Predictions of soil movements using persistence, auto-regression, and neural network models: a case-study in Mandi, India

2022 ◽  
Vol 7 (1) ◽  
pp. 1
Author(s):  
Varun Dutt ◽  
Priyanka . ◽  
Aakash Maurya ◽  
Mohit Kumar ◽  
Pratik Chaturvedi ◽  
...  
Author(s):  
Joarder Kamruzzaman ◽  
Ruhul A. Sarker ◽  
Rezaul K. Begg

In today’s global market economy, currency exchange rates play a vital role in national economy of the trading nations. In this chapter, we present an overview of neural network-based forecasting models for foreign currency exchange (forex) rates. To demonstrate the suitability of neural network in forex forecasting, a case study on the forex rates of six different currencies against the Australian dollar is presented. We used three different learning algorithms in this case study, and a comparison based on several performance metrics and trading profitability is provided. Future research direction for enhancement of neural network models is also discussed.


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