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This work introduces a quantum-inspired intelligent hybrid (QIIH) method for stock market forecasting. It performs a quantum-inspired evolutionary search for the minimum necessary dimension (time lags) embedded in the problem for determining the characteristic phase space that generates the financial time series phenomenon. The proposed QIIH method consists of a quantum-inspired intelligent hybrid...
This paper proposes the Morphological-Rank-Linear Time-lag Added Evolutionary Forecasting (MRLTAEF) method for financial time series forecasting, which performs an evolutionary search for the minimum number of relevant time lags necessary to efficiently represent complex time series. It consists of an intelligent hybrid model composed of a Morphological-Rank-Linear (MRL) filter combined with a Modified...
This paper presents an study of a new hybrid method based on the greedy randomized adaptive search procedure(GRASP) and evolutionary strategies(ES) concepts for tuning the structure and parameters of an artificial neural network (ANN). It consists of an ANN trained and adjusted by this new method, which searches for the minimum number of (and their specific) relevant time lags for a correct time series...
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