Dendritic Neuron Model Trained by Biogeography-Based Optimization for Crude Oil Price Forecasting

Shi Wang, Daiki Sugiyama, Jian Sun, Lin Yang, Shangce Gao

研究成果: 書籍の章/レポート/会議録会議への寄与査読

14 被引用数 (Scopus)

抄録

Recent research reveals that single neuron with flexible dendritic plasticity can perform computation and information processing. Several dendritic neuron models have been proposed and achieving great success in various applications. All previous models use error back-propagation (BP) training method to adjust weights and thresholds in the model. Due to the inherent local search properties of BP, their performance usually suffers from the local optima problem. In this paper, we propose a biogeography-based optimization method to train the dendritic neuron model. Experiment is conducted for crude oil price forecasting and the results suggest that the proposed method can perform very well in comparison with the traditional multiple-layered perceptron.

本文言語英語
ホスト出版物のタイトルProceedings - 2018 10th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2018
出版社Institute of Electrical and Electronics Engineers Inc.
ページ36-40
ページ数5
ISBN(電子版)9781538658369
DOI
出版ステータス出版済み - 2018/11/09
イベント10th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2018 - Hangzhou, 中国
継続期間: 2018/08/252018/08/26

出版物シリーズ

名前Proceedings - 2018 10th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2018
1

学会

学会10th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2018
国/地域中国
CityHangzhou
Period2018/08/252018/08/26

ASJC Scopus 主題領域

  • 人工知能
  • コンピュータ ビジョンおよびパターン認識
  • 人間とコンピュータの相互作用
  • 計算数学
  • 制御と最適化
  • コンピュータ サイエンスの応用

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