AIMC Topic: Forecasting

Clear Filters Showing 191 to 200 of 1639 articles

Enhanced forecasting of rice price and production in Malaysia using novel multivariate fuzzy time series models.

Scientific reports
A significant portion of the world's population relies on rice as a primary source of nutrition. In Malaysia, rice production began in the early 1960s, which led to the cultivation of the country's most significant food crop up till the present day. ...

Hybrid CNN-GRU Model for Real-Time Blood Glucose Forecasting: Enhancing IoT-Based Diabetes Management with AI.

Sensors (Basel, Switzerland)
For people with diabetes, controlling blood glucose level (BGL) is a significant issue since the disease affects how the body metabolizes food, which makes careful insulin regulation necessary. Patients have to manually check their blood sugar levels...

Beyond homophily in spatial-temporal traffic flow forecasting.

Neural networks : the official journal of the International Neural Network Society
Traffic flow forecasting is a crucial yet complex task due to the intricate spatial-temporal correlations arising from road interactions. Recent methods model these interactions using message-passing Graph Convolution Networks (GCNs), which work for ...

Regional PM prediction with hybrid directed graph neural networks and Spatio-temporal fusion of meteorological factors.

Environmental pollution (Barking, Essex : 1987)
Traditional statistical prediction methods on PM often focus on a single temporal or spatial dimension, with limited consideration for regional transport interactions among adjacent cities. To address this limitation, we propose a hybrid directed gra...

The Role and Future of Artificial Intelligence in Robotic Image-Guided Interventions.

Techniques in vascular and interventional radiology
Artificial intelligence and robotics are transforming interventional radiology, driven by advancements in computer vision, robotics and procedural automation. Historically focused on diagnostics, AI now also enhances procedural capabilities in IR, en...

A hybrid model for monthly runoff forecasting based on mixed signal processing and machine learning.

Environmental science and pollution research international
Monthly runoff forecasting plays a critically supportive role in water resources planning and management. Various signal decomposition techniques have been widely applied to enhance the accuracy of monthly runoff forecasting. However, the forecasting...

A hybrid deep learning model-based LSTM and modified genetic algorithm for air quality applications.

Environmental monitoring and assessment
Over time, computing power and storage resource advancements have enabled the widespread accumulation and utilization of data across various domains. In the field of air quality, analyzing data and developing air quality models have become pivotal in...

Uncovering the Probiotic Supplement Landscape: Market Offerings, Sales Patterns, and Future Forecasts Using Machine Learning Approach - A Case Study of Montenegro.

Probiotics and antimicrobial proteins
Global increasing awareness about the health benefits of probiotics resulted to explorational growth in probiotic food supplement market. However, in some countries such as Montenegro, specific probiotic supplement regulation and comprehensive market...

MTLPM: a long-term fine-grained PM2.5 prediction method based on spatio-temporal graph neural network.

Environmental monitoring and assessment
The concentration of PM2.5 is one of the air quality indicators that the public pays the most attention to. Existing methods for PM2.5 prediction primarily analyze and forecast data from individual monitoring stations, without considering the mutual ...

The Transformative Impact of AI, Extended Reality, and Robotics in Interventional Radiology: Current Trends and Applications.

Techniques in vascular and interventional radiology
Interventional Radiology is at the forefront of integrating advanced imaging techniques and minimally-invasive procedures to enhance patient care. The advent of Digital Health Technologies (DHTs), including artificial intelligence (AI), robotics, and...