Results 111 to 120 of about 245 (160)
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2004
In this paper we will analyze data obtained from a fuzzy set, where samples are defined using a membership grade of a fuzzy set. Generally, multivariant model is to analyze samples characterized using plural variants. In this paper such smaples are also characterized by a fuzzy set.
Junzo Watada +2 more
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In this paper we will analyze data obtained from a fuzzy set, where samples are defined using a membership grade of a fuzzy set. Generally, multivariant model is to analyze samples characterized using plural variants. In this paper such smaples are also characterized by a fuzzy set.
Junzo Watada +2 more
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Leanness assessment and optimization by fuzzy cognitive map and multivariate analysis
Expert Systems with Applications, 2015A new method to assess and optimize organizational leanness.Standard leanness measures from the body of the literature.Fuzzy cognitive map and multivariate analysis are used for evaluation.A number of packing and printing organizations are studied.The proposed analogy helps managers to assess the leanness. The strategy of organizational lean production
Ali Azadeh +4 more
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A scale fuzzy windowing comparison applied to multivariate descriptive analysis
Intelligent Data Analysis, 2012Observational and experimental data are often investigated into so that the factor effects and/or variables connections can be assessed quickly and easily via inference tests. This article suggests starting the statistical analysis using a 5-step descriptive procedure: 1) Data characterization, 2) Data coding, 3) Data table drafting, 4) Data table ...
Pierre Loslever +4 more
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Multivariate Fuzzy Analysis for Mobile Ad hoc Network Threat Detection
International Journal of Business Data Communications and Networking, 2008Detection of malicious, compromised and selfish node attacks is urgently needed to protect Mobile Ad hoc Networks (MANET) and their applications from failures. Once a MANET component is affected by a malicious, compromised or selfish node its operational state shifts from normal state to vulnerable state.
Sathish Kumar Alampalayam, Essam Natsheh
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A Multivariate Fuzzy Analysis for the Regeneration of Urban Poverty Areas
2008Urban poverty, specially in the metropolitan areas, represent one of the most relevant problems to both developed and developing countries. The objective of the present work is to identify, based on statistical data, territorial zones characterized by the presence of urban poverty, related to property ownership and the availability of residential ...
Paola Perchinunno +2 more
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Stability analysis and synthesis of multivariable fuzzy systems using interval arithmetic
Fuzzy Sets and Systems, 2004zbMATH Open Web Interface contents unavailable due to conflicting licenses.
José Manuel Andújar +2 more
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Analysis of approximation of continuous fuzzy functions by multivariate fuzzy polynomials
Fuzzy Sets and Systems, 2002zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Stability analysis of nonlinear multivariable Takagi-Sugeno fuzzy control systems
IEEE Transactions on Fuzzy Systems, 1999Points out how the nonlinearities involved in multivariable Takagi-Sugeno (T-S) fuzzy control systems could originate complex behavior phenomena, such as multiple equilibrium points or limit cycles, that cannot be detected using conventional stability analysis techniques.
Federico Cuesta +3 more
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Local Multivariate Analysis Based on Fuzzy Clustering
2008In this chapter, we describe the close relationship between enhanced clustering algorithms and local multivariate analysis. The objective functions are defined based on the standard fuzzification approach. However, it is easy to define similar objective functions based on other fuzzification approaches and the most parts of the discussions given in ...
Sadaaki Miyamoto +2 more
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Proceedings of the 5th International Conference on Sustainable Information Engineering and Technology, 2020
Multivariate Transductive Neuro-Fuzzy Inference System model, named the mTNFI is a previously proposed conceptual transductive approach designed for analysis and modelling of multivariate time-series data. In this study, we revisit, implement and evaluate the mTNFI model potential for patterns of relationship extraction from a collection of ...
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Multivariate Transductive Neuro-Fuzzy Inference System model, named the mTNFI is a previously proposed conceptual transductive approach designed for analysis and modelling of multivariate time-series data. In this study, we revisit, implement and evaluate the mTNFI model potential for patterns of relationship extraction from a collection of ...
openaire +1 more source