AIMC Topic: Wind

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A gyroscope-free visual-inertial flight control and wind sensing system for 10-mg robots.

Science robotics
Tiny "gnat robots," weighing just a few milligrams, were first conjectured in the 1980s. How to stabilize one if it were to hover like a small insect has not been answered. Challenges include the requirement that sensors be both low mass and high ban...

Opportunistic soaring by birds suggests new opportunities for atmospheric energy harvesting by flying robots.

Journal of the Royal Society, Interface
The use of flying robots (drones) is increasing rapidly, but their utility is limited by high power demand, low specific energy storage and poor gust tolerance. By contrast, birds demonstrate long endurance, harvesting atmospheric energy in environme...

xLength: Predicting Expected Ski Jump Length Shortly after Take-Off Using Deep Learning.

Sensors (Basel, Switzerland)
With tracking systems becoming more widespread in sports research and regular training and competitions, more data are available for sports analytics and performance prediction. We analyzed 2523 ski jumps from 205 athletes on five venues. For every j...

Modeling monthly reference evapotranspiration process in Turkey: application of machine learning methods.

Environmental monitoring and assessment
In this study, the predictive power of three different machine learning (ML)-based approaches, namely, multi-gene genetic programming (MGGP), M5 model trees (M5Tree), and K-nearest neighbor algorithm (KNN), for long-term monthly reference evapotransp...

Evaluation of Empirical and Machine Learning Approaches for Estimating Monthly Reference Evapotranspiration with Limited Meteorological Data in the Jialing River Basin, China.

International journal of environmental research and public health
The accurate estimation of reference evapotranspiration () is crucial for water resource management and crop water requirements. This study aims to develop an efficient and accurate model to estimate the monthly in the Jialing River Basin, China. Fo...

Research on adaptive combined wind speed prediction for each season based on improved gray relational analysis.

Environmental science and pollution research international
The stability of the power grid and the operational security of the power system depend on the precise prediction of wind speed. In consideration of the nonlinear and non-stationary characteristics of wind speed in different seasons, this paper emplo...

Machine learning and features for the prediction of thermal sensation and comfort using data from field surveys in Cyprus.

International journal of biometeorology
Perception can influence individuals' behaviour and attitude affecting responses and compliance to precautionary measures. This study aims to investigate the performance of methods for thermal sensation and comfort prediction. Four machine learning a...

Short-Term Demand Forecasting Method in Power Markets Based on the KSVM-TCN-GBRT.

Computational intelligence and neuroscience
With the consumption of new energy and the variability of user activity, accurate and fast demand forecasting plays a crucial role in modern power markets. This paper considers the correlation between temperature, wind speed, and real-time electricit...

Multi-step wind speed forecasting based on a hybrid decomposition technique and an improved back-propagation neural network.

Environmental science and pollution research international
Accurate wind speed forecasting (WSF) not only ensures stable power system operation but also contributes to enhancing the competitiveness of wind power companies in the market. In this paper, a hybrid prediction model based on secondary decompositio...