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Investigating the Effects of Full-Spectrum LED Lighting on Strawberry Traits Using Correlation Analysis and Time-Series Prediction. [PDF]
Plants (Basel)Lu Y, Gong M, Li J, Ma J.
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A New Auto-Regressive Multi-Variable Modified Auto-Encoder for Multivariate Time-Series Prediction: A Case Study with Application to COVID-19 Pandemics. [PDF]
Int J Environ Res Public Healthde Oliveira EV +2 more
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Time Series Prediction and Neural Networks
Journal of Intelligent and Robotic Systems, 2001zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ray J. Frank +2 more
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2021
Over the past decades, the rapid development of big cities is raising the demands of underground space utilization. One of the favorable options for urban development is to build underground tunnels. Notably, a lot of tunnels are located at a low depth in soil or soft rock zones under densely populated areas, and thus the excavation works of shallow ...
Limao Zhang +3 more
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Over the past decades, the rapid development of big cities is raising the demands of underground space utilization. One of the favorable options for urban development is to build underground tunnels. Notably, a lot of tunnels are located at a low depth in soil or soft rock zones under densely populated areas, and thus the excavation works of shallow ...
Limao Zhang +3 more
openaire +1 more source
2013
This article deals with a smart time series prediction based on characteristic patterns recognition. Our goal is to find and recognize important patterns which repeatedly appear in the market history for the purpose of prediction of subsequent trader’s action. The pattern recognition approach is based on neural networks.
Eva Volná +3 more
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This article deals with a smart time series prediction based on characteristic patterns recognition. Our goal is to find and recognize important patterns which repeatedly appear in the market history for the purpose of prediction of subsequent trader’s action. The pattern recognition approach is based on neural networks.
Eva Volná +3 more
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THE CLUSNET ALGORITHM AND TIME SERIES PREDICTION
International Journal of Neural Systems, 1993This paper describes a novel neural network architecture named ClusNet. This network is designed to study the trade-offs between the simplicity of instance-based methods and the accuracy of the more computational intensive learning methods. The features that make this network different from existing learning algorithms are outlined.
W. Hsu +2 more
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Time series — information and prediction
Biological Cybernetics, 1990A time series \(Y_ t\) can be transformed into another time series \(V_ t\) by means of a linear transformation. Should the matrix of that transformation have an inverse, the pair \((Y_ t,V_ t)\) is called invertible. Based on the decomposition procedure for stationary time series it is shown that a sufficient condition for the invertibility of the ...
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1993
A classic statement of the problem of predicting stationary time series x(t) is as follows [6.1, 6.2]. Suppose that a stationary random time series x(t) is defined on time axis t ∈ [∞,+∞]. To simplify the discussion, let us assume that the mean value of the process is zero: $${\rm{E}}\,x\left( t \right) = 0.$$
M. A. Sadovskii, V. F. Pisarenko
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A classic statement of the problem of predicting stationary time series x(t) is as follows [6.1, 6.2]. Suppose that a stationary random time series x(t) is defined on time axis t ∈ [∞,+∞]. To simplify the discussion, let us assume that the mean value of the process is zero: $${\rm{E}}\,x\left( t \right) = 0.$$
M. A. Sadovskii, V. F. Pisarenko
openaire +3 more sources