A Dendritic Neuron Model Optimized by Meta-Heuristics with a Power-Law-Distributed Population Interaction Network for Financial Time-Series Forecasting

Yuxin Zhang, Yifei Yang, Xiaosi Li, Zijing Yuan, Yuki Todo and Haichuan Yang ()
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Yuxin Zhang: Department of Engineering, Wesoft Company Ltd., Kawasaki-shi 210-0024, Japan
Yifei Yang: Faculty of Engineering, University of Toyama, Toyama-shi 930-8555, Japan
Xiaosi Li: Department of Engineering, Wesoft Company Ltd., Kawasaki-shi 210-0024, Japan
Zijing Yuan: Faculty of Engineering, University of Toyama, Toyama-shi 930-8555, Japan
Yuki Todo: Faculty of Electrical and Computer Engineering, Kanazawa University, Kanazawa-shi 920-1192, Japan
Haichuan Yang: Department of Engineering, Wesoft Company Ltd., Kawasaki-shi 210-0024, Japan

Mathematics, 2023, vol. 11, issue 5, 1-20

Abstract: The famous McCulloch–Pitts neuron model has been criticized for being overly simplistic in the long term. At the same time, the dendritic neuron model (DNM) has been shown to be effective in prediction problems, and it accounts for the nonlinear information-processing capacity of synapses and dendrites. Furthermore, since the classical error back-propagation (BP) algorithm typically experiences problems caused by the overabundance of saddle points and local minima traps, an efficient learning approach for DNMs remains desirable but difficult to implement. In addition to BP, the mainstream DNM-optimization methods include meta-heuristic algorithms (MHAs). However, over the decades, MHAs have developed a large number of different algorithms. How to screen suitable MHAs for optimizing DNMs has become a hot and challenging area of research. In this study, we classify MHAs into different clusters with different population interaction networks (PINs). The performance of DNMs optimized by different clusters of MHAs is tested in the financial time-series-forecasting task. According to the experimental results, the DNM optimized by MHAs with power-law-distributed PINs outperforms the DNM trained based on the BP algorithm.

Keywords: dendritic neuron model; meta-heuristic algorithms; financial time-series forecasting; population interaction networks (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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