Comparative study between Differential Evolution and Particle Swarm Optimization algorithms in training of feed-forward neural network for stock price prediction

By Mustafa E. Abdual-Salam, Hatem Mohamed Abdul-kader, W. F. Abd-El-Wahed. 2010

41 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Pradipta Kishore Dash
2. Ranjeeta Bisoi
3. Ajit Kumar Rout
4. Rajashree Dash
5. Omer Berat Sezer

Citations in the corpus

• Forecasting financial time series using a low complexity recurrent neural network and evolutionary learning approach (2015, methodology): “…Swarm Optimization (PSO) in the training and testing of feed-forward neural network for the prediction of daily stock market prices has shown that DE provides a faster convergence speed and better accuracy than PSO algorithm in the prediction of fluctuated time series (Abdual-Salam et al., 2010).”