Results 1 to 10 of about 245 (160)
Prevalence and correlates of dizziness in community-dwelling older people: a cross sectional population based study [PDF]
BMC Geriatrics, 2013 Background Dizziness is a common complaint among older adults and has been linked to a wide range of health conditions, psychological and social characteristics in this population.
de Moraes Suzana Albuquerque +3 more
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Multivariate Analysis of Variance for Fuzzy Data [PDF]
International Journal of Fuzzy Logic and Intelligent Systems, 2004 We propose some properties of fuzzy multivariate analysis of variance by fuzzy vector operation with agreement index. We deals fuzzy null hypotheses and fuzzy alternative hypothesis and define the agreement index for the grades of the judgements that the hypothesis is rejection or acceptance. Finally, we provide an example to evaluate the judgements.
Man-Ki Kang, Sung Il Han
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STABILITY ANALYSIS OF FUZZY CONTROL SYSTEMS. MULTIVARIABLE POINT OF VIEW [PDF]
IFAC Proceedings Volumes, 2005 Abstract The paper proposes a new global stability analysis method dedicated to fuzzy control systems containing Mamdani fuzzy controllers with dynamics to control SISO linear / linearized plants. The method is expressed in terms of relatively simple steps based on the generalization of the describing function method to the MIMO case and on the ...
Radu-Emil Precup, Stefan Preitl
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Multiscale multivariate fuzzy entropy analysis
Acta Physica Sinica, 2013 Multiscale multivariate sample entropy can test the multivariate complexity, which is accepted as a kind of reflection of nonlinear dynamical interactions in multichannel data. It is however relatively unstable due to the rigid ranking scheme used in comparison among different patterns.
null Li Peng +5 more
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A Multivariate Multiscale Fuzzy Entropy Algorithm with Application to Uterine EMG Complexity Analysis [PDF]
Entropy, 2016 The recently introduced multivariate multiscale entropy (MMSE) has been successfully used to quantify structural complexity in terms of nonlinear within- and cross-channel correlations as well as to reveal complex dynamical couplings and various degrees of synchronization over multiple scales in real-world multichannel data.
Mosabber Uddin Ahmed +3 more
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Fuzzy-Based Multivariate Analysis for Input Modeling of Risk Assessment in Wind Farm Projects [PDF]
Algorithms, 2020 Currently, input modeling for Monte Carlo simulation (MSC) is performed either by fitting a probability distribution to historical data or using expert elicitation methods when historical data are limited. These approaches, however, are not suitable for wind farm construction, where—although lacking in historical data—large amounts of subjective ...
Emad Mohamed +2 more
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Weighted fuzzy clustering for (fuzzy) constraints in multivariate image analysis–alternating least square of hyperspectral images [PDF]
Journal of Spectral Imaging, 2016 In order to investigate hyperspectral images, many techniques such as multivariate image analysis (MIA) or multivariate curve resolution–alternating least squares (MCR–ALS) can be applied. When focusing on the use of MCR–ALS, constraints are of the utmost importance for a correct resolution of the data into its individual contributions. In this article,
Cyril Ruckebusch +6 more
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Computers & Chemical Engineering, 2014 Abstract Root cause analysis is an important method for fault diagnosis when used with multivariate statistical process monitoring (MSPM). Conventional contribution analysis in MSPM can only isolate the effects of the fault by pinpointing inconsistent variables, but not the underlying cause.
Bo He, Tao Chen 0009, Xianhui Yang
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ProcessesIn this work, a new nonlinear control method is proposed, which integrates the Takagi–Sugeno (T–S) fuzzy model with the Principal Component Analysis (PCA) technique. The approach uses PCA to reduce the system’s dimensionality, minimizing the number of fuzzy rules required in the T–S fuzzy model.
Al-Hadithi, Basil Mohammed +1 more
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Expert SystemsABSTRACT This study develops a novel two‐stage framework to evaluate financial health, distress and liquidity traps in the banking industry by integrating a Fuzzy Modulatory Data Envelopment Analysis model with a Fuzzy Multivariate Lognormal Regression. The methodology incorporates fuzzy set theory with alpha‐cuts to capture vagueness
Wanke, Peter +2 more
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