Kriging Infill of Missing Data and Temporal Analysis of Rainfall in North Central Region of Bangladesh

Choudhury, Nazia Hassan; Rahman, Ataur

doi:10.4172/2332-2594.1000141

Cited by 6 publications

(1 citation statement)

References 9 publications

(7 reference statements)

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“…[11] The unobserved locations were filled in using the prediction results, and the gaps in particular areas were filled in by interpolating the available data. Though its original application was in geostatistics, kriging is a general statistical interpolation technique that finds use in numerous other areas, including climatology [9] and education [14].…”

Section: Introductionmentioning

confidence: 99%

Spatial Data Mining for Prediction of Unobserved Zinc Pollutant using Various Kriging Methods

Krotha,

SK,

et al. 2023

Preprint

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After years of contamination, rivers may get large amounts of heavy metal pollution. Our investigation's goal is to identify the river's hazardous locations. In our study case, we select the zinc-contaminated floodplains of the Meuse River (Zn). Excessive zinc levels may lead to a variety of health issues, including anemia, rashes, vomiting, and cramping in the stomach. However, there isn't a lot of sample data available about the Meuse River's zinc concentration; as a result, it's necessary to generate the missing data in unidentified regions. This study employs universal Kriging in spatial data mining to explore and predict unknown zinc pollutants. The semivariogram is a useful tool for representing the variability pattern of zinc. To predict the unknown regions, this captured model will be interpolated using the Kriging method. Regression with geographic weighting makes it possible to see how stimulus-response relationships change over space. We use a variety of semivariograms in our work, such as matern, exponential, and linear models. We also propose Universal Kriging and geographically weighted regression. The experimental findings show that: (i) the matern model, as determined by calculating the minimum error sum of squares, is the best theoretical semivariogram model; and (ii) the accuracy of the predictions can be visually demonstrated by projecting the results onto the real map.

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Section: Introductionmentioning

confidence: 99%

Spatial Data Mining for Prediction of Unobserved Zinc Pollutant using Various Kriging Methods

Krotha,

SK,

et al. 2023

Preprint

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Spatial–temporal variability and extreme climate indices of precipitation in a coastal watershed of southeastern Brazil

Guarnier

Barroso

2021

Environ Monit Assess

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Multi-day rhythms modulate seizure risk in epilepsy

et al. 2018

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Epilepsy is defined by the seemingly random occurrence of spontaneous seizures. The ability to anticipate seizures would enable preventative treatment strategies. A central but unresolved question concerns the relationship of seizure timing to fluctuating rates of interictal epileptiform discharges (here termed interictal epileptiform activity, IEA), a marker of brain irritability observed between seizures by electroencephalography (EEG). Here, in 37 subjects with an implanted brain stimulation device that detects IEA and seizures over years, we find that IEA oscillates with circadian and subject-specific multidien (multi-day) periods. Multidien periodicities, most commonly 20–30 days in duration, are robust and relatively stable for up to 10 years in men and women. We show that seizures occur preferentially during the rising phase of multidien IEA rhythms. Combining phase information from circadian and multidien IEA rhythms provides a novel biomarker for determining relative seizure risk with a large effect size in most subjects.

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Kriging Infill of Missing Data and Temporal Analysis of Rainfall in North Central Region of Bangladesh

Cited by 6 publications

References 9 publications

Spatial Data Mining for Prediction of Unobserved Zinc Pollutant using Various Kriging Methods

Spatial Data Mining for Prediction of Unobserved Zinc Pollutant using Various Kriging Methods

Spatial–temporal variability and extreme climate indices of precipitation in a coastal watershed of southeastern Brazil

Multi-day rhythms modulate seizure risk in epilepsy

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