Sliding Window Based Technique to Obtain Correlation Between Field Variables

dc.contributor.authorChavan, Harshada Chandrakant
dc.date.accessioned2018-03-22T21:01:56Z
dc.date.available2018-03-22T21:01:56Z
dc.date.issued2015en_US
dc.description.abstractIn agriculture, finding correlation between field variables such as yield, NDVI, etc. is a classic problem. The most popular solution for finding correlation is to use regression analysis over complete field. In a field, there are numerous soil variables such as soil composition, water content, etc. that affect the correlation and it is not always possible to consider such factors in regression model. These factors adversely affect the accuracy of the correlation model. We demonstrate that it is incomplete and inaccurate to represent such correlation using single regression model for the complete field. We propose a novel technique- Sliding Window Based Technique, which finds correlations over small areas, windows, of the field instead of modelling one correlation for entire field. We prove our claims with the help of experiments done on the field data. We evaluate the relationship over multiple window sizes and select appropriate window sizes for further analysis.en_US
dc.identifier.urihttps://hdl.handle.net/10365/27844
dc.publisherNorth Dakota State Universityen_US
dc.rightsNDSU Policy 190.6.2
dc.rights.urihttps://www.ndsu.edu/fileadmin/policy/190.pdf
dc.titleSliding Window Based Technique to Obtain Correlation Between Field Variablesen_US
dc.typeThesisen_US
ndsu.advisorDenton, Anne M.
ndsu.collegeEngineeringen_US
ndsu.degreeMaster of Science (MS)en_US
ndsu.departmentComputer Scienceen_US
ndsu.programComputer Scienceen_US

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