Results 261 to 270 of about 8,462,031 (305)

Short term hospital occupancy prediction

Health Care Management Science, 2006
Inpatient census, or occupancy, is a primary driver of resource use in hospitals. Fluctuations in occupancy complicate decisions related to staffing, bed management, ambulance diversions, and may ultimately impact both quality of patient care and nursing job satisfaction.
Steven J, Littig, Mark W, Isken
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Short-Term Tide Prediction

2007
Ever since the first fishermen ventured into the sea, tides have been the subject of intense human observation. As a result, computational models and 'tide predicting machines', mechanical computers for predicting tides have been developed over 100 years ago.
Hasler, N., Hasler, K.
openaire   +3 more sources

The Short-term User Modeling for Predictive Applications

Journal on Data Semantics, 2018
One of the important purposes of data mining on the web is to reveal hidden characteristics of users including their behavior. These characteristics are often used to analyze previous user actions, his/her preferences, and also to predict the future behavior.
Michal Kompan, Ondrej Kassák, Mária Bieliková   +2 more
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Predicting short-term disability in multiple sclerosis

Neurology, 2007
To develop covariate specific short-term disability curves to demonstrate the probability of progressing by Expanded Disability Status Scale (EDSS) at semiannual visits.Semiannual EDSS scores were prospectively collected in 218 relapsing-remitting (RR) and clinically isolated syndrome (CIS) patients as part of the Comprehensive Longitudinal ...
S A, Gauthier, M, Mandel, C R G, Guttmann, B I, Glanz, S J, Khoury, R A, Betensky, H L, Weiner   +6 more
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Are Prices Predictable in the Short Term?

SSRN Electronic Journal, 2015
Standard financial models assume that capital markets are fully efficient, which makes asset prices unforecastable. In contrast, the behavioral finance argues that markets may not be efficient, at least in the short term, given the limits to arbitrage. Combining both strands of literature, our paper provides evidence to suggest that multiple states of ...
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Short-Term Traffic Prediction Using Long Short-Term Memory Neural Networks

2018 IEEE International Congress on Big Data (BigData Congress), 2018
Short-term traffic prediction allows Intelligent Transport Systems to proactively respond to events before they happen. With the rapid increase in the amount, quality, and detail of traffic data, new techniques are required that can exploit the information in the data in order to provide better results while being able to scale and cope with increasing
Zainab Abbas, Ahmad Al-Shishtawy, Sarunas Girdzijauskas, Vladimir Vlassov   +3 more
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An Aggregation Approach to Short-Term Traffic Flow Prediction

IEEE Transactions on Intelligent Transportation Systems, 2009
In this paper, an aggregation approach is proposed for traffic flow prediction that is based on the moving average (MA), exponential smoothing (ES), autoregressive MA (ARIMA), and neural network (NN) models. The aggregation approach assembles information from relevant time series. The source time series is the traffic flow volume that is collected 24 h/
Man-Chun Tan, Sze Chun Wong, Jian-Min Xu, Zhan-Rong Guan, Peng Zhang 0014   +4 more
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Short Term Stock Prediction Using SOM

2009
In this paper, we propose a stock movement prediction model using self organization map. The correlation is adapted to select inputs from technical indexes. The self-organization map is utilized to make decision of stock selling or buying. The proposed model is tested on the Microsoft and General Electric.
Prompong Sugunsil, Samerkae Somhom
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Neural Short-Term Prediction Based on Dynamics Reconstruction

Neural Processing Letters, 1999
In this paper we present an application of dynamics reconstruction techniques to model order estimation. Both the Grassberger–Procaccia and the Takens‘ method were applied, yielding similar values for the correlation dimension, hence for the model order.
CAMASTRA, Francesco, COLLA A. M.
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Short-Term Traffic Prediction

Traffic prediction accuracy is pivotal for fruitful urban transportation management. Existing methodologies often struggle to record complex spatio-temporal features of traffic patterns, which results in sub-optimal congestion management. This approach integrates Bayesian inference with a graph attention network (GAN) and a SARIMA model to ...
S. Jothishwar, Visnu Dharsini S., S. Dinesh, K. Jayasurya   +3 more
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