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

Predicting Wheat Potential Yield in China Based on Eco-Evolutionary Optimality Principles by Shen Tan, Shengchao Qiao, Han Wang, Sheng Chang

“…However, most existing crop models for wheat PY rely on type-specific parameters that describe wheat traits, which often require calibration and, in turn, reduce prediction confidence when applied across different spatial or temporal scales. …”
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

Data Fusion and Dimensionality Reduction for Pest Management in Pitahaya Cultivation by Wilson Chango, Mónica Mazón-Fierro, Juan Erazo, Guido Mazón-Fierro, Santiago Logroño, Pedro Peñafiel, Jaime Sayago

“…First, early fusion better captures cross-domain interactions before dimensionality reduction, improving prediction robustness. Second, KPCA-poly offers an effective non-linear mapping suitable for tropical agroecosystem complexity. …”
Get full text

Constraint-incorporated deep learning model for predicting heat transfer in porous media under diverse external heat fluxes by Ziling Guo, Hui Wang, Huangyi Zhu, Zhiguo Qu

“…The temperature field within porous media is considerably affected by different boundary conditions, and effective thermal conductivity varies with spatial structure morphologies. At present, traditional prediction methods for the temperature field are expensive and time consuming, particularly for large structures and dimensions, whereas deep learning surrogate models have limitations related to constant boundary conditions and two-dimensional input slices, lacking the three-dimensional topology and spatial correlations. …”
Get full text

Spatiotemporal Characteristics, Causes, and Prediction of Wildfires in North China: A Study Using Satellite, Reanalysis, and Climate Model Datasets by Mengxin Bai, Peng Zhang, Pei Xing, Wupeng Du, Zhixin Hao, Hui Zhang, Yifan Shi, Lulu Liu

“…Finally, we developed a prediction model for burned areas, leveraging the strong correlation between the FFMC and burned areas. …”
Get full text

Near real-time LOD prediction using ConvLSTM model through integrating IGS rapid LOD and effective angular momentum by Kehao Yu, Xiaoya Wang, Zhao Li, Jian Wang, Lihua Li, Weiping Jiang, Kai Yang, Jingwen Long, Yunzhao Li

Get full text

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

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

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

Enhancing landslide-scale rainfall threshold predictive modeling for rainfall-induced red-bed soft rock landslide occurrence using a stock-taking approach by Qi Li, Zidan Liu, Ziyu Tao

“…Using a Bayesian modeling framework for predicting the probability occurrence of landslides triggered by a rainfall event above the defined rainfall threshold, we found that high intensity rainfall events play a more important role in triggering R-SRLs than their long duration.…”
Get full text