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Forecasting

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A Machine Learning-Based Water Potability Prediction Model by Using Synthetic Minority Oversampling Technique and Explainable AI.

Computational intelligence and neuroscience
During the last few decades, the quality of water has deteriorated significantly due to pollution and many other issues. As a consequence of this, there is a need for a model that can make accurate projections about water quality. This work shows the...

Application of Combination Forecasting Model in Aircraft Failure Rate Forecasting.

Computational intelligence and neuroscience
Effective prediction of aircraft failure rate has important guiding significance for formulating reasonable maintenance plans, carrying out reliable maintenance activities, improving health management levels, and ensuring the safety of aircraft fligh...

Mitigating urinary incontinence condition using machine learning.

BMC medical informatics and decision making
BACKGROUND: Urinary incontinence (UI) is the inability to completely control the process of releasing urine. UI presents a social, medical, and mental issue with financial consequences.

Artificial Intelligence in Spinal Imaging: Current Status and Future Directions.

International journal of environmental research and public health
Spinal maladies are among the most common causes of pain and disability worldwide. Imaging represents an important diagnostic procedure in spinal care. Imaging investigations can provide information and insights that are not visible through ordinary ...

Application of Neural Network with Autocorrelation in Long-Term Forecasting of Systemic Financial Risk.

Computational intelligence and neuroscience
Carrying out early warning of systemic financial risk is a prerequisite for timely adjustment of monetary policy and macroprudential policy to effectively prevent and resolve systemic financial risks. This paper constructs a systemic financial risk m...

Variational mode decomposition combined fuzzy-Twin support vector machine model with deep learning for solar photovoltaic power forecasting.

PloS one
A novel Variational Mode Decomposition (VMD) combined Fuzzy-Twin Support Vector Machine Model with deep learning mechanism is devised in this research study to forecast the solar Photovoltaic (PV) output power in day ahead basis. The raw data from th...

Research on adaptive combined wind speed prediction for each season based on improved gray relational analysis.

Environmental science and pollution research international
The stability of the power grid and the operational security of the power system depend on the precise prediction of wind speed. In consideration of the nonlinear and non-stationary characteristics of wind speed in different seasons, this paper emplo...

Improved runoff forecasting based on time-varying model averaging method and deep learning.

PloS one
In order to improve the accuracy and stability of runoff prediction. This study proposed a dynamic model averaging method with Time-varying weight (TV-DMA). Using this method, an integrated prediction model framework for runoff prediction was constru...

Water demand in watershed forecasting using a hybrid model based on autoregressive moving average and deep neural networks.

Environmental science and pollution research international
Increasing water demand is exacerbating water shortages in water-scarce regions (such as India, China, and Iran). Effective water demand forecasting is essential for the sustainable management of water supply systems in watersheds. To alleviate the c...

How do I/we forecast tomorrow's transfusion? A focus on recipients' profiles.

Transfusion clinique et biologique : journal de la Societe francaise de transfusion sanguine
Red blood cell (RBC) transfusion is a life-saving medical intervention and has an essential role in the management of surgical patients. However, blood donations and supply levels are decreasing, therefore there is an unmet need for the accurate pred...