Financial forecasting using ANFIS networks with Quantum-behaved Particle Swarm Optimization

By Ahmad Bagheri, Hamed Mohammadi Peyhani, Mohsen Akbari. 2014

191 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Economics and Econometrics, Management Science and Operations Research

How researchers see this paper

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

In Artificial Intelligence

1. Ebubekir Kaya
2. Mohammed Abdulaziz Aide Al-qaness
3. Dervis Karaboga
4. Hong Fan
5. Mohamed Abd El Aziz
6. Ahmed A. Ewees
7. Bahriye Akay
8. Pinar Çivicioglu

In Economics and Econometrics

1. Dervis Karaboga
2. Ebubekir Kaya
3. Weiwei Jiang

In Management Science and Operations Research

1. Dervis Karaboga
2. Ebubekir Kaya
3. Weiwei Jiang

Citations in the corpus

• Stock Market Prediction on High-Frequency Data Using Generative Adversarial Nets (2018, background): “With the rapid growth of Internet and computing technologies, the frequency for performing operations on the stock market had increased to fractions of seconds [4, 5].”
• Optimization Method for Forecasting Confirmed Cases of COVID-19 in China (2020, methodology): “The SI methods include the particle swarm optimization (PSO) [31,32], social-spider optimization [33], sine-cosine algorithm (SCA) [34], and multi-verse optimizer (MVO) [35].”
• Adaptive network based fuzzy inference system (ANFIS) training approaches: a comprehensive survey (2018, methodology): “Apart from these, GA/SVD based hybrid training approaches are applied in the different studies (Bagheri et al. 2009, 2005; Jamali et al. 2011;Khoshbin et al. 2016;Marzbanrad and Jamali 2009; Salmalian and Soleimani 2011). Rastegar et al. (2005) adjusted the parameters of membership functions by usin”