scholarly journals Trends of reported human brucellosis cases in mainland China from 2007 to 2017: an exponential smoothing time series analysis

2018 ◽  
Vol 23 (1) ◽  
Author(s):  
Peng Guan ◽  
Wei Wu ◽  
Desheng Huang
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Mainland China ◽  
Exponential Smoothing ◽  
Human Brucellosis ◽  
Series Analysis

scholarly journals COVID-19 transmission in Mainland China is associated with temperature and humidity: A time-series analysis

2020 ◽  
Vol 728 ◽  
pp. 138778 ◽  
Author(s):  
Hongchao Qi ◽  
Shuang Xiao ◽  
Runye Shi ◽  
Michael P. Ward ◽  
Yue Chen ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Mainland China ◽  
Series Analysis ◽  
Temperature And Humidity

Time-Series Analysis on Human Brucellosis During 2004-2013 in Shandong Province, China

2014 ◽  
Vol 62 (3) ◽  
pp. 228-235 ◽  
Author(s):  
L. Yang ◽  
Z.-W. Bi ◽  
Z.-Q. Kou ◽  
X.-J. Li ◽  
M. Zhang ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Shandong Province ◽  
Human Brucellosis ◽  
Series Analysis

Analysis of Surface Water Quality in Tehran

2002 ◽  
Vol 37 (2) ◽  
pp. 489-511 ◽  
Author(s):  
Golamreza Asadollah-Fardi
Keyword(s):  
Water Quality ◽  
Time Series ◽  
Surface Water ◽  
Time Series Analysis ◽  
Surface Water Quality ◽  
Exponential Smoothing ◽  
Future Design ◽  
Series Analysis

Abstract Box-Jenkins and exponential smoothing time series analysis of the monthly water quality in surface water in Tehran was conducted as a case study. Various univariate models were developed for each determinand. Most of the models were seasonal, indicating that the water quality determinands vary throughout the year. The models follow the same pattern of variations present in the data. This study shows the credibility of the models, therefore the models may be used for future design purposes.

scholarly journals Time series analysis of temporal trends in the pertussis incidence in Mainland China from 2005 to 2016

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Qianglin Zeng ◽  
Dandan Li ◽  
Gui Huang ◽  
Jin Xia ◽  
Xiaoming Wang ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Temporal Trends ◽  
Mainland China ◽  
Series Analysis

scholarly journals Time Series Analysis of Decadal Precipitation Pattern at Selected Cities of Southern India

2021 ◽  
Vol 20 (3) ◽  
Author(s):  
T. S. Subbiah ◽  
P. Parthiban ◽  
R. Mahesh ◽  
A. Das
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Empirical Analysis ◽  
Stochastic Modeling ◽  
Tamil Nadu ◽  
Exponential Smoothing ◽  
Southern India ◽  
Precipitation Pattern ◽  
Short Term ◽  
Series Analysis

To characterize and explore the short-term climatic patterns over the last decade (Jan. 2009 to Dec. 2018), the present research has been carried out, involving time series analysis of precipitation pattern in three cities of Tamil Nadu, namely, Thanjavur, Nagapattinam, and Chennai, referring to deltaic, coastal and highly urbanized cities of Tamil Nadu, respectively. The study involves time series empirical analysis, decomposition, exponential smoothing, and various stochastic modeling. Herein, the location-specific suitable models are obtained and specific predictions are being carried out, as well.

scholarly journals Forecasting the spread of COVID19 in Hungary

2020 ◽  
Author(s):  
Owais Mujtaba Khanday ◽  
Samad Dadvandipour ◽  
Mohd. Aaqib Lone
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Reproduction Number ◽  
Sir Model ◽  
Exponential Smoothing ◽  
Short Term ◽  
Smoothing Methods ◽  
Series Analysis ◽  
Short Term Forecasting

AbstractTime series analysis of the COVID19/ SARS-CoV-2 spread in Hungary is presented. Different methods effective for short-term forecasting are applied to the dataset, and predictions are made for the next 20 days. Autoregression and other exponential smoothing methods are applied to the dataset. SIR model is used and predicted 64% of the population could be infected by the virus considering the whole population is susceptible to be infectious Autoregression, and exponential smoothing methods indicated there would be more than a 60% increase in the cases in the coming 20 days. The doubling of the number of total cases is found to around 16 days using an effective reproduction number.

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