A PSO Boosted Ensemble of Extreme Learning Machines for Time Series Forecasting
暂无分享,去创建一个
[1] Guoqiang Peter Zhang,et al. Time series forecasting using a hybrid ARIMA and neural network model , 2003, Neurocomputing.
[2] Nasser M. Nasrabadi,et al. Pattern Recognition and Machine Learning , 2006, Technometrics.
[3] S. A. Jafari,et al. Robust combining methods in committee neural networks , 2011, 2011 IEEE Symposium on Computers & Informatics.
[4] Thomas G. Dietterich. Multiple Classifier Systems , 2000, Lecture Notes in Computer Science.
[5] Lars Kai Hansen,et al. Neural Network Ensembles , 1990, IEEE Trans. Pattern Anal. Mach. Intell..
[6] Wei Fan,et al. An adaptive ensemble model of extreme learning machine for time series prediction , 2015, 2015 12th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP).
[7] Maciej Ogorzalek,et al. Time series prediction with ensemble models applied to the CATS benchmark , 2007, Neurocomputing.
[8] Chee Kheong Siew,et al. Extreme learning machine: Theory and applications , 2006, Neurocomputing.
[9] Oscar Castillo,et al. Particle Swarm Optimization of the Fuzzy Integrators for Time Series Prediction Using Ensemble of IT2FNN Architectures , 2017, Nature-Inspired Design of Hybrid Intelligent Systems.
[10] M. Ogorzalek,et al. Time series prediction with ensemble models , 2004, 2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541).
[11] A. S. Weigend,et al. Results of the time series prediction competition at the Santa Fe Institute , 1993, IEEE International Conference on Neural Networks.
[12] David W. Opitz,et al. Actively Searching for an E(cid:11)ective Neural-Network Ensemble , 1996 .
[13] Ram Gopal Raj,et al. The artificial neural network for solar radiation prediction and designing solar systems: a systematic literature review , 2015 .
[14] Shuichi Kurogi,et al. Time series prediction of the CATS benchmark using Fourier bandpass filters and competitive associative nets , 2007, Neurocomputing.
[15] Milton S. Boyd,et al. Designing a neural network for forecasting financial and economic time series , 1996, Neurocomputing.
[16] Oscar Castillo,et al. A new approach for time series prediction using ensembles of ANFIS models with interval type-2 and type-1 fuzzy integrators , 2013, 2013 IEEE Conference on Computational Intelligence for Financial Engineering & Economics (CIFEr).
[17] Saso Dzeroski,et al. Ensembles of Multi-Objective Decision Trees , 2007, ECML.
[18] Andries Petrus Engelbrecht,et al. A study of particle swarm optimization particle trajectories , 2006, Inf. Sci..
[19] Voratas Kachitvichyanukul,et al. Comparison of Three Evolutionary Algorithms: GA, PSO, and DE , 2012 .
[20] R. Eberhart,et al. Comparing inertia weights and constriction factors in particle swarm optimization , 2000, Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512).
[21] Thomas Martinetz,et al. 'Neural-gas' network for vector quantization and its application to time-series prediction , 1993, IEEE Trans. Neural Networks.
[22] Eloy Irigoyen,et al. Gas Consumption Prediction Based on Artificial Neural Networks for Residential Sectors , 2017, SOCO-CISIS-ICEUTE.
[23] Zhang-Quan Shen,et al. Optimizing Weights by Genetic Algorithm for Neural Network Ensemble , 2004, ISNN.