Generative adversarial networks in time series: A systematic literature review

E Brophy, Z Wang, Q She, T Ward - ACM Computing Surveys, 2023‏ - dl.acm.org
Generative adversarial network (GAN) studies have grown exponentially in the past few
years. Their impact has been seen mainly in the computer vision field with realistic image …

Deep learning in neural networks: An overview

J Schmidhuber - Neural networks, 2015‏ - Elsevier
In recent years, deep artificial neural networks (including recurrent ones) have won
numerous contests in pattern recognition and machine learning. This historical survey …

Artificial neural network model to predict the compressive strength of eco-friendly geopolymer concrete incorporating silica fume and natural zeolite

AA Shahmansouri, M Yazdani, S Ghanbari… - Journal of Cleaner …, 2021‏ - Elsevier
The growing concern about global climate change and its adverse impacts on societies is
putting severe pressure on the construction industry as one of the largest producers of …

[ספר][B] Neural networks and deep learning

CC Aggarwal - 2018‏ - Springer
“Any AI smart enough to pass a Turing test is smart enough to know to fail it.”–*** Ian
McDonald Neural networks were developed to simulate the human nervous system for …

Wave physics as an analog recurrent neural network

TW Hughes, IAD Williamson, M Minkov, S Fan - Science advances, 2019‏ - science.org
Analog machine learning hardware platforms promise to be faster and more energy efficient
than their digital counterparts. Wave physics, as found in acoustics and optics, is a natural …

[HTML][HTML] Deep LSTM model for diabetes prediction with class balancing by SMOTE

SA Alex, NZ Jhanjhi, M Humayun, AO Ibrahim… - Electronics, 2022‏ - mdpi.com
Diabetes is an acute disease that happens when the pancreas cannot produce enough
insulin. It can be fatal if undiagnosed and untreated. If diabetes is revealed early enough, it …

[HTML][HTML] Electricity price forecasting using recurrent neural networks

U Ugurlu, I Oksuz, O Tas - Energies, 2018‏ - mdpi.com
Accurate electricity price forecasting has become a substantial requirement since the
liberalization of the electricity markets. Due to the challenging nature of electricity prices …

How effective is the Grey Wolf optimizer in training multi-layer perceptrons

S Mirjalili - Applied intelligence, 2015‏ - Springer
This paper employs the recently proposed Grey Wolf Optimizer (GWO) for training Multi-
Layer Perceptron (MLP) for the first time. Eight standard datasets including five classification …

[ספר][B] Optical wireless communications: system and channel modelling with Matlab®

Z Ghassemlooy, W Popoola, S Rajbhandari - 2019‏ - taylorfrancis.com
The 2nd Edition of Optical Wireless Communications: System and Channel Modelling with
MATLAB® with additional new materials, is a self-contained volume that provides a concise …

Crop yield prediction integrating genotype and weather variables using deep learning

J Shook, T Gangopadhyay, L Wu… - Plos one, 2021‏ - journals.plos.org
Accurate prediction of crop yield supported by scientific and domain-relevant insights, is
useful to improve agricultural breeding, provide monitoring across diverse climatic …