A Hybrid Long Short-Term Memory-Graph Convolutional Network Model for Enhanced Stock Return Prediction: Integrating Temporal and Spatial Dependencies by Songze Shi, Fan Li, Wei Li

“…This study proposes a hybrid model integrating long short-term memory (LSTM) networks and graph convolutional networks (GCNs) to enhance accuracy by capturing both temporal dynamics and spatial inter-stock relationships. …”
Get full text

An Approach to Predicting Urban Carbon Stock Using a Self-Attention Convolutional Long Short-Term Memory Network Model: A Case Study in Wuhan Urban Circle by Zhi Zhou, Xueling Wu, Bo Peng

Subjects: Get full text

Spatial-Temporal Coordination of Agricultural Quality and Water Carrying Capacity in Chengdu-Chongqing by Bingchang Li, Xinlan Liang, Cuihua Bian, Fengxin Sun, Zichen Xia, Binghao Sun, Ying Cao

“…Employing the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) model, obstacle degree analysis, standard deviational ellipse, and grey prediction modeling, the study finds that AQI exhibits a sustained upward trend—doubling in over half of the region’s cities—while WCI shows fluctuating growth, constrained by climatic extremes and uneven water distribution. …”
Get full text

Event Prediction Using Spatial–Temporal Data for a Predictive Traffic Accident Approach Through Categorical Logic by Eleftheria Koutsaki, George Vardakis, Nikos Papadakis

“…Finally, we implement the traffic accident prediction model using the Prolog language with the corresponding Queries in JPL.…”
Get full text

Spatial multi-omics analysis of tumor-stroma boundary cell features for predicting breast cancer progression and therapy response by Yuanyuan Wu, Youyang Shi, Zhanyang Luo, Xiqiu Zhou, Yonghao Chen, Xiaoyun Song, Sheng Liu

Get full text

Modelling the Spatial Dependence of Multi‐Species Point Patterns by Chathuri L. Samarasekara, Ian Flint, Yan Wang

“…ABSTRACT The study of the spatial point patterns in ecology, such as the records of the observed locations of trees, shrubs, nests, burrows, or documented animal presence, relies on multivariate point process models. …”
Get full text

Characterizing, predicting, and mapping of soil spatial variability in Gharb El-Mawhoub area of Dakhla Oasis using geostatistics and GIS approaches by Salman Selmy, Salah Abd El-Aziz, Ahmed El-Desoky, Moatez El-Sayed

“…The current study was undertaken in the Gharb El-Mawhoub area of Dakhla Oasis to determine, predict, map, and assess the spatial variation of physicochemical attributes. …”
Get full text

Comparative analysis of Sentinel-2 and PlanetScope imagery for chlorophyll-a prediction using machine learning models by Eden T. Wasehun, Leila Hashemi Beni, Courtney A. Di Vittorio, Christopher M. Zarzar, Kyana R.L. Young

“…On the other hand, the SVR model demonstrated better predictive performance for Chl-a concentration retrieval using PlanetScope (PS) data (R2 = 0.71, RMSE = 8.15 μg/l, bias = 0.46). …”
Get full text

Assessment and Prediction of Carbon Storage Based on Land Use/Land Cover Dynamics in the Gonghe Basin by Hong Jia, Siqi Yang, Lianyou Liu, Hang Li, Zeshi Li, Yixin Chen, Jifu Liu

“…Based on the land use data of the Gonghe Basin from 1990 to 2020, the InVEST model was applied to analyze the spatiotemporal changes in carbon storage, and the PLUS model was used to predict the changes in carbon storage under three different development scenarios in 2030. …”
Get full text

Integrating Machine Learning Techniques for Enhanced Safety and Crime Analysis in Maryland by Zeinab Bandpey, Soroush Piri, Mehdi Shokouhian

Subjects: Get full text

Vers une nouvelle classification des modèles d'évaluation et de prédiction de l'érosion hydrique by Aïcha Fadil, Farid El Wahidi

“…However, these models contrast considerably regarding to the studied phenomena, their nature and their complexity in the field, and to the implemented approach, through the variety and the quality of used data, the spatial and temporal scales of application and the information obtained as output, types and uncertainties.An attempt to classify water erosion assessment models (129 models are considered) is presented based on their most critical geospatial attributes for water erosion modeling. …”
Get full text

Spatial-temporal evolution characteristics and driving factors of carbon emission prediction in China-research on ARIMA-BP neural network algorithm by Sanglin Zhao, Zhetong Li, Hao Deng, Xing You, Jiaang Tong, Bingkun Yuan, Zihao Zeng

“…Based on the energy consumption data of 30 provinces in China from 2000 to 2021, this paper calculates and predicts the total carbon emissions of 30 provinces in China from 2000 to 2035 based on ARIMA model and BP neural network model, and uses ArcGIS and standard elliptic difference to visually analyze the spatial and temporal evolution characteristics, and further uses LMDI model to decompose the driving factors affecting carbon emissions. …”
Get full text

Pedestrian Trajectory Prediction via Window Attention and Spatial Graph Interaction Network by Xiang Gu, Chao Li, Jie Yang, Jing Wang, Qiwei Huang

“…However, the task still faces challenges in modeling long-term dependencies, complex spatial interactions, and multi-scale feature fusion. …”
Get full text

Urban Fire Spatial–Temporal Prediction Based on Multi-Source Data Fusion by Haiyu Xiang, Lizhi Wu, Zidong Guo, Shaoyun Ren

“…Temporal variables, such as past fire incidents and external influences like meteorological conditions, significantly impact fire risk, while spatial attributes, including regional characteristics and cross-regional interactions, further complicate predictive modeling. …”
Get full text

Spatial epidemiology of Tabanus (Diptera: Tabanidae) vectors of Trypanosoma by Roberta Marques, Daniel Jiménez-García, Luis E. Escobar, Tiago Kütter Krolow, Rodrigo Ferreira Krüger

Get full text

A novel surrogate model with deep learning for predicting spacial-temporal pressure in coalbed methane reservoirs by Yukun Dong, Xiaodong Zhang, Jiyuan Zhang, Kuankuan Wu, Shuaiwei Liu

Subjects: Get full text

Buzzing towards Resilience: Investigating the Spatial Alignment of the Desert Pallid Bee, <i>Centris pallida</i>, and Its Host Plants in Response to Climate Change by Terese Maxine P. Cruz, Stephen L. Buchmann, Kathleen L. Prudic

Get full text

Spatial interpolation of health and demographic variables: Predicting malaria indicators with and without covariates. by Camille Morlighem, Chibuzor Christopher Nnanatu, Corentin Visée, Atoumane Fall, Catherine Linard

“…Overall, socioeconomic indicators were generally better predicted by covariate-based models (e.g., random forest and Bayesian models), while methods using spatial autocorrelation alone (e.g., thin plate splines) performed better for variables with heterogeneous spatial structure, such as ethnicity and malaria prevention indicators. …”
Get full text

Graphormer Boosted: Molecular Property Prediction With Enhanced Graph Spatial and Edge Encodings by Sarah A. Fadlallah, Francesc Serratosa, Carme Julia

Get full text

MDA-MIM: a radar echo map prediction model integrating multi-scale feature fusion and dual attention mechanism by HU Qiang, GAO Yating, YIN Binli, QU Lianen

“…To better capture the non-stationary characteristics of radar echo data, a self-attention mechanism was introduced into the non-stationary module of the MIM model, dynamically adjusting the weights of different time steps and spatial positions. …”
Get full text