2D Graphical Analysis of Wastewater Influent Capacity Time Series
The extraction of meaningful information from image
could be an alternative method for time series analysis. In this paper,
we propose a graphical analysis of time series grouped into table
with adjusted colour scale for numerical values. The advantages of
this method are also discussed. The proposed method is easy to
understand and is flexible to implement the standard methods of
pattern recognition and verification, especially for noisy
environmental data.
[1] Golyandina N., Nekrutkin V., Zhigljavsku A.Z, Analysis of Time Series
Structure; SSA and related techniques, Chapman &Hall/CRC
Monographs on Statistic & Applied Probability, Boca Raton 2001.
[2] Kitagawa G., Introduction to Time Serieas Modeling, Chapman
&Hall/CRC Monographs on Statistic & Applied Probability, Boca Raton
2009.
[3] Gamal El-Din A., Smith D.W., "Modelling approach for high flow rate
in wastewater treatment operation", Journal of Environmental
Engineering and Science 2000, vol. 1, pp. 275-291.
[4] Dahlaus R., Eichler M., "Causality and graphical models in time series
analysis", http://galton.uchicago.edu/~eichler/hsss.pdf.
[5] Hu Y., Osuna-Highley E., Hua J., Nowicki T.S., Stolz R., McKayle C.,
Murphy R.F., "Automated analysis of protein subcellular location in
time series images", Bioinformatic 2010 vol.26 no. 13, pp.1630-1636.
[6] Zvornarev P.S., Apalkov I.V., Khryashchev, Priorov A.L., "Adaptive
Switching Median Filter with Neural Network Impulse Detection Step",
Lecture Notes in Computer Science, 2005 Volume 3696/2005 pp. 537-
542.
[7] Rong-Chin L., Wen-Hsiang T., "Gray-Scale Hough transform for thick
line detection in gray-scale images", Pattern Recognition,1995, vol. 28,
no.5, pp.647-661.
[1] Golyandina N., Nekrutkin V., Zhigljavsku A.Z, Analysis of Time Series
Structure; SSA and related techniques, Chapman &Hall/CRC
Monographs on Statistic & Applied Probability, Boca Raton 2001.
[2] Kitagawa G., Introduction to Time Serieas Modeling, Chapman
&Hall/CRC Monographs on Statistic & Applied Probability, Boca Raton
2009.
[3] Gamal El-Din A., Smith D.W., "Modelling approach for high flow rate
in wastewater treatment operation", Journal of Environmental
Engineering and Science 2000, vol. 1, pp. 275-291.
[4] Dahlaus R., Eichler M., "Causality and graphical models in time series
analysis", http://galton.uchicago.edu/~eichler/hsss.pdf.
[5] Hu Y., Osuna-Highley E., Hua J., Nowicki T.S., Stolz R., McKayle C.,
Murphy R.F., "Automated analysis of protein subcellular location in
time series images", Bioinformatic 2010 vol.26 no. 13, pp.1630-1636.
[6] Zvornarev P.S., Apalkov I.V., Khryashchev, Priorov A.L., "Adaptive
Switching Median Filter with Neural Network Impulse Detection Step",
Lecture Notes in Computer Science, 2005 Volume 3696/2005 pp. 537-
542.
[7] Rong-Chin L., Wen-Hsiang T., "Gray-Scale Hough transform for thick
line detection in gray-scale images", Pattern Recognition,1995, vol. 28,
no.5, pp.647-661.
@article{"International Journal of Earth, Energy and Environmental Sciences:51696", author = "Monika Chuchro and Maciej Dwornik", title = "2D Graphical Analysis of Wastewater Influent Capacity Time Series", abstract = "The extraction of meaningful information from image
could be an alternative method for time series analysis. In this paper,
we propose a graphical analysis of time series grouped into table
with adjusted colour scale for numerical values. The advantages of
this method are also discussed. The proposed method is easy to
understand and is flexible to implement the standard methods of
pattern recognition and verification, especially for noisy
environmental data.", keywords = "graphical analysis, time series, seasonality, noisy
environmental data", volume = "5", number = "5", pages = "301-4", }