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

• المؤلفون الرئيسيون: Wang, Yaoli, Wang, Lipo, Yang, Fangjun, Di, Wenxia, Chang, Qing
• مؤلفون آخرون: School of Electrical and Electronic Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2021
• الموضوعات: Engineering::Electrical and electronic engineering; Direct Input-To-Output Connections; The Elman Neural Network
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/154501
• المؤسسة: 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...