AIMC Topic: Forecasting

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T-RippleGNN: Predicting traffic flow through ripple propagation with attentive graph neural networks.

PloS one
Recently, accurate traffic flow prediction has become a significant part of intelligent transportation systems, which can not only satisfy citizens' travel need and life satisfaction, but also benefit urban traffic management and control. However, tr...

Forecasting monthly runoff in a glacierized catchment: A comparison of extreme gradient boosting (XGBoost) and deep learning models.

PloS one
Accurate monthly runoff forecasting is vital for water management, flood control, hydropower, and irrigation. In glacierized catchments affected by climate change, runoff is influenced by complex hydrological processes, making precise forecasting eve...

Forecasting acute childhood malnutrition in Kenya using machine learning and diverse sets of indicators.

PloS one
OBJECTIVES: Malnutrition is a leading cause of morbidity and mortality for children under-5 globally. Low- and middle-income countries, such as Kenya, bear the greatest burden of malnutrition. The Kenyan government has been collecting clinical indica...

Accurate total consumer price index forecasting with data augmentation, multivariate features, and sentiment analysis: A case study in Korea.

PloS one
The Consumer Price Index (CPI) is a key economic indicator used by policymakers worldwide to monitor inflation and guide monetary policy decisions. In Korea, the CPI significantly impacts decisions on interest rates, fiscal policy frameworks, and the...

A two-stage forecasting model using random forest subset-based feature selection and BiGRU with attention mechanism: Application to stock indices.

PloS one
The heteroscedastic and volatile characteristics of stock price data have attracted the interest of researchers from various disciplines, particularly in the realm of price forecasting. The stock market's non-stationary and volatile nature, driven by...

Residual XGBoost regression-Based individual moving range control chart for Gross Domestic Product growth monitoring.

PloS one
Accurate and reliable Gross Domestic Product (GDP) forecasting is indispensable for informed economic policymaking and risk management. Autocorrelation, a prevalent characteristic of macroeconomic time series, poses significant challenges to traditio...

Study on forecasting method of power engineering cost based on BIM and DynGCN.

PloS one
In view of the shortcomings of power engineering cost in precision and dynamic in big data environments, this paper proposes building information modelling (BIM) and spatiotemporal modelling-based dynamic graph convolutional neural networks (DynGCN)....

Artificial Intelligence in the Service of Medicine: Current Solutions and Future Perspectives, Opportunities, and Challenges.

La Clinica terapeutica
OBJECTIVE: This article aims to identify the opportunities and risks of Artificial Intelligence tools (AIT) applied to clinical practice, while also reflecting on their impact on the doctor-patient relationship.

Machine learning-based sales forecasting during crises: Evidence from a Turkish women's clothing retailer.

Science progress
BACKGROUND: Retail involves directly delivering goods and services to end consumers. Natural disasters and epidemics/pandemics have significant potential to disrupt supply chains, leading to shortages, forecasting errors, price increases, and substan...

Current Use And Evaluation Of Artificial Intelligence And Predictive Models In US Hospitals.

Health affairs (Project Hope)
Effective evaluation and governance of predictive models used in health care, particularly those driven by artificial intelligence (AI) and machine learning, are needed to ensure that models are fair, appropriate, valid, effective, and safe, or FAVES...