85   Artículos

 
en línea
Yoga Sasmita, Heri Kuswanto and Dedy Dwi Prastyo    
Standard time-series modeling requires the stability of model parameters over time. The instability of model parameters is often caused by structural breaks, leading to the formation of nonlinear models. A state-dependent model (SDM) is a more general an... ver más
Revista: Forecasting    Formato: Electrónico

 
en línea
Yan Chen and Chunchun Hu    
Accurate prediction of fine particulate matter (PM2.5) concentration is crucial for improving environmental conditions and effectively controlling air pollution. However, some existing studies could ignore the nonlinearity and spatial correlation of time... ver más
Revista: ISPRS International Journal of Geo-Information    Formato: Electrónico

 
en línea
Xianchang Wang, Siyu Dong and Rui Zhang    
In the prediction of time series, Empirical Mode Decomposition (EMD) generates subsequences and separates short-term tendencies from long-term ones. However, a single prediction model, including attention mechanism, has varying effects on each subsequenc... ver más
Revista: Information    Formato: Electrónico

 
en línea
Jacques Hermes, Marcus Rosenblatt, Christian Tönsing and Jens Timmer    
Describing viral outbreaks, such as the COVID-19 pandemic, often involves employing compartmental models composed of ordinary differential equation (ODE) systems. Estimating the parameter values for these ODE models is crucial and relies on accessible da... ver más
Revista: Algorithms    Formato: Electrónico

 
en línea
Tomasz Stepinski and Anna Dmowska    
To better understand the persistence of residential racial segregation in U.S. cities, it is essential to develop testable, spatially explicit models of racial dynamics. However, the original census data are not formatted in a way that facilitates the te... ver más
Revista: ISPRS International Journal of Geo-Information    Formato: Electrónico

 
en línea
Yannik Hahn, Tristan Langer, Richard Meyes and Tobias Meisen    
Deep learning models have revolutionized research fields like computer vision and natural language processing by outperforming traditional models in multiple tasks. However, the field of time series analysis, especially time series forecasting, has not s... ver más
Revista: Forecasting    Formato: Electrónico

 
en línea
Henri Pörhö, Jani Tomperi, Aki Sorsa, Esko Juuso, Jari Ruuska and Mika Ruusunen    
The aim of wastewater treatment plants (WWTPs) is to clean wastewater before it is discharged into the environment. Real-time monitoring and control will become more essential as the regulations for effluent discharges are likely to become stricter in th... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Zhongyan Liu, Jiangtao Mei, Deguo Wang, Yanbao Guo and Lei Wu    
As a new type of riser connecting offshore platforms and submarine pipelines, steel catenary risers (SCRs) are generally subject to waves and currents for a long time, thus it is significant to fully evaluate the SCR structure?s safety. Aiming at the dam... ver más
Revista: Journal of Marine Science and Engineering    Formato: Electrónico

 
en línea
Saad Sh. Sammen, Mohammad Ehteram, Zohreh Sheikh Khozani and Lariyah Mohd Sidek    
Predicting reservoir water levels helps manage droughts and floods. Predicting reservoir water level is complex because it depends on factors such as climate parameters and human intervention. Therefore, predicting water level needs robust models. Our st... ver más
Revista: Water    Formato: Electrónico

 
en línea
Hatef Dastour and Quazi K. Hassan    
Having a complete hydrological time series is crucial for water-resources management and modeling. However, this can pose a challenge in data-scarce environments where data gaps are widespread. In such situations, recurring data gaps can lead to unfavora... ver más
Revista: Hydrology    Formato: Electrónico

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