Results 261 to 270 of about 397,119 (307)
Advanced Functional Materials, EarlyView.Bloodstream infections (BSI) are one of the leading causes of mortality and morbidity in both civilian and military populations. This paper summarizes recent progress in novel treatment strategies to manage BSI arising from both bacterial and fungal pathogens using molecules, particles, and materials to elicit host‐directed immunity.
Thomas Thomou +11 more
wiley +1 more source
Early In-Hospital Mortality Prediction Based on xTimesNet and Time Series Interpretable Methods
Xueyan Wang +4 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
openaire +1 more source
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
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: $${\rm{E}}\,x\left( t \right) = 0.$$
J. Santana, R. Vilela Mendes
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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: $${\rm{E}}\,x\left( t \right) = 0.$$
J. Santana, R. Vilela Mendes
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Physics Letters A, 1995
Abstract We introduce a technique to characterize and measure predictability in time series. The technique allows one to formulate precisely a notion of the predictable component of given time series. We illustrate our method for both numerical and experimental time series data.
Liming W. Salvino +3 more
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Abstract We introduce a technique to characterize and measure predictability in time series. The technique allows one to formulate precisely a notion of the predictable component of given time series. We illustrate our method for both numerical and experimental time series data.
Liming W. Salvino +3 more
openaire +1 more source
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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Time Series Prediction and Neural Networks
Journal of Intelligent and Robotic Systems, 2001zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Frank, R. J., Davey, N., Hunt, S. P.
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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 Volna +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 Volna +3 more
openaire +1 more source