Projects

AI Forecasting Tool

AI forecasting tool based on R Shiny architecture, where you can upload your data, edit your data & visualize, select desired model, predict & forecast and finally extract. Also, it let you discuss on multiple topics with AI.

ML Forecasting on EV Population

ML based forecasting of EV demand for next 5 years.

India's Financial Growth - Streamlit

This app is based on Streamlit. This app visualizes important KPI's of financial growth of Indian economy. The Data is available at Database of Indian Economy.

Analysis of WPI Time Series Data

This study models and forecasts the Wholesale Price Index (WPI) from April 1994 to January 2020, addressing challenges due to varying base years by approximating all data to the 2012 base year using backward regression. Both additive and multiplicative models were considered by analyzing the original data and its logarithm. The best-fitting model, selected based on the lowest Akaike Information Criterion (AIC), was used to forecast WPI from February to October 2020. Additionally, time series outliers and structural breaks were analyzed, and a model based on the last structural break was used to produce forecasts, which were then compared to those of the initial model.

ANALYSIS OF INDEX OF INDUSTRIAL PRODUCTION OF INDIA (IIP)

Here the data for Index of Industrial Production of India (IIP) available from April 1993 to March 2019. Since, here the data was available for different base periods, we transformed the whole data to the same base period. Next, we had studied the behavior of IIP (e.g. trend, seasonal fluctuations, pattern in stationary part etc.) and we tried to fit 4 different models to both original series & logarithmic series and choose the best models for each series based on minimum Akaike’s Information Criterion (AIC). Next we forecasted based on these best fitted models and studied further for presence of structural breaks and outliers.

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