Shallow neural networks for fluid flow reconstruction with limited sensors
نویسندگان
چکیده
منابع مشابه
Using Neural Networks with Limited Data to Estimate Manufacturing Cost
Neural networks were used to estimate the cost of jet engine components, specifically shafts and cases. The neural network process was compared with results produced by the current conventional cost estimation software and linear regression methods. Due to the complex nature of the parts and the limited amount of information available, data expansion techniques such as doubling-data and data-cr...
متن کاملNumerical treatment for nonlinear steady flow of a third grade fluid in a porous half space by neural networks optimized
In this paper, steady flow of a third-grade fluid in a porous half space has been considered. This problem is a nonlinear two-point boundary value problem (BVP) on semi-infinite interval. The solution for this problem is given by a numerical method based on the feed-forward artificial neural network model using radial basis activation functions trained with an interior point method. ...
متن کاملApplication of Wavelet Neural Networks for Improving of Ionospheric Tomography Reconstruction over Iran
In this paper, a new method of ionospheric tomography is developed and evaluated based on the neural networks (NN). This new method is named ITNN. In this method, wavelet neural network (WNN) with particle swarm optimization (PSO) training algorithm is used to solve some of the ionospheric tomography problems. The results of ITNN method are compared with the residual minimization training neura...
متن کاملNeural Monitoring With CMOS Image Sensors
Implantable image sensors have several biomedical applications due to their miniature size, light weight, and low power consumption achieved through sub-micron standard CMOS (Complementary Metal Oxide Semiconductor) technologies. The main applications are in specific cell labeling, neural activity detection, and biomedical imaging. In this paper the recent research studies on implantable CMOS i...
متن کاملRecurrent Neural Networks With Limited Numerical Precision
Recurrent Neural Networks (RNNs) produce state-of-art performance on many machine learning tasks but their demand on resources in terms of memory and computational power are often high. Therefore, there is a great interest in optimizing the computations performed with these models especially when considering development of specialized low-power hardware for deep networks. One way of reducing th...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences
سال: 2020
ISSN: 1364-5021,1471-2946
DOI: 10.1098/rspa.2020.0097