Showing items with similar title or keywords.

• Application of artificial neural network and genetic algorithm to forecasting of wind power output 

  Chao, Lin (2007)

• Using deep neural networks for kinematic analysis : challenges and opportunities 

  Cronin, Neil J. (Elsevier BV, 2021)

  Kinematic analysis is often performed in a lab using optical cameras combined with reflective markers. With the advent of artificial intelligence techniques such as deep neural networks, it is now possible to perform such ...

• Testing, comissioning and additional development of neural network application for condition monitoring of wind turbine drive train 

  Ojala, Mikko-Ilari (2013)

• Process‐Informed Neural Networks : A Hybrid Modelling Approach to Improve Predictive Performance and Inference of Neural Networks in Ecology and Beyond 

  Wesselkamp, Marieke; Moser, Niklas; Kalweit, Maria; Boedecker, Joschka; Dormann, Carsten F. (Wiley, 2024)

  Despite deep learning being state of the art for data-driven model predictions, its application in ecology is currently subject to two important constraints: (i) deep-learning methods are powerful in data-rich regimes, but ...

• Applications of Artificial Intelligence in the Economy, Including Applications in Stock Trading, Market Analysis, and Risk Management 

  Rahmani, Amir Masoud; Rezazadeh, Bahareh; Haghparast, Majid; Chang, Wei-Che; Ting, Shen Guan (Institute of Electrical and Electronics Engineers (IEEE), 2023)

  In an increasingly automated world, Artificial Intelligence (AI) promises to revolutionize how people work, consume, and develop their societies. Science and technology advancement has led humans to seek solutions to ...