AIMC Topic: Forecasting

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A Multi-objective transfer learning framework for time series forecasting with Concept Echo State Networks.

Neural networks : the official journal of the International Neural Network Society Feb 20, 2025
This paper introduces a novel transfer learning framework for time series forecasting that uses Concept Echo State Network (CESN) and a multi-objective optimization strategy. Our approach addresses the challenges of feature extraction and knowledge t...
Algorithms Humans Forecasting Neural Networks, Computer Time Factors Machine Learning
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Learning from leading indicators to predict long-term dynamics of hourly electricity generation from multiple resources.

Neural networks : the official journal of the International Neural Network Society Feb 19, 2025
Electricity is generated through various resources and then flows between regions via a complex system (grid). Imbalances in electricity generation can lead to the waste of renewable energy. As renewable energy is becoming a larger part of the grid, ...
Renewable Energy Deep Learning Time Factors Electricity Neural Networks, Computer Forecasting
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Long-term solar radiation forecasting in India using EMD, EEMD, and advanced machine learning algorithms.

Environmental monitoring and assessment Feb 18, 2025
Solar radiation plays a critical role in the carbon sequestration processes of terrestrial ecosystems, making it a key factor in environmental sustainability among various renewable energy sources. This study integrates two advanced signal processing...
Sunlight Radiation Monitoring Algorithms Forecasting Environmental Monitoring Solar Energy India Machine Learning
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Hybrid multi-modality multi-task learning for forecasting progression trajectories in subjective cognitive decline.

Neural networks : the official journal of the International Neural Network Society Feb 15, 2025
While numerous studies strive to exploit the complementary potential of MRI and PET using learning-based methods, the effective fusion of the two modalities remains a tricky problem due to their inherently distinctive properties. In addition, current...
Humans Forecasting Female Machine Learning Positron-Emission Tomography Disease Progression Aged Cognitive Dysfunction Male Magnetic Resonance Imaging
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Early detection of disease outbreaks and non-outbreaks using incidence data: A framework using feature-based time series classification and machine learning.

PLoS computational biology Feb 13, 2025
Forecasting the occurrence and absence of novel disease outbreaks is essential for disease management, yet existing methods are often context-specific, require a long preparation time, and non-outbreak prediction remains understudied. To address this...
Humans Machine Learning COVID-19 Disease Outbreaks Incidence ROC Curve Forecasting SARS-CoV-2 Computational Biology Singapore
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Of Lyme disease and machine learning in a One Health world.

American journal of veterinary research Feb 11, 2025
OBJECTIVE: Lyme disease is a vector-borne emerging zoonosis in Ontario driven by human population growth and climate change. Lyme disease is also a prime example of the One Health concept. While little can be done to immediately reverse climate chang...
Zoonoses One Health Ontario Lyme Disease Humans Forecasting Animals Machine Learning
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Forecasting Epidemic Spread With Recurrent Graph Gate Fusion Transformers.

IEEE journal of biomedical and health informatics Feb 10, 2025
Predicting the unprecedented, nonlinear nature of COVID-19 presents a significant public health challenge. Recent advances in deep learning, such as graph neural networks (GNNs), recurrent neural networks (RNNs), and Transformers, have enhanced predi...
Humans Forecasting SARS-CoV-2 Deep Learning Neural Networks, Computer COVID-19
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Machine learning-based evolution of water quality prediction model: An integrated robust framework for comparative application on periodic return and jitter data.

Environmental pollution (Barking, Essex : 1987) Feb 9, 2025
Accurate water quality prediction is paramount for the sustainable management of surface water resources. Current deep learning models face challenges in reliably forecasting water quality due to the non-stationarity of environmental conditions and t...
Machine Learning Water Quality Forecasting Environmental Monitoring
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A prospective real-time transfer learning approach to estimate influenza hospitalizations with limited data.

Epidemics Feb 7, 2025
Accurate, real-time forecasts of influenza hospitalizations would facilitate prospective resource allocation and public health preparedness. State-of-the-art machine learning methods are a promising approach to produce such forecasts, but they requir...
Influenza, Human Seasons Hospitalization United States Humans Machine Learning Forecasting Prospective Studies
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Analyzing and forecasting under-5 mortality trends in Bangladesh using machine learning techniques.

PloS one Feb 7, 2025
BACKGROUND: Under-5 mortality remains a critical social indicator of a country's development and economic sustainability, particularly in developing nations like Bangladesh. This study employs machine learning models, including Linear Regression, Rid...
Linear Models Forecasting Infant, Newborn Bangladesh Humans Male Female Child Mortality Machine Learning Child, Preschool Infant Mortality Infant Bayes Theorem
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