Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations
Time series and dependent variables
Physica D
Time Series Analysis: Forecasting and Control
Time Series Analysis: Forecasting and Control
Neural Networks Approach to the Random Walk Dilemma of Financial Time Series
Applied Intelligence
Image Compression by Layered Quantum Neural Networks
Neural Processing Letters
Evolving neural networks through augmenting topologies
Evolutionary Computation
A multilayered feed-forward network based on qubit neuron model
Systems and Computers in Japan
Neural Computing and Applications
An Examination of Qubit Neural Network in Controlling an Inverted Pendulum
Neural Processing Letters
Nonlinear Time Series Analysis
Nonlinear Time Series Analysis
Finding the embedding dimension and variable dependencies in time series
Neural Computation
A New Intelligent System Methodology for Time Series Forecasting with Artificial Neural Networks
Neural Processing Letters
A Hybrid Intelligent Morphological Approach for Stock Market Forecasting
Neural Processing Letters
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
A class of hybrid morphological perceptrons with application in time series forecasting
Knowledge-Based Systems
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part I
Quantum-inspired evolutionary algorithm for a class of combinatorial optimization
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Evolutionary Computation
Combination of artificial neural-network forecasters for prediction of natural gas consumption
IEEE Transactions on Neural Networks
Tuning of the structure and parameters of a neural network using an improved genetic algorithm
IEEE Transactions on Neural Networks
A constructive algorithm for training cooperative neural network ensembles
IEEE Transactions on Neural Networks
Quarterly Time-Series Forecasting With Neural Networks
IEEE Transactions on Neural Networks
Neural modeling for time series: A statistical stepwise method for weight elimination
IEEE Transactions on Neural Networks
Hybrid method for the analysis of time series gene expression data
Knowledge-Based Systems
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In this work we present the robust automatic phase-adjustment (RAA) method to overcome the random walk dilemma for financial time series forecasting. It consists of a hybrid model composed of a qubit multilayer perceptron (QuMLP) with a quantum-inspired evolutionary algorithm (QIEA), which is able to evolve the complete QuMLP architecture and parameters, as well as searches for the best time lags to optimally describe financial phenomena. In the attempt to improve the QuMLP parameters supplied by QIEA, each individual of the QIEA population is further trained by the complex back-propagation (CBP) algorithm. Also, for each forecasting model generated, we use a phase fix procedure to adjust time phase distortions that appear in financial time series. Furthermore, an experimental analysis is conducted with the proposed method through six real world financial time series, and the obtained results are discussed and compared to results found with the best methods recently presented in the literature.