Zobrazeno 1 - 10
of 15
pro vyhledávání: '"V. Deneshkumar"'
Publikováno v:
Journal of Statistics & Management Systems. 26:317-330
COVID-19 pandemic is presenting a great need for understanding the symptoms of people affected by the disease. The main objective of this work is implementation of CART methodology to determine the symptoms associated with COVID-19 disease. The decis
Publikováno v:
Applied Ecology and Environmental Sciences. 10:717-722
Publikováno v:
European Journal of Mathematics and Statistics. 2:1-6
In day-to-day life, the price level fluctuations in the Consumer Price Index (CPI) goods and service. So, the retail consumers are affecting by that price level changes, who are on the demand side of the economy. The main objective of this work is to
Autor:
K. Senthamarai Kannan, Angela Tavares Paes, Rizwan Suliankatchi Abdulkader, Vijayakumar Koyilil, V. Deneshkumar, Tunny Sebastian
Publikováno v:
Communications in Statistics: Case Studies, Data Analysis and Applications. 8:68-80
Publikováno v:
Communications in Statistics: Case Studies, Data Analysis and Applications. 5:85-91
CD4 cell count test is used to monitor the immunological status of the immune system. We took an attempt to check the efficacy of a HIV treatment based on the progression of CD4 cell count ...
Akademický článek
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Publikováno v:
International Journal of Research in Medical Sciences. :3702-3708
Background: Knowledge of antibiotic sensitivity patterns in the critically ill would lead to better outcomes by refinement of empirical therapy. The aim of the study was to analyze the antibiotic sensitivity patterns of pathogens in the critically il
Publikováno v:
Journal of Statistics and Management Systems. 18:547-559
Artificial Neural Network (ANN) provides an attractive alternative tool for researchers for agricultural forecasting. The Multi Layer Feed Forward Neural Net (MLFFNN) is one of the most widely used neural nets. Here, the MLFFNN architecture is examin
Publikováno v:
International Journal of Computer Applications. 76:12-18
Time series data mining (TSDM) techniques explores large amount of time series data in search of interesting relationships among variables. The TSDM methods overcome limitations including stationarity and linearity requirements of traditional time se
Akademický článek
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