Reference Vector-Based Multiobjective Clustering Ensemble Approach for Time Series Forecasting

This paper integrates the maximal overlap discrete wavelet transform (MODWT), long and short-term memory neural network (EA-LSTM) of evolutionary attention mechanism and reference vector based clustering algorithm (RVMOC) and proposes a new prediction method of the stock market return rate, which is...

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Veröffentlicht in:	Computational economics Jg. 64; H. 1; S. 181 - 210
Hauptverfasser:	Liu, Chao, Gao, Fengfeng, Zhang, Mengwan, Li, Yuanrui, Qian, Cun
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.07.2024 Springer Springer Nature B.V
Schlagworte:	Algorithms Behavioral/Experimental Economics Clustering Computer Appl. in Social and Behavioral Sciences Decomposition Discrete Wavelet Transform Economic Theory/Quantitative Economics/Mathematical Methods Economics Economics and Finance Evolutionary algorithms Forecasting Forecasts and trends Learning Math Applications in Computer Science Neural networks Operations Research/Decision Theory Prediction models Predictions Securities markets Short term memory Stock exchanges Stock markets Time series Wavelet transforms Weighting Reference vector-based multi-objective clustering (RVMOC) Evolutionary algorithm (EA) Maximal overlap discrete wavelet transform (MODWT) Attention-based long short-term memory (A-LSTM)
ISSN:	0927-7099, 1572-9974
Online-Zugang:	Volltext
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