Advantages of direct input-to-output connections in neural networks : the Elman network for stock index forecasting

• Main Authors: Wang, Yaoli, Wang, Lipo, Yang, Fangjun, Di, Wenxia, Chang, Qing
• Other Authors: School of Electrical and Electronic Engineering
• Format: Article
• Language: English
• Published: 2021
• Subjects: Engineering::Electrical and electronic engineering; Direct Input-To-Output Connections; The Elman Neural Network
• Online Access: https://hdl.handle.net/10356/154501
• Institution: Nanyang Technological University

The Elman neural network (ElmanNN) is well-known for its capability of processing dynamic information, which has led to successful applications in stock forecasting. In this paper, we introduce direct input-to-output connections (DIOCs) into the ElmanNN and show that the proposed Elman neural networ...