Abstract
In this paper, a novel Legendre neural network model is proposed, namely additive Legendre neural network (ALNN). A new hybrid evolutionary method besed on binary particle swarm optimization (BPSO) algorithm and firefly algorithm is proposed to optimize the structure and parameters of ALNN model. Shanghai stock exchange composite index is used to evaluate the performance of ALNN. Results reveal that ALNN performs better than LNN model.
Highlights
Artificial neural networks (ANNs) are powerful mathematical methods that can be used to learn complex linear and non-linear continuous functions, and have been successfully applied to many areas in the past decades [1]
Due to that traditional neural network has some disadvantages such as low efficiency, long learning time and easy to fall into the local minimum solution, Legendre neural network (LNN) was proposed
Shanghai stock exchange composite index is used to evaluate the performance of additive Legendre neural network (ALNN)
Summary
Artificial neural networks (ANNs) are powerful mathematical methods that can be used to learn complex linear and non-linear continuous functions, and have been successfully applied to many areas in the past decades [1]. Patra et al proposed a Legendre neural network model for equalization of nonlinear communication channels with 4-QAM signal constellation [2]. Patra et al propose a computationally efficient Legendre neural network for identification of nonlinear dynamic systems [3]. Pei et al forecastedand investigated the stock prices of the financial model by an improved Legendre neural network–Legendre neural network with random time strength function [4]. To reduce the optimization complexity and improve efficiency, in this paper, a novel Legendre neural network model is proposed, namely additive Legendre neural network (ALNN). Binary particle swarm optimization (BPSO) algorithm is proposed to select proper input Legendre polynomials in order to construct proper structure. Shanghai stock exchange composite index is used to evaluate the performance of ALNN
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
