India is accounting for almost 20 percent of total milk production in the world and 70 percent of this share is coming from small, marginal farmers and landless people of the country residing in rural areas and this shows that dairy industry has an important role in social and economic development in India. Dairy is growing with a positive rate as per capita availability has reached to 375 (gms/day) in 2017-18 from 178 (gms/day) in 1990-91. In this study, time series data (2001-02 to 2015-16) on milk production and different milching species population of Chhattisgarh have been used to find out the suitable forecasting models for milk production and population of these mulching animals of Chhattisgarh. To meet the objective of study different Autoregressive Integrated Moving Average (ARIMA) models have been tried and among all ARIMA (0,2,0) model has been found more suitable for production of milk in India and Chhattisgarh both. Availability of milk is forecasted suitably by ARIMA (0,2,1) and ARIMA(0,1,1) for India and Chhattisgarh respectively. Similarly different ARIMA models have been fitted for population of different species animals. By this study milk production is expected to reach 219.73 MMT and 1.599 MMT by 2022-23 in India and Chhattisgarh respectively.
Due to the impact of Corona virus (COVID-19) pandemic that exists today, all countries, national and international organizations are in a continuous effort to find efficient and accurate statistical models for forecasting the future pattern of COVID infection. Accurate forecasting should help governments to take decisive decisions to master the pandemic spread. In this article, we explored the COVID-19 database of India between 17th March to 1st July 2020, then we estimated two nonlinear time series models: Artificial Neural Network (ANN) and Fuzzy Time Series (FTS) by comparing them with ARIMA model. In terms of model adequacy, the FTS model out performs the ANN for the new cases and new deaths time series in India. We observed a short-term virus spread trend according to three forecasting models.Such findings help in more efficient preparation for the Indian health system.
A large proportion of the Indian population is vegetarian and pulses are important sources of protein in the daily diet .In this paper an attempt has been made to summarize the overall nature of area, production and productivity of mung in India. By and large there has been considerable expansion in area, production and productivity of mung in all the states under study including whole India during the study period. Among the states under study, the maximum annual growth in area (9.75%) and production (14.55%) of mung was observed in Rajasthan. Bihar stands first in productivity of mung among the states under study. Rajasthan, Karnataka and Andhra Pradesh have fails to reach national average per hectare production of 367.37 kg/ha. In this paper an attempt has been made to summarize these measures along with some new measures with an objective to study the yield sustainability of particular crop over the growing regions and compare across the states/regions. Sustainability in yield of mung in different states along with whole India has been measured with the help of existing and proposed measures of sustainability indices. Whole India is showing higher sustainability in yield of mung as per the two existing and proposed methods. According to all the indices including developed two methods Rajasthan is having comparatively lower sustainability to produce mung among the states under study. Results of existing measures and proposed measure are almost in conformity with each other. From the forecasted value, it can be said that, mung productivity of India would increase to 408.84 kg/ha in 2022 as compared to 2012. In Mung, area, production and productivity Rajasthan would be leading state of India in 2022.This projection would be helpful for policy implication and planning.
The current event in the world is corona-virus; the spread of this virus can put all countries in situation of incapacity of how manage and face. This article focused on the class of ARIMA models and Fuzzy Time Series. The techniques are applied to trajectory Corona virus on three African countries: Algeria, Egypt and South Africa over the period (2020-02-15 /2020-03-19). Although the hyper stochastic of this pandemic, it is seen that ARIMA models fits well the trajectory of Covid-19. We predict a continuous trend of virus spreading in next days, a fact that alert the governments of theses countries and the whole African countries for further strengthen prevention and intervention policies to combat this epidemic
There are no studies and only limited data that compare the difference in mortality between twins and singletons in the Arab world. We studied the survival of 306,966 children, including 9,280 twins, over the period 1970–2013 in six Arab countries (Algeria, Egypt, Iraq, Mauritania, Sudan and Tunisia) based on the Multiple Indicator Cluster Survey (MICS) database. With the use of relative survival models, we estimated the mortality of twins relative to singletons by including socioeconomic and demographic variables. This study confirms the results of previous studies on the excess risk of death of twins compared to singletons. There is evidence that excess mortality decreases with follow-up; in addition, male twins have a higher risk of death compared to females for all countries except Tunisia. Wealth index and education levels of women are factors that influence the risk of mortality. It is recommended that these findings are considered when performing future health and population strategies in these Arab countries.
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