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IJSTR >> Volume 9 - Issue 1, January 2020 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Research On Stochastic Forecasting Discharge Level Time Series Data Using Extended Linear Group And Extended Semi-Group Approach

[Full Text]

 

AUTHOR(S)

S Sathish, SK Khadar Babu

 

KEYWORDS

Stochastic process, Seasonal periods, Moving average, stochastic extended linear group average, stochastic extended linear semi-group average, Maximum likelihood estimation.

 

ABSTRACT

The water is an important component for human beings, animals, autotrophs and heterotrophs. Actually, human beings continuously adopted to their physical environment. Due to the increased population, human needs more water for drinking, agriculture, etc. The proposed paper explained in detail, the standard measures like mean, standard deviation, co-efficient of R2 and auto-correlations of the downscaling data in hydrology. The new model is MLE by Gaussian distribution is a method that we will find the values of that result are best fit the data sets. Simple downscaling approach, in general, can perform well as the parametric method, generate the observed water level using SELGA and SELSGA approaches. Maximum Likelihood Estimation is the best prediction using parameters of water level data sets. The new model is used, the present proposed article is to predict future values using stochastic extended linear group average and stochastic extended linear semi-group average on generated downscaling data sets.

 

REFERENCES

[1] Adib, A.R.M, Majd, “Optimization of Reservoir Volume by Yield Model And Simulation of it by Dynamic Programming and Markov Chain Method”. American-Eurasion J.Agric. & Environ. Sci., 2009, vol. 5, no. 6, pp. 796-803.
[2] K. Ayob, S.D, Amat ,” Water Use Trend at Universiti Tekologi Malaysia”: Application Of Arima Model. Jurnal Teknology, 2004, vol. 41, n0. 1, pp. 47-56.
[3] Andreas Behr and Sebastian Tente -Stochastic frontier analysis and means of maximum Likelihood and the method of moments, 2008, vol. 978-3-319-20502-18.
[4] W.R Bell, “An Introduction to Forecasting with Time Series Models”. Insurance Mathematics and Economics 3, 1984, pp. 241-255.
[5] B.L ,Bowerman, R.T, O’Connell, “Forecasting and Time Series”: An Applied Approach, 1993, Third Edition. Duxbury Press.

[6] T.W, Hansen, S.J, Mason, L, Sun, A, Tall, “ Review at seasonal climate forecasting for agriculture in Sub-Saharan” Africa.Exp.Agric, 2011, vol.47, no.2, pp. 205.
[7] C. Lee, C, Ko,” Short-term Load Forecasting Using Lifting Scheme and ARIMA Models”. Expert Systems with Applications, 2011, Vol. 38, pp. 5902-591.
[8] G, Naadimuthu, E.S. Lee, “Stochastic Modelling and Optimization of Water Resources Systems”, Mathematical Modelling, 1982, Vol. 3, pp. 117-136.
[9] S, Sathish, SK. Khadar Babu, “Stochastic time series analysis of hydrology data for water resources”. J.Iop Anal.Appl, 2017, vol. 263, 042140.
[10] P.R. Vittal, V.Thangaraj and V.Muralidhar, “Stochastic models for the amount of overflow In a finite dam with random inputs, random outputs and Exponential release policy”, Stochastic analysis and Applications, 2011, vol. 29, pp. 473-485.
[11] R.L, Wilby, S.P, Charles, E, Zorita, B, Timbal, P, Whetton, L, Mearns, “Guidelines for Use of Climate Scenarios Developed from StatisticalDownscaling Methods”. IPCC Task Group on Data and ScenarioSupport for Impact and Climate Analysis, 2004.
[12] R.L, Wilby, H, Hassan, K, Hanaki, “Statistical downscaling of hydrometeorological variables using general circulation model output”, J. Hydrol.,1998, vol. 205,pp.1–19.
[13] F, Wetterhall, H, Winsemius, E, Dutra, M, Werner, E, Paper Berger, “Seasonal predictions of agro-metrological drought indicators for theLimpopo basin”, Hydrol. Earth Syst. Sci, 2015, vol.19, no.6, pp. 2577-258.
[14] Walsh P, Wheeler W (2012) Water uncommon document vital andmoney sparing addition examination. U.S. natural fitness association, taking strolls Paper, 12-05.
[15] Walski TM, Parker FL (1974) patron's water super report. J Environ Eng ASCE a hundred:593–sixty one.