Results 21 to 30 of about 397,119 (307)
PREDICTION OF INCOMING ORDERS USING THE LONG SHORT-TERM MEMORY METHOD AT PT. XYZ
JISA (Jurnal Informatika dan Sains), 2021 Currently the need for domestic packaging paper continues to increase, driven by the level of consumer awareness about sustainable packaging. PT XYZ is a local company engaged in the Corrugated Cardboard Box (KKG) industry.
Lukman Irawan +2 more
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Time Series Segmentation Based on Stationarity Analysis to Improve New Samples Prediction
Sensors, 2021 A wide range of applications based on sequential data, named time series, have become increasingly popular in recent years, mainly those based on the Internet of Things (IoT).
Ricardo Petri Silva +3 more
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GAN-Based Prediction of Time Series [PDF]
, 2021 The study aims at generating initial and directional insights in the applicability of conditional recurrent generative adversarial nets for the imputation and forecasting of medical time series data. Our experiment with blood pressure series showed that a generative recurrent autoencoder exhibits significant individual learning progress but needs ...
Sven, Festag, Cord, Spreckelsen
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Time Series Prediction on Population Dynamics [PDF]
E3S Web of ConferencesPredicting the time series is a challenging topic mainly on the era of big data. In this research, data taken from population dynamics of one dimension of logistic map with various parameters that leading the system into chaos.
Dwipayana I. Made Eka
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Time series prediction using artificial neural networks
Ciencias Marinas, 2002 In this work, artificial neural network (ANN) algorithms were used to predict time series of the oceanographic variables Southern Oscilation Index (SOI) and sea surface temperature anomaly (SSTA).
MA Pérez-Chavarría +2 more
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Poster: Visual prediction of time series [PDF]
2009 IEEE Symposium on Visual Analytics Science and Technology, 2009 Many well-known time series prediction methods have been used daily by analysts making decisions. To reach a good prediction, we introduce several new visual analysis techniques of smoothing, multi-scaling, and weighted average with the involvement of human expert knowledge. We combine them into a well-fitted method to perform prediction.
Hao, Ming +5 more
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Prediction in Locally Stationary Time Series [PDF]
Journal of Business & Economic Statistics, 2020 We develop an estimator for the high-dimensional covariance matrix of a locally stationary process with a smoothly varying trend and use this statistic to derive consistent predictors in nonstationary time series. In contrast to the currently available methods for this problem the predictor developed here does not rely on fitting an autoregressive ...
Holger Dette, Weichi Wu
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Gender Prediction by Gait Analysis Based on Time Series Variation of Joint Positions [PDF]
Journal of Systemics, Cybernetics and Informatics, 2015 In this paper, a novel gender prediction scheme based on a gait analysis is proposed. For the gait analysis, we propose a novel feature extraction scheme that uses the time series vari- ation in the joint positions directly. Here, normalization by linear
Ryusuke Miyamoto, Risako Aoki
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Time series prediction evolving Voronoi regions [PDF]
Applied Intelligence, 2009 Time series prediction is a complex problem that consists of forecasting the future behavior of a set of data with the only information of the previous data. The main problem is the fact that most of the time series that represent real phenomena include local behaviors that cannot be modelled by global approaches.
Luque, Cristóbal +2 more
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Chaotic Time-Series Prediction using Intelligent Methods [PDF]
Iranian Journal of Electrical and Electronic Engineering, 2023 Today, it can be said that in every field in which timely information is needed, we can use the applications of time-series prediction. In this paper, among so many chaotic systems, the Mackey-Glass and Loranz are chosen.
M. Nezhadshahbodaghi +3 more
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