ahmed

“…Models also exhibit strong predictive power in forecasting PM levels of two other CAMSs in Dhaka. …”
Get full text

External validation of risk prediction models for post-stroke mortality in Berlin by Jessica L Rohmann, Tobias Kurth, Heinrich J Audebert, Marco Piccininni, Lukas Reitzle

“…We aimed to assess the performance of two prediction models for post-stroke mortality in Berlin, Germany.Design We used data from the Berlin-SPecific Acute Treatment in Ischaemic or hAemorrhagic stroke with Long-term follow-up (B-SPATIAL) registry.Setting Multicentre stroke registry in Berlin, Germany.Participants Adult patients admitted within 6 hours after symptom onset and with a 10th revision of the International Classification of Diseases discharge diagnosis of ischaemic stroke, haemorrhagic stroke or transient ischaemic attack at one of 15 hospitals with stroke units between 1 January 2016 and 31 January 2021.Primary outcome measures We evaluated calibration (calibration-in-the-large, intercept, slope and plot) and discrimination performance (c-statistic) of Bray et al’s 30-day mortality and Smith et al’s in-hospital mortality prediction models. …”
Get full text

A lightweight hybrid model for accurate ammonia prediction in pig houses by Jacqueline Musabimana, Qiuju Xie, Hong Zhou, Ping Zheng, Honggui Liu, Tiemin Ma, Jiming Liu

“…The model improves accuracy compared to other state-of-the-art and ability for NH3 prediction.…”
Get full text

Monitoring and forecasting of land use/land cover (LULC) in Al-Hassa Oasis, Saudi Arabia based on the integration of the Cellular Automata (CA) and the Cellular Automata-Markov Mod... by Ashraf Abdelkarim

“…This study sought to integrate the Cellular Automata-Markov Model (CA-Markov) and the Cellular Automata (CA) using sensing data for land cover maps for the years: 1988, 2000, 2013 and 2020 to monitor, detect, and predict the spatial and temporal of Land Use/Land Cover (LULC) change in Al-Hassa Oasis, Saudi Arabia. …”
Get full text

A novel cancer-associated membrane signature predicts prognosis and therapeutic response for lung adenocarcinoma by Biao Tu, Jun Wu, Wei Zhang, Haitao Tang, Tenghui Dai, Bingfeng Xie

“…A distinct LUAD-enriched epithelial cluster (Epi_c0) exhibiting hypoxic and EMT signatures was identified. 35 cancer-specific membrane proteins were defined, several of which, including TSPAN8, BACE2, and COX16, showed strong spatial localization within the tumor regions. LCaMPS, a 9-membrane gene-based prognostic model, stratified patient prognosis and predicted 5- and 10-year survival rates with high accuracy. …”
Get full text

Movement Patterns and Habitat Suitability of Translocated Sumatran Tigers (Panthera tigris sumatrae) by Farhan Reza Pahlevi, Lilik Budi Prasetyo, Dolly Priatna

Get full text

Tuberculosis disease burden in China: a spatio-temporal clustering and prediction study by Jingzhe Guo, Ce Liu, Fang Liu, Erkai Zhou, Runxue Ma, Ling Zhang, Bin Luo

Get full text

Multivariate Segment Expandable Encoder-Decoder Model for Time Series Forecasting by Yanhong Li, David C. Anastasiu

“…Additionally, MSEED incorporates a simple vanilla encoder-decoder model for strengthening rolling predictions. The framework has been tested on four challenging real-world datasets, focusing on two critical forecasting scenarios: long-term predictions (three days ahead) and rolling predictions (every four hours) to simulate real-time decision-making in water resource management. …”
Get full text

Modeling inter-city population flows: a Deep Radiation model with multisource geographic features by Jingjing Liu, Lei Xu, Le Ma, Chao Wang, Nengcheng Chen

Get full text

Evaluation of CMIP Earth System Models on Root Biomass Simulation by Ke ZHOU, Youqi SU, Yu ZHANG, Minhong SONG, Tongwen WU, Linfeng YANG, Xizhao WANG, Tianya LI

“…Roots play an important role in the carbon cycle of ecosystems.The Earth System Models （ESMs） of the Coupled Model Intercomparison Project （CMIP） have been widely used to simulate and predict root biomass.In this paper， the spatial distribution， dynamic change， and comparison with observed values of root biomass of 14 ESMs simulated historical experiments were analyzed.The results showed that： （1） The global distribution of multi-year average from 1850 to 2005 of root biomass indicated that 7 ESMs had maximum or minimum values， while the rest ESMs showed that root biomass was higher in the middle and high latitudes of the equator and the northern hemisphere.The root biomass distribution at different latitudes showed that 40°S is also one of the high value areas； （2） The simulation results from 1995 to 2005 are compared with the site observation data （1990 -2010） in different climatic zones by using SS index， the result showed deviations are relatively large but the simulation effect of temperate zone is slightly better than frigid zone and tropical zone.On the global scale， BCC-CSM2-MR is the best simulated ESM； （3） In the Qinghai-Xizang Plateau， ESMs can reasonably simulate the seasonal variation over the years 1850 to 2005 of root biomass， but the relationship between interannual variation of the simulated root biomass and the meteorological factors （temperature， precipitation） by different ESMs is different.In order to conduct more precise and in-depth research and analysis， in addition to improving the model， it is also necessary to improve the collection of observational data.…”
Get full text

Spatial and Temporal Changes in Nutrient Source Contribution in a Lowland Catchment Within the Baltic Sea Region Under Climate Change Scenarios by Damian Bojanowski, Paulina Orlińska‐Woźniak, Paweł Wilk, Ewa Jakusik, Ewa Szalińska

“…To track spatial and seasonal changes of total nitrogen and phosphorus for the Wełna River (central Poland), we used climate change data and the SWAT model. …”
Get full text