AI Medical Compendium Topic:
Forecasting

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A novel approach on water resource management with Multi-Criteria Optimization and Intelligent Water Demand Forecasting in Saudi Arabia.

Environmental research
Ever-increasing demands for freshwater resources have elevated the likelihood of severe water stress in several places of Saudi Arabia during the last several decades. With effective decision-making processes, development objectives on water resource...

Vehicle Destination Prediction Using Bidirectional LSTM with Attention Mechanism.

Sensors (Basel, Switzerland)
Satellite navigation has become ubiquitous to plan and track travelling. Having access to a vehicle's position enables the prediction of its destination. This opens the possibility to various benefits, such as early warnings of potential hazards, rou...

Explainable artificial intelligence (XAI) for exploring spatial variability of lung and bronchus cancer (LBC) mortality rates in the contiguous USA.

Scientific reports
Machine learning (ML) has demonstrated promise in predicting mortality; however, understanding spatial variation in risk factor contributions to mortality rate requires explainability. We applied explainable artificial intelligence (XAI) on a stack-e...

The Application of Machine Learning ICA-VMD in an Intelligent Diagnosis System in a Low SNR Environment.

Sensors (Basel, Switzerland)
This paper proposes a new method called independent component analysis-variational mode decomposition (ICA-VMD), which combines ICA and VMD. The purpose is to study the application of ICA-VMD in low signal-to-noise ratio (SNR) signal processing and d...

Runoff forecasting model based on variational mode decomposition and artificial neural networks.

Mathematical biosciences and engineering : MBE
Accurate runoff forecasting plays a vital role in water resource management. Therefore, various forecasting models have been proposed in the literature. Among them, the decomposition-based models have proved their superiority in runoff series forecas...

Transfer learning for spatio-temporal transferability of real-time crash prediction models.

Accident; analysis and prevention
Real-time crash prediction is a heavily studied area given their potential applications in proactive traffic safety management in which a plethora of statistical and machine learning (ML) models have been developed to predict traffic crashes in real-...

CNN-GRU-AM for Shared Bicycles Demand Forecasting.

Computational intelligence and neuroscience
The demand forecast of shared bicycles directly determines the utilization rate of vehicles and projects operation benefits. Accurate prediction based on the existing operating data can reduce unnecessary delivery. Since the use of shared bicycles is...

Energy Consumption Forecasting for Smart Meters Using Extreme Learning Machine Ensemble.

Sensors (Basel, Switzerland)
The employment of smart meters for energy consumption monitoring is essential for planning and management of power generation systems. In this context, forecasting energy consumption is a valuable asset for decision making, since it can improve the p...

Forecasting of Patient-Specific Kidney Transplant Function With a Sequence-to-Sequence Deep Learning Model.

JAMA network open
IMPORTANCE: Like other clinical biomarkers, trajectories of estimated glomerular filtration rate (eGFR) after kidney transplant are characterized by intra-individual variability. These fluctuations hamper the distinction between alarming graft functi...

Probabilistic Deep Learning to Quantify Uncertainty in Air Quality Forecasting.

Sensors (Basel, Switzerland)
Data-driven forecasts of air quality have recently achieved more accurate short-term predictions. However, despite their success, most of the current data-driven solutions lack proper quantifications of model uncertainty that communicate how much to ...