Article citationsMore>>

Roman, U.C., Patela, P.L. and Poreya, P.D. (2012) Prediction of Missing Rainfall Data Using Conventional and Artificial Neural Network Techniques. ISH Journal of Hydraulic Engineering, 18, 224-231.
http://dx.doi.org/10.1080/09715010.2012.721660

has been cited by the following article:

• TITLE: MissRF: A Visual Basic Application in MS Excel to Find out Missing Rainfall Data and Related Analysis

  AUTHORS: Pradeep Kumar Mohanty, Dwitikrishna Panigrahi, Milu Acharya

  KEYWORDS: MissRF; Normal Ratio Method; Visual Basic; MS Excel

  JOURNAL NAME: Intelligent Information Management, Vol.6 No.2, March 20, 2014

  ABSTRACT: Hydrological analyses are often encountered with many missing periods of rainfall while designing developmental action plans for inaccessible and disadvantageous area. Visual basic based application software (to run in MS Excel) was developed to calculate and autofilled the missing rainfall data using widely followed Normal Ratio Method. The operational details of the software are described in the paper.