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Deep learning in robotics: a review of recent research
Advances in deep learning over the last decade have led to a flurry of research in the
application of deep artificial neural networks to robotic systems, with at least 30 papers …
application of deep artificial neural networks to robotic systems, with at least 30 papers …
Time2vec: Learning a vector representation of time
Time is an important feature in many applications involving events that occur synchronously
and/or asynchronously. To effectively consume time information, recent studies have …
and/or asynchronously. To effectively consume time information, recent studies have …
Time series analysis based on informer algorithms: A survey
Q Zhu, J Han, K Chai, C Zhao - Symmetry, 2023 - mdpi.com
Long series time forecasting has become a popular research direction in recent years, due
to the ability to predict weather changes, traffic conditions and so on. This paper provides a …
to the ability to predict weather changes, traffic conditions and so on. This paper provides a …
A big data driven framework for demand-driven forecasting with effects of marketing-mix variables
This study aims to investigate the contributions of promotional marketing activities, historical
demand and other factors to predict, and develop a big data-driven fuzzy classifier-based …
demand and other factors to predict, and develop a big data-driven fuzzy classifier-based …
From Fourier to Koopman: Spectral methods for long-term time series prediction
We propose spectral methods for long-term forecasting of temporal signals stemming from
linear and nonlinear quasi-periodic dynamical systems. For linear signals, we introduce an …
linear and nonlinear quasi-periodic dynamical systems. For linear signals, we introduce an …
Modified genetic algorithm-based feature selection combined with pre-trained deep neural network for demand forecasting in outpatient department
A well-performed demand forecasting can provide outpatient department (OPD) managers
with essential information for staff scheduling and rostering, considering the non-reservation …
with essential information for staff scheduling and rostering, considering the non-reservation …
Artificial intelligence-based evaluation of the factors affecting the sales of an iron and steel company
It is important to predict the sales of an iron and steel company and to identify the variables
that influence these sales for future planning. The aim in this study was to identify and model …
that influence these sales for future planning. The aim in this study was to identify and model …
Deep signature transforms
The signature is an infinite graded sequence of statistics known to characterise a stream of
data up to a negligible equivalence class. It is a transform which has previously been treated …
data up to a negligible equivalence class. It is a transform which has previously been treated …
Short-term wind power forecasting by stacked recurrent neural networks with parametric sine activation function
X Liu, J Zhou, H Qian - Electric Power Systems Research, 2021 - Elsevier
Short-term wind power forecasting is a challenging issue in renewable power generation
and distribution due to inevitable intermittency, complex fluctuation and high volatility of wind …
and distribution due to inevitable intermittency, complex fluctuation and high volatility of wind …
Taming the waves: sine as activation function in deep neural networks
G Parascandolo, H Huttunen, T Virtanen - 2016 - openreview.net
Most deep neural networks use non-periodic and monotonic—or at least quasiconvex—
activation functions. While sinusoidal activation functions have been successfully used for …
activation functions. While sinusoidal activation functions have been successfully used for …