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A New Approach to Multiple Time Series Prediction Using MIMO Fuzzy Aggregation Models with Modular Neural Networks
16 references·1 citing·39 second hop
A New Approach to Multiple Time Series Prediction Using MIMO Fuzzy Aggregation Models with Modular Neural Networks (2019)A New Approach to Multiple Time Series Pr…The Aggregation Operators Based on Archimedean t-Conorm and t-Norm for Single-Valued Neutrosophic Numbers and their Application to Decision Making (2016)The Aggregation Operators Bas…Recurrent neural network and a hybrid model for prediction of stock returns (2014)Recurrent neural network and …Particle swarm optimization of ensemble neural networks with fuzzy aggregation for time series prediction of the Mexican Stock Exchange (2014)Particle swarm optimization o…Hesitant fuzzy Hamacher aggregation operators for multicriteria decision making (2014)Hesitant fuzzy Hamacher aggre…Hesitant fuzzy Hamacher aggregation operators and their application to multiple attribute decision making (2014)Hesitant fuzzy Hamacher aggre…Some Hamacher Aggregation Operators Based on the Interval-Valued Intuitionistic Fuzzy Numbers and Their Application to Group Decision Making (2013)Some Hamacher Aggregation Ope…A review and comparison of strategies for multi-step ahead time series forecasting based on the NN5 forecasting competition (2012)A review and comparison of st…A new approach for time series prediction using ensembles of ANFIS models (2011)A new approach for time serie…Multiple-output modeling for multi-step-ahead time series forecasting (2010)Multiple-output modeling for …Long-term prediction of time series by combining direct and MIMO strategies (2009)Long-term prediction of time …Aggregation Functions: A Guide for Practitioners (2007)Aggregation Functions: A Guid…Forecasting the behavior of multivariate time series using neural networks (1992)Forecasting the behavior of m…On ordered weighted averaging aggregation operators in multicriteria decisionmaking (1988)On ordered weighted averaging…Time Series Analysis: Forecasting and Control. (1978)Time Series Analysis: Forecas…Time Series Analysis: Forecasting and Control (1977)Time Series Analysis: Forecas…Time Series Analysis Forecasting and Control. (1971)Time Series Analysis Forecast…Interval Forecasting of Financial Time Series by Accelerated Particle Swarm-Optimized Multi-Output Machine Learning System (2020)Interval Forecasting of Finan…Time series prediction: Forecasting the future and understanding the past (1994)Beyond one-step-ahead forecasting: Evaluation of alternative multi-step-ahead forecasting models for crude oil prices (2013)Multi-step-ahead time series prediction using multiple-output support vector regression (2013)A Bias and Variance Analysis for Multistep-Ahead Time Series Forecasting (2015)The Combination of Forecasts (1969)Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Forecasting with artificial neural networks: (1998)Machine Learning Strategies for Time Series Forecasting (2013)Time series forecasting using artificial neural networks methodologies: A systematic review (2018)An optimized model using LSTM network for demand forecasting (2020)Time Series Analysis, Forecasting and Control. (1971)Time series forecasting using a hybrid ARIMA and neural network model (2003)Forecasting daily stock market return using dimensionality reduction (2016)Stock Price Prediction via Discovering Multi-Frequency Trading Patterns (2017)Stock Market Analysis: A Review and Taxonomy of Prediction Techniques (2019)Fuzzy sets (1965)Intuitionistic fuzzy sets (1986)Fuzzy sets (1996)Generalized Pythagorean Fuzzy Geometric Aggregation Operators Using Einsteint-Norm andt-Conorm for Multicriteria Decision-Making Process (2016)Someq-Rung Orthopai Fuzzy Bonferroni Mean Operators and Their Application to Multi-Attribute Group Decision Making (2017)Multiple-Attribute Decision-Making Based on Archimedean Bonferroni Operators of q -Rung Orthopair Fuzzy Numbers (2018)Forecasting Economic Time Series (1979)A comparison of artificial neural network and time series models for forecasting commodity prices (1996)How effective are neural networks at forecasting and prediction? A review and evaluation (1998)Conditional Time Series Forecasting with Convolutional Neural Networks (2017)A Consensus Model to Detect and Manage Noncooperative Behaviors in Large-Scale Group Decision Making (2013)Pythagorean Membership Grades, Complex Numbers, and Decision Making (2013)Fermatean fuzzy weighted averaging/geometric operators and its application in multi-criteria decision-making methods (2019)A 2-tuple fuzzy linguistic representation model for computing with words (2000)Intuitionistic Fuzzy Aggregation Operators (2007)Pythagorean Membership Grades in Multicriteria Decision Making (2013)Distribution of the Estimators for Autoregressive Time Series with a Unit Root (1979)Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root (1981)Generalized autoregressive conditional heteroskedasticity (1986)Principles of forecasting : a handbook for researchers and practitioners (2001)25 years of time series forecasting (2006)The politics of attention: how government prioritizes problems (2006)Some recent development in a concept of causality (1988)Unit root tests in panel data: asymptotic and finite-sample properties (2002)
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References

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  • 1971Time Series Analysis Forecasting and Control.6,714 cited
  • 1978Time Series Analysis: Forecasting and Control.5,299 cited
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  • 2012A review and comparison of strategies for multi-step ahead time series forecasting based on the NN5 forecasting competition745 cited
  • 1992Forecasting the behavior of multivariate time series using neural networks517 cited
  • 2014Recurrent neural network and a hybrid model for prediction of stock returns506 cited
  • 2013Some Hamacher Aggregation Operators Based on the Interval-Valued Intuitionistic Fuzzy Numbers and Their Application to Group Decision Making404 cited
  • 2010Multiple-output modeling for multi-step-ahead time series forecasting254 cited
  • 2011A new approach for time series prediction using ensembles of ANFIS models178 cited
  • 2014Particle swarm optimization of ensemble neural networks with fuzzy aggregation for time series prediction of the Mexican Stock Exchange135 cited
  • 2016The Aggregation Operators Based on Archimedean t-Conorm and t-Norm for Single-Valued Neutrosophic Numbers and their Application to Decision Making114 cited
  • 2014

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Hesitant fuzzy Hamacher aggregation operators for multicriteria decision making
112 cited
  • 2014Hesitant fuzzy Hamacher aggregation operators and their application to multiple attribute decision making96 cited
  • 2009Long-term prediction of time series by combining direct and MIMO strategies81 cited
  • Cited by

    • 2020Interval Forecasting of Financial Time Series by Accelerated Particle Swarm-Optimized Multi-Output Machine Learning System41 cited