AIMC Topic: Wind

Clear Filters Showing 1 to 10 of 79 articles

Capsule-based federated reinforcement learning adaptive sliding mode for anomaly detection and control of floating wind turbines.

PloS one
Floating wind turbines (FWTs) are now recognized as one of the most effective and affordable renewable energy sources. However, their performance is strongly influenced by dynamic environmental conditions, particularly sea waves under significant osc...

Modeling and forecasting vibrio vulnificus concentration of long-range dependence on marine environmental conditions.

Water research
Vibrio vulnificus (vvh) is an epidemiologically significant bacterium that naturally occurs in coastal waters under favorable environmental conditions and causes one of the highest mortality rates among known foodborne pathogens. Little is currently ...

Robust adaptive control with lumped model uncertainty and wind disturbance estimation for airship trajectory tracking.

PloS one
The robotic airship can be used as an aerostatic platform for many potential applications, for example, communication, hovering payload deliveries, data-gathering for research studies, etc. These applications require a fully autonomous perspective of...

Performance enhancement of a wind driven PMSG using an artificial neural network based nonlinear backstepping controller.

PloS one
With the increasing demand for wind energy in the electric power generation industry, optimizing robust and efficient control strategies is essential for a wind energy conversion system (WECS). In this regard, this study proposes a novel hybrid contr...

Iterative rolling difference-Z-score and machine learning imputation for wind turbine foundation monitoring.

PloS one
In engineering structure performance monitoring, capturing real-time on-site data and conducting precise analysis are critical for assessing structural condition and safety. However, equipment instability and complex on-site environments often lead t...

Fault diagnosis model based on multi-strategy adaptive COA and improved weighted kernel ELM: A case study on wind turbine blade icing.

PloS one
The icing failures of wind turbine blades are critical factors that affect both power generation efficiency and safety. To improve the diagnostic accuracy and speed, an improved weighted kernel extreme learning machine (IWKELM) optimized by multi-str...

Explainable machine learning for predictive modeling of blowing snow detection and meteorological feature assessment using XGBoost-SHAP.

PloS one
Accurate forecasting of blowing snow events is vital for improving numerical models of snow processes, yet traditional predictive methods often lack interpretability. This study leverages eXtreme Gradient Boosting (XGBoost) to detect blowing snow eve...

Evaluating Machine Learning and Deep Learning models for predicting Wind Turbine power output from environmental factors.

PloS one
This study presents a comprehensive comparative analysis of Machine Learning (ML) and Deep Learning (DL) models for predicting Wind Turbine (WT) power output based on environmental variables such as temperature, humidity, wind speed, and wind directi...

A networked station system for high-resolution wind nowcasting in air traffic operations: A data-augmented deep learning approach.

PloS one
This study introduces a high-resolution wind nowcasting model designed for aviation applications at Madeira International Airport, a location known for its complex wind patterns. By using data from a network of six meteorological stations and deep le...

Enhancing air quality predictions in Chile: Integrating ARIMA and Artificial Neural Network models for Quintero and Coyhaique cities.

PloS one
In this comprehensive analysis of Chile's air quality dynamics spanning 2016 to 2021, the utilization of data from the National Air Quality Information System (SINCA) and its network of monitoring stations was undertaken. Quintero, Puchuncaví, and Co...