DLNM Explorer
Distributed Lag Non-Linear Modelling of Exogenous Shocks on Agricultural System A user-friendly platform to quantify how an external shock - such as geopolitical risk, weather or climate anomalies, or policy and price shocks - affects a time series of interest (trade, prices, production, arrivals) through non-linear and delayed (lagged) pathways.
Launch tool →Climate Anomaly
Climate Anomaly compares every month in your climate record with the normal for that same calendar month at that same place. It reports the departure as RAI, MRAI, SRAI, SSPI and SPI for rainfall, and as z-scores, deviations and percentage departures for rainfall and temperature. You choose the baseline period.
Launch tool →FuzzyML
Intuitionistic Fuzzy Machine Learning for Time Series Forecasting Forecast any time series with seven machine learning models that see the data through intuitionistic fuzzy sets . Each past value enters the model together with its degree of membership and non-membership in fuzzy clusters, so the model also learns from the uncertainty (hesitation) in the data.
Launch tool →Time Series Forecasting Website
Your comprehensive platform for crop yield forecasting and data analysis using cutting-edge AI models. Transform your agricultural data into actionable insights with deep learning, machine learning, and statistical time series models.
Launch tool →ARIMA-Informed LSTM
A forecasting model that embeds ARIMA's statistical structure - trend, autocorrelation and persistence - as prior knowledge inside an LSTM network.
Launch tool →GARCH-Guided LSTM
Combines GARCH conditional-variance modelling with an LSTM's nonlinear sequence learning, for improved volatility forecasting.
Launch tool →Rice Pest Early Warning System
Weather Based Pest Forecasting System under SREE PVF Project in Rice Using Statistical and ML Hybrid Approaches
Launch tool →ICAR-CIRB Buffalo Total Lactation Estimation System
A Machine Learning Approach to estimate milk yield
Launch tool →