[PDF] Top 20 Identification environment and robust forecasting for nonlinear time series
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Identification environment and robust forecasting for nonlinear time series
... Key words, nonlinear time series, bilinear, Lagrange multiplier test, neural network, forecasting, robust... 38 BERLIN WU tests can provide a well-designed procedure f[r] ... See full document
17
Forecasting nonlinear time series of energy consumption using a hybrid dynamic model
... a forecasting model may be unreliable when historical observations of energy consumption vary ...accurate and reliable than other fore- casting ...utilities for accurate ... See full document
6
The Use of Kernel Set and Sample Memberships in the Identification of Nonlinear Time Series
... patients and survival patients for the first four days of ...data for each patient is measured with 30 ...features and identify nonlinear time series for the ICU ... See full document
10
A Novel Modified Particle Swarm Optimization for Forecasting Financial Time Series
... Nursing and Management College, Taipei City, Taiwan ...Abstract—Time series has been widely applied in the real world; traditional methods can hardly solve the dynamic environment issue ... See full document
5
Forecasting time series using a methodology based on autoregressive integrated moving average and genetic programming
... hybrid forecasting model, which combines ARIMA to model the linear component (L t ) of a time ser- ies and the GP to model the nonlinear component (N t ), to improve the accuracy of ARIMA ... See full document
7
Forecasting Time-Varying Covariance with a Robust Bayesian Threshold Model
... index and S&P500 index futures for the period 3 January 1995 to 31 October ...size for each stock market is 3221. Both spot and futures prices are collected from TICK ...DATA. For ... See full document
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Time Series Forecasting by Combining the Radial Basis Function Network and the Self-organizing Map
... important for many real-time series, because one may not know what the underlying data-generating process ...inputs and the outputs for any forecasting model, then the accurate ... See full document
13
Robust cerebellar model articulation controller design for unknown nonlinear systems
... theory and traditional feedback ...dynamics and its environment; the objection for the real-time application is unrealizable for the unknown ... See full document
5
A general invariance principle for nonlinear time-varying systems and its applications
... sensors and actuators, displacement feedback, large space structure, robust ...sensors and actuators can be stabilized robustly against any uncertainty in mass, damping, and stiff- ness ... See full document
5
A novel nonlinear forecasting model for output of bike industry by Grey model and Taguchi-differential evolution algorithm
... bike, nonlinear time series ...health and sustainability has changed the living style of people all around the ...leisure and the transportation value, a growing numbers of people ... See full document
5
Forecasting energy consumption in Taiwan using hybrid nonlinear models
... season for each year generally occurs in June or July, because energy use is greatest in the ...Winters and WARCH models for electricity The electricity consumption series z t , given in ... See full document
9
Auto-configuring radial basis function networks for chaotic time series and flood forecasting
... E-mail: changfj@ntu.edu.tw water quality (Maier et al., 2004; Sahoo et al., 2006; Chaves and Kojiri, 2007). Of the many types of neural networks, one of the most widely used is the radial basis function neural ... See full document
10
An Enhanced HMM-Based for Fuzzy Time Series Forecasting Model
... The previous study focused on constructing relationship by Markov or HMM, the drawback is only deal with one factor or one hidden variable and one observable variable. The proposed model solves the problem ... See full document
33
An Enhanced HMM-Based for Fuzzy Time Series Forecasting Model
... fast and accurate forecasting method can help mak- ers to make appropriate ...Song and Chissom proposed the definition and the forecasting framework of fuzzy time series ... See full document
6
Forecasting enrollments based on fuzzy time series
... In this paper, we present a new method to fore- cast university enrollments based on fuzzy time series, where the data of historical enrollments of the University of [r] ... See full document
9
Forecasting Wavelet Transformed Time Series with Attentive Neural Networks
... Conclusion Wavelet transform is able to explicitly disclose the latent component s at different frequencies from a complex time series. We develop a novel attention-based neural network that leverages C NN ... See full document
12
Nonlinear dynamic indications in time series of epilepsy electroencephalogram
... brain. For a neural network, such as brain, nonlinearity is necessary to descript the complexity of dynamic ...some nonlinear dynamic indictions, such as Hurst exponent, sample entropy, and detrended ... See full document
2
Robust nonlinear observer for Lipschitz nonlinear systems subject to disturbances
... Robust Nonlinear Observer for Lipschitz Nonlinear Systems Subject to Disturbances Min-Shin Chen and Chi-Che Chen Abstract—This note proposes a robust nonlinear observer ... See full document
5
Robust self-tuning fuzzy tracker design of time-varying nonlinear systems
... Classification code:961 Systems Science - 731.4 System Stability - 731.5 Robotics - 744.1 Lasers, General - 921 Mathematics - 921.1 Algebra - 921.2 Calculus - 922.1 Probability Theory - 931 Classical Physics; Quantum ... See full document
2
Robust control analysis and design for discrete-time singular systems
... This example indicates a fact that the robust control problems of singular systems must consider not only stability robustness but system regularity and impulse elimin[r] ... See full document
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