Hidden Markov guided Deep Learning models for forecasting highly volatile agricultural commodity prices

Author:

Avinash G.,Ramasubramanian V.,Ray Mrinmoy,Paul Ranjit Kumar,Godara Samarth,Nayak G.H. Harish,Kumar Rajeev RanjanORCID,Manjunatha B.ORCID,Dahiya Shashi,Iquebal Mir AsifORCID

Publisher

Elsevier BV

Reference68 articles.

1. Seasonal forecasting of agricultural commodity price using a hybrid STL and ELM method: Evidence from the vegetable market in China;Xiong;Neurocomputing,2018

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3. Tomato, onion and potato (TOP) value chains,2022

4. Predicting stock price trend using MACD optimized by historical volatility;Wang;Math. Probl. Eng.,2018

5. Forecasting price movements using technical indicators: Investigating the impact of varying input window length;Shynkevich;Neurocomputing,2017

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