AIMC Topic: Wind

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Training radial basis function networks for wind speed prediction using PSO enhanced differential search optimizer.

PloS one May 16, 2018
This paper presents an integrated hybrid optimization algorithm for training the radial basis function neural network (RBF NN). Training of neural networks is still a challenging exercise in machine learning domain. Traditional training algorithms in...
Wind Models, Theoretical Neural Networks, Computer Machine Learning
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Integrated optimization of unmanned aerial vehicle task allocation and path planning under steady wind.

PloS one Mar 21, 2018
Wind has a significant effect on the control of fixed-wing unmanned aerial vehicles (UAVs), resulting in changes in their ground speed and direction, which has an important influence on the results of integrated optimization of UAV task allocation an...
Algorithms Aircraft Calibration Wind Systems Integration Robotics Remote Sensing Technology
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Stacked Autoencoders for Outlier Detection in Over-the-Horizon Radar Signals.

Computational intelligence and neuroscience Oct 23, 2017
Detection of outliers in radar signals is a considerable challenge in maritime surveillance applications. High-Frequency Surface-Wave (HFSW) radars have attracted significant interest as potential tools for long-range target identification and outlie...
Wind Cluster Analysis Signal Processing, Computer-Assisted Humans Machine Learning Algorithms Radar Nonlinear Dynamics Signal-To-Noise Ratio
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Prediction of Short-Distance Aerial Movement of Phakopsora pachyrhizi Urediniospores Using Machine Learning.

Phytopathology Sep 6, 2017
Dispersal of urediniospores by wind is the primary means of spread for Phakopsora pachyrhizi, the cause of soybean rust. Our research focused on the short-distance movement of urediniospores from within the soybean canopy and up to 61 m from field-gr...
Wind Machine Learning Models, Theoretical Phakopsora pachyrhizi Temperature Glycine max Plant Diseases Spores, Fungal Humidity
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Evaluating the predictability of PM grades in Seoul, Korea using a neural network model based on synoptic patterns.

Environmental pollution (Barking, Essex : 1987) Sep 6, 2016
As of November 2014, the Korean Ministry of Environment (KME) has been forecasting the concentration of particulate matter with diameters ≤ 10 μm (PM) classified into four grades: low (PM ≤ 30 μg m), moderate (30 < PM ≤ 80 μg m), high (80 < PM ≤ 150 ...
Seasons Meteorology Seoul Air Pollutants Particulate Matter Temperature Wind China Models, Theoretical Environmental Monitoring Particle Size Neural Networks, Computer Forecasting Republic of Korea
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Modeling the reflection of Photosynthetically active radiation in a monodominant floodable forest in the Pantanal of Mato Grosso State using multivariate statistics and neural networks.

Anais da Academia Brasileira de Ciencias Aug 15, 2016
The study of radiation entrance and exit dynamics and energy consumption in a system is important for understanding the environmental processes that rule the biosphere-atmosphere interactions of all ecosystems. This study provides an analysis of the ...
Photosynthesis Radiation Forests Wind Neural Networks, Computer Multivariate Analysis Seasons Brazil Humidity Wetlands Time Factors Rain
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FDI based on Artificial Neural Network for Low-Voltage-Ride-Through in DFIG-based Wind Turbine.

ISA transactions Jun 2, 2016
As per modern electrical grid rules, Wind Turbine needs to operate continually even in presence severe grid faults as Low Voltage Ride Through (LVRT). Hence, a new LVRT Fault Detection and Identification (FDI) procedure has been developed to take the...
Algorithms Computer Simulation Wind Equipment Failure Signal Processing, Computer-Assisted Nonlinear Dynamics Neural Networks, Computer Mechanical Phenomena Electric Power Supplies
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Forecasting PM10 in Algiers: efficacy of multilayer perceptron networks.

Environmental science and pollution research international Sep 18, 2015
Air quality forecasting system has acquired high importance in atmospheric pollution due to its negative impacts on the environment and human health. The artificial neural network is one of the most common soft computing methods that can be pragmatic...
Environment Algeria Particle Size Humans Air Pollutants Wind Neural Networks, Computer Models, Theoretical Forecasting Environmental Monitoring Temperature
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An Interval-Valued Neural Network Approach for Uncertainty Quantification in Short-Term Wind Speed Prediction.

IEEE transactions on neural networks and learning systems Feb 26, 2015
We consider the task of performing prediction with neural networks (NNs) on the basis of uncertain input data expressed in the form of intervals. We aim at quantifying the uncertainty in the prediction arising from both the input data and the predict...
Time Factors Predictive Value of Tests Algorithms Humans Uncertainty Wind Motion Neural Networks, Computer Reproducibility of Results
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Adaptive Neural Control of a Class of Output-Constrained Nonaffine Systems.

IEEE transactions on cybernetics Feb 4, 2015
In this paper, we present a novel tracking controller for a class of uncertain nonaffine systems with time-varying asymmetric output constraints. Firstly, the original nonaffine constrained (in the sense of the output signal) control system is transf...
Torque Nonlinear Dynamics Neural Networks, Computer Models, Theoretical Wind Signal Processing, Computer-Assisted
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