A novel model by evolving partially connected neural network for stock price trend forecasting

By Pei-Chann Chang, Di-di Wang, Changle Zhou. 2012

126 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Management Science and Operations Research, Signal Processing

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. M. Ugur Gudelek
2. Michal Tkác
3. Robert Verner
4. A. Ozbayoglu
5. Song Wu
6. Hao Chen
7. S. Arda Boluk
8. Jinwen Sun

In Management Science and Operations Research

1. M. Ugur Gudelek
2. A. Ozbayoglu
3. S. Arda Boluk
4. Michal Tkác
5. Robert Verner
6. Song Wu
7. Hao Chen
8. Jinwen Sun

In Signal Processing

1. A. Ozbayoglu
2. S. Arda Boluk
3. M. Ugur Gudelek

Citations in the corpus

• Artificial neural networks in business: Two decades of research (2016, background): “Throughout the investigated period authors have applied artificial neural networks to various problems including credit scoring [161, 258, 259], financial analysis [52, 186], or stock performance prediction [89, 162, 166].”
• A Double-Layer Neural Network Framework for High-Frequency Forecasting (2017, background): “2013], partially connected NN [Chang et al. 2012], hybrid of non-linear ICA and NN [Dai et al.”
• A deep learning based stock trading model with 2-D CNN trend detection (2017, methodology): “In [12], a variation of ANN, which has tuned hyper-parameter optimized with an evolutionary algorithm, is studied.”