[HTML][HTML] Predicting Time SeriesUsing an Automatic New Algorithm of the Kalman Filter

JD Borrero, J Mariscal - Mathematics, 2022 - mdpi.com
Time series forecasting is one of the main venues followed by researchers in all areas. For
this reason, we develop a new Kalman filter approach, which we call the alternative Kalman …

[HTML][HTML] Characterizing and forecasting the responses of tropical forest leaf phenology to El Nino by machine learning algorithms

T Lamjiak, R Kaewthongrach, B Sirinaovakul… - Plos one, 2021 - journals.plos.org
Climate change and global warming have serious adverse impacts on tropical forests. In
particular, climate change may induce changes in leaf phenology. However, in tropical dry …

Analyzing the safety impacts of variable speed limit control on aggregated driving behavior based on traffic big data

X Qu, M Yang, J Ji, L Li, B Ran - Journal of advanced …, 2021 - Wiley Online Library
Variable speed limit (VSL) control dynamically adjusts the displayed speed limit to
harmonize traffic speed, prevent congestions, and reduce crash risks based on prevailing …

[HTML][HTML] Dynamic Associations Between Centers for Disease Control and Prevention Social Media Contents and Epidemic Measures During COVID-19: Infoveillance …

S Yin, S Chen, Y Ge - JMIR infodemiology, 2024 - infodemiology.jmir.org
Background Health agencies have been widely adopting social media to disseminate
important information, educate the public on emerging health issues, and understand public …

Performance Measures for Evaluating the Accuracy of Time Series Hybrid Model Using High Frequency Data

TO Olatayo, KI Ekerikevwe - Britain International of Exact Sciences …, 2022 - biarjournal.com
Given that the traditional ARIMAX model has rarely been applied to any of the climate
change and environmental agents, which are the most cognate agents with associated …

Factor augmentation for cryptocurrency return forecasting

Y Yeom, Y Han, J Lee, S Park, J Lee… - The Korean Journal of …, 2022 - koreascience.kr
In this study, we propose factor augmentation to improve forecasting power of
cryptocurrency return. We consider financial and economic variables as well as …

Infoveillance study on the dynamic associations between CDC social media contents and epidemic measures during COVID-19

S Yin, S Chen, Y Ge - medRxiv, 2023 - medrxiv.org
Background Health agencies have been widely adopting social media to disseminate
important information, educate the public on emerging health issues, and understand public …

A Combined Discrete Road Traffic State Prediction Model Based on GFD‐ARMA‐FISHER Analytical Framework

P Yuan, Y Han - Mathematical Problems in Engineering, 2022 - Wiley Online Library
With the popularization of the Internet and the widespread application of mobile terminal,
travelers are increasingly dependent on traffic information. It is particularly important to …

[PDF][PDF] Detecting concurrent relationships of selected time series data for ARIMAX model

HC ChangTzeng, DF Chang, YH Lo - ICIC Express Letters Part B …, 2019 - icicelb.org
Traditional ARIMA (autoregressive integrated moving average) model works with one series
data set, while various cases, with multivariable series data sets, did not fit ARIMA models …

Forecasting the volume of mortgage loans with open Internet data in the period of noticeable changes in the Russian mortgage market

E Stavinova, A Timoshina, P Chunaev - Procedia Computer Science, 2021 - Elsevier
Forecasting the volume of mortgage loans is important due to the necessity to correctly plan
money flows and to ensure the liquidity of assets of credit organizations. At the time of the …