Please use this identifier to cite or link to this item: http://nopr.niscair.res.in/handle/123456789/55517
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dc.contributor.authorSundar, M Shyam-
dc.contributor.authorNatarajan, N-
dc.contributor.authorVasudevan, M-
dc.date.accessioned2020-10-21T05:08:36Z-
dc.date.available2020-10-21T05:08:36Z-
dc.date.issued2020-09-
dc.identifier.issn2582-6727 (Online); 2582-6506 (Print)-
dc.identifier.urihttp://nopr.niscair.res.in/handle/123456789/55517-
dc.description1587-1592en_US
dc.description.abstractEstimation of demographic variations for societal or infrastructural development policies requires accurate prediction of futuristic population for a given locality. Economic viability as well as sustainability at large, of the engineering designs in urban development activities depend on the variations in projected populations for a given design period. Considering the uncertainties in existing calculation practices to derive an average value, present study offers a computationally efficient program capable of forecasting the future population based on the existing past population data using three well-known population forecasting methods, namely, arithmetic increase method, geometric increase method and incremental increase method. The results proved that when compared to manual calculation, the predictions were accurate, precise and computationally efficient. This user-friendly tool will be highly beneficial for various service providers where population forecasting is inevitable. The robustness of the computer code has been demonstrated using six decades of real time census data of Coimbatore city.en_US
dc.language.isoen_USen_US
dc.publisherNISCAIR-CSIR, Indiaen_US
dc.rights CC Attribution-Noncommercial-No Derivative Works 2.5 Indiaen_US
dc.sourceIJMS Vol.49(09) [September 2020]en_US
dc.subjectAveraging methodsen_US
dc.subjectComputation efficiencyen_US
dc.subjectComputer modelen_US
dc.subjectPopulation forecastingen_US
dc.subjectWater demanden_US
dc.titleA handy tool for forecasting population to aid estimation of water demanden_US
dc.typeArticleen_US
Appears in Collections:IJMS Vol.49(09) [September 2020]

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