SSRN Author: Bhawna MallickBhawna Mallick SSRN Content
http://www.ssrn.com/author=2643549
http://www.ssrn.com/rss/en-usSat, 01 Jul 2017 01:41:20 GMTeditor@ssrn.com (Editor)Sat, 01 Jul 2017 01:41:20 GMTwebmaster@ssrn.com (WebMaster)SSRN RSS Generator 1.0New: A Study of Time Series Models ARIMA and ETSThe aim of the study is to introduce some approach which might help in improving daily temperature of data. Weather is a natural a phenomenon for which forecasting is a great challenge today. Weather parameters such as Rainfall, Relative Humidity , Wind Speed, Air Temperature are highly non-linear and complex phenomena, which include mathematical simulation and modeling for its correct forecasting. Weather Forecasting is use to simplify the purpose of knowledge and tools that are used for the state of atmosphere at a given place. The prediction is becoming more complicated due to changing weather condition. There are different software and types are available for Time Series forecasting. Our aim is to analyze the parameters and do the comparison of some strategies in predicting these temperatures. Here we tend to analyze the data of given parameters and notice the prediction for few period using the strategy of Autoregressive Integrated Moving Average (ARIMA) and Exponential ...
http://www.ssrn.com/abstract=2898968
http://www.ssrn.com/1604473.htmlFri, 30 Jun 2017 08:52:52 GMTUpdate: A Study of Time Series Models ARIMA and ETSThe aim of the study is to introduce some approach which might help in improving daily temperature of data. Weather is a natural a phenomenon for which forecasting is a great challenge today. Weather parameters such as Rainfall, Relative Humidity , Wind Speed, Air Temperature are highly non-linear and complex phenomena, which include mathematical simulation and modeling for its correct forecasting. Weather Forecasting is use to simplify the purpose of knowledge and tools that are used for the state of atmosphere at a given place. The prediction is becoming more complicated due to changing weather condition. There are different software and types are available for Time Series forecasting. Our aim is to analyze the parameters and do the comparison of some strategies in predicting these temperatures. Here we tend to analyze the data of given parameters and notice the prediction for few period using the strategy of Autoregressive Integrated Moving Average (ARIMA) and Exponential ...<br/><i>The Paper was removed</i>
http://www.ssrn.com/abstract=2898968
http://www.ssrn.com/1564682.htmlWed, 08 Feb 2017 06:56:32 GMTNew: A Study of Time Series Models ARIMA and ETSThe aim of the study is to introduce some approach which might help in improving daily temperature of data. Weather is a natural a phenomenon for which forecasting is a great challenge today. Weather parameters such as Rainfall, Relative Humidity , Wind Speed , Air Temperature are highly non-linear and complex phenomena, which include mathematical simulation and modeling for its correct forecasting. Weather Forecasting is use to simplify the purpose of knowledge and tools that are used for the state of atmosphere at a given place. The prediction is becoming more complicated due to changing weather condition. There are different software and types are available for Time Series forecasting. Our aim is to analyze the parameters and do the comparison of some strategies in predicting these temperatures. Here we tend to analyze the data of given parameters and notice the prediction for few period using the strategy of Autoregressive Integrated Moving Average (ARIMA) and Exponential ...
http://www.ssrn.com/abstract=2898968
http://www.ssrn.com/1559080.htmlWed, 18 Jan 2017 12:58:40 GMT