AIMC Topic: Forecasting

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Global greenhouse gas reduction forecasting via machine learning model in the scenario of energy transition.

Journal of environmental management Nov 15, 2024
Global warming is becoming increasingly serious, with greenhouse gas (GHGs) emissions identified as a principal contributor. In response to the climate crisis, many countries are actively transitioning to renewable energy. Therefore, it is crucial to...
Global Warming Machine Learning Forecasting Bayes Theorem Greenhouse Gases Models, Theoretical
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Global forecasting of carbon concentration through a deep learning spatiotemporal modeling.

Journal of environmental management Nov 15, 2024
Given the global urgency to mitigate climate change, a key action is the development of effective carbon concentration reduction policies. To this end, an influential factor is the availability of accurate predictions of carbon concentration trends. ...
Deep Learning Models, Theoretical Carbon Neural Networks, Computer Forecasting Climate Change Methane Carbon Dioxide
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Optimized robust learning framework based on big data for forecasting cardiovascular crises.

Scientific reports Nov 15, 2024
Numerous Deep Learning (DL) scenarios have been developed for evolving new healthcare systems that leverage large datasets, distributed computing, and the Internet of Things (IoT). However, the data used in these scenarios tend to be noisy, necessita...
Neural Networks, Computer Algorithms Humans Deep Learning Forecasting Big Data Cardiovascular Diseases
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Comparative analysis of volatility forecasting for healthcare stock indices amid public health crises: a study based on the Bayes-CNN model.

Frontiers in public health Nov 14, 2024
In recent years, public health events have significantly impacted various aspects of human production and daily life, particularly in the domains of disease transmission and economic stability. While many scholars have primarily focused on the influe...
Bayes Theorem Forecasting Investments Humans Pandemics SARS-CoV-2 Public Health Neural Networks, Computer COVID-19 China
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Advancing ensemble learning techniques for residential building electricity consumption forecasting: Insight from explainable artificial intelligence.

PloS one Nov 14, 2024
Accurate electricity consumption forecasting in residential buildings has a direct impact on energy efficiency and cost management, making it a critical component of sustainable energy practices. Decision tree-based ensemble learning techniques are p...
Humans Decision Trees Artificial Intelligence Electricity Machine Learning Housing Forecasting
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Promises and pitfalls of artificial intelligence models in forecasting rheumatoid arthritis treatment response and outcomes.

Seminars in arthritis and rheumatism Nov 9, 2024
None.
Forecasting Arthritis, Rheumatoid Treatment Outcome Humans Artificial Intelligence Antirheumatic Agents
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Explainable artificial intelligence for reliable water demand forecasting to increase trust in predictions.

Water research Nov 9, 2024
The "EU Artificial Intelligence Act" sets a framework for the implementation of artificial intelligence (AI) in Europe. As a legal assessment reveals, AI applications in water supply systems are categorised as high-risk AI if a failure in the AI appl...
Models, Theoretical Water Supply Machine Learning Forecasting Artificial Intelligence
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Development of a deep learning-based feature stream network for forecasting riverine harmful algal blooms from a network perspective.

Water research Nov 5, 2024
Global increases in the occurrence of harmful algal blooms (HABs) are of major concern in water quality and resource management. A predictive model capable of quantifying the spatiotemporal associations between HABs and their influencing factors is r...
Deep Learning Environmental Monitoring Harmful Algal Bloom Rivers Republic of Korea Cyanobacteria Forecasting
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Forecasting nitrous oxide emissions from a full-scale wastewater treatment plant using LSTM-based deep learning models.

Water research Nov 5, 2024
Nitrous oxide (NO) emissions from wastewater treatment plants (WWTPs) exhibit significant seasonal variability, making accurate predictions with conventional biokinetic models difficult due to complex and poorly understood biochemical processes. This...
Forecasting Deep Learning Netherlands Nitrous Oxide Wastewater Waste Disposal, Fluid
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Machine learning for forecasting initial seizure onset in neonatal hypoxic-ischemic encephalopathy.

Epilepsia Nov 4, 2024
OBJECTIVE: This study was undertaken to develop a machine learning (ML) model to forecast initial seizure onset in neonatal hypoxic-ischemic encephalopathy (HIE) utilizing clinical and quantitative electroencephalogram (QEEG) features.
Forecasting Female Humans Machine Learning Electroencephalography Seizures Infant, Newborn Hypoxia-Ischemia, Brain Male
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