English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Weather forecasting is an important issue in meteorology and scientific research in this research, the Seasonal Auto Regressive Integrated Moving Average (ARIMA) model, which is based on Box-Jenkins method, was adopted to build the forecasting model. The Monthly Rainfall data for Balodabazar, Bemetara, Raipur city for the period (Jan. 1968 to Dec. 2018) was used. The autocorrelation and partial autocorrelation functions for time series data from years 1968 to 2018 were used to identify the most appropriate orders of the ARIMA models. To calculate the model's accuracy and compare among them, statistical criteria such as RMSE and R2 were used. The model Balodabazar (1,0,1) (1,1,1), Bemetara (0,0,2) (0,1,1), Raipur (1,0,1) (0,1,1) gave the most accurate results and used to forecast the monthly rainfall for the period (2019 to 2025) for study regions. This long term prediction will help decision makers in efficient scheduling of urban planning, and rainwater harvesting and crop management.

Time series ARIMA model to forecast monthly precipitation for Balodabazar, Bemetara and Raipur (Chhattisgarh)