Feature fusion ensemble classification approach for epileptic seizure prediction using electroencephalographic bio-signals by Yazeed Alkhrijah, Yazeed Alkhrijah, Shehzad Khalid, Shehzad Khalid, Syed Muhammad Usman, Amina Jameel, Muhammad Zubair, Haya Aldossary, Aamir Anwar, Saad Arif

“…The output of these classifiers is then fed into the model-agnostic meta learner ensemble classifier with LSTM as the base classifier for the final prediction of interictal and preictal states.ResultsThe proposed methodology is trained and tested on the publicly available CHB-MIT dataset while achieving 99.34% sensitivity, 98.67% specificity, and a false positive alarm rate of 0.039.DiscussionThe proposed method not only outperforms the existing methods in terms of sensitivity and specificity but is also computationally efficient, making it suitable for real-time epileptic seizure prediction systems.…”
Get full text

A cloud-based framework for the quantification of the spatially-explicit uncertainty of remotely sensed benthic habitats by Spyridon Christofilakos, Alina Blume, Avi Putri Pertiwi, Chengfa Benjamin Lee, Dimosthenis Traganos, Peter Reinartz

“…The calculation of the spatially-explicit uncertainty is based on the Shannon Entropy equation and the probability values of a successful prediction according to the ML model. …”
Get full text

Landslide assessment considering spatial calibration zoning of physical and mechanical parameters of rock and soil mass by Weimin YIN, Yuanyao LI, Xing LI, Ming LI, Le JU, Ou XIE

“…However, traditional SINMAP models overlook the spatial differences in rock and soil characteristics due to geological environmental changes, resulting in low accuracy in assessment results. …”
Get full text

Application of capsule networks based on reparameterized heterogeneous convolution in multi-scale heterogeneous environment matrix in predictive modeling of interdisciplinary compl... by Shuya Liu, Xiaoli Zhang

“…Abstract Predictive modeling of complex systems frequently encounters inadequate processing capabilities for multi-scale heterogeneous data, as conventional methods grapple with the effective integration of such data. …”
Get full text

Study on the spatial spillover effect of reclaimed water utilization efficiency in water environment-sensitive areas with heterogeneous technology by Wei Jin, Shuhan Gao, Wei Jiang, Huimin Wang

“…This paper uses the three-stage Slack-Based Measure (SBM) model to measure the efficiency of recycled water utilization in 41 cities in the Yangtze River Delta, and based on the characteristics of technological heterogeneity, systematically exploring the spatial correlation mechanism of recycled water utilization. …”
Get full text

Attention Mechanism with Spatial-Temporal Joint Deep Learning Model for the Forecasting of Short-Term Passenger Flow Distribution at the Railway Station by Zhicheng Dai, Dewei Li, Shiqing Feng

“…We conduct a comparative analysis of the prediction performance and time complexity of the proposed architecture against existing baseline models, demonstrating superior performance and robustness exhibited by the ST-Bi-LSTM model (achieving a reduction in RMSE of over 10%). …”
Get full text

Mean limiting pressure factors determination in contiguous pile walls using RAFELA and nonlinear regression models in spatially random soil by Divesh Ranjan Kumar, Sittha Kaorapapong, Warit Wipulanusat, Suraparb Keawsawasvong

Get full text

An EG-Tree Model Incorporating Spatial Heterogeneity for Analyzing Multifactorial Coupling Effects on Carbon Emissions Across Industries and Regions in China by Jinrui Zang, Xin Hu, Kun Qie, Zian Zhang, Shi Zhang

Get full text

Collaborative Superpixelwised PCA for Hyperspectral Image Classification by Chao Yao, Junrui Gu, Zehua Guo, Miao Ma, Qingrui Guo, Gong Cheng

Get full text

Study on the effect of technological innovation on carbon emission intensity in 278 prefecture-level cities in China by Xuelian Zhu, Jianan Che, Xiaogeng Niu, Nannan Cao, Meiyu Liu

“…This study investigates the impact of technological innovation on the carbon intensity of Chinese cities using a spatial Durbin model combined with prefecture-level data. …”
Get full text

Geospatial Modelling of Flood Susceptibility of the Calabar City, Cross River State, Nigeria by Joel Efiong, Eme Efiong, Oluyemi Akintoye, Ebin Inah, Obianuju Awan, Francis Ogban

Get full text

Approaches to Proxy Modeling of Gas Reservoirs by Alexander Perepelkin, Anar Sharifov, Daniil Titov, Zakhar Shandrygolov, Denis Derkach, Shamil Islamov

“…On average, the ST-GNN method reduces computational time by a factor of 4.3 compared to traditional hydrodynamic models, with a median predictive error not exceeding 10% across diverse datasets, despite variability in specific scenarios. …”
Get full text

Modeling regional aboveground carbon stock dynamics affected by land use and land cover changes by A.D. Malik, M.C.W. Arief, S. Withaningsih, P. Parikesit

Get full text

Prevalence, associated risk factors and satellite imagery analysis in predicting soil-transmitted helminth infection in Nakhon Si Thammarat Province, Thailand by Jarawadee Muenjak, Jutarat Thongrod, Chanakan Choodamdee, Pongphan Pongpanitanont, Manachai Yingklang, Tongjit Thanchomnang, Sakhone Laymanivong, Penchom Janwan

“…We developed an innovative predictive model by integrating convolutional neural networks (CNNs) for land-use classification of satellite imagery with artificial neural networks (ANNs) following dimensionality reduction through principal component analysis (PCA). …”
Get full text

Prediction of Spatiotemporal Distribution of Electric Vehicle Charging Load Based on Multi-Source Information by WANG Qiang, BI Yuhao, GAO Chao, SONG Duoyang

“…The proposed charging demand gravity model optimizes users' charging station selection behavior by integrating factors such as charging station size， electricity price， and user time cost， resulting in a more reasonable spatial and temporal distribution of the charging load[Conclusions] This study constructed a spatial and temporal distribution prediction model for electric vehicle charging loads by integrating information from multiple sources. …”
Get full text

Assessing spatial soil erosion under climate change using SWAT model in a semi-arid watershed of northeastern Tunisia by Fathia Jarray, Taoufik Hermassi, Haykel Sellami, Mohamed Ali Ben Abdallah, Mohamed Mechergui

Get full text

Modelling of spatially correlated weather-based electricity forecasting using combined frequency-based signal decomposition with optimized boosting approach by Indra A. Aditya, Didit Adytia

“…The primary contribution is a spatially correlation-driven feature selection technique to choose ideal weather input sites, coupled with the extraction of predominant frequency components from the load signal to enhance model input. …”
Get full text

Nonlocal fractional MGT-non-Fourier photothermal model with spatial and temporal nonlocality for controlling the behavior of semiconductor materials with spherical cavities by Mofareh Alhazmi, Ahmed E. Abouelregal

“…In this work, we present the nonlocal Moore-Gibson-Thompson photothermal (NMGTPT) theory, a novel framework that integrates spatial and temporal nonlocality to address limitations in both traditional and advanced thermoelastic models. …”
Get full text

Modelling the Spatial Distribution of <i>Dosidicus gigas</i> in the Southeast Pacific Ocean at Multiple Temporal Scales Based on Deep Learning by Mingyang Xie, Bin Liu, Xinjun Chen, Wei Yu, Jintao Wang, Jiawen Xu

“…With the advent of the big data era in ocean remote sensing and fisheries, there is a growing demand for finer temporal scales to predict spatial distribution of the jumbo flying squid (<i>Dosidicus gigas</i>). …”
Get full text

High-spatial-resolution surface soil moisture retrieval using the Deep Forest model in the cloud environment over the Tibetan Plateau by Zhenghao Li, Qiangqiang Yuan, Xin Su

“…As a key climate variable, soil moisture plays a crucial role in drought detection, flood warning, and crop yield prediction. In recent years, the demand for high-spatial-resolution soil moisture has increased, particularly in environmental management. …”
Get full text