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» The fuzzy approach to statistical analysis
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JCIT
2008
124views more  JCIT 2008»
15 years 14 days ago
A Knowledge based Approach Using Fuzzy Inference Rules for Vowel Recognition
Automatic speech recognition by machine is one of the most efficient methods for man-machine communications. Because speech waveform is nonlinear and variant. Speech recognition r...
Hrudaya K. Tripathy, B. K. Tripathy, Pradip K. Das
CEC
2007
IEEE
15 years 2 months ago
A novel general framework for evolutionary optimization: Adaptive fuzzy fitness granulation
— Computational complexity is a major challenge in evolutionary algorithms due to their need for repeated fitness function evaluations. Here, we aim to reduce number of fitness f...
Mohsen Davarynejad, Mohammad R. Akbarzadeh-Totonch...
EUSFLAT
2001
116views Fuzzy Logic» more  EUSFLAT 2001»
15 years 1 months ago
Risk assessment in natural disasters with fuzzy probabilities
Risk assessment in regions with low earthquake activity is important for reinsurance companies and governmental building authorities. They need a complete picture of the possible ...
Uwe Wagner
APIN
1999
143views more  APIN 1999»
15 years 5 days ago
Solving Electrical Distribution Problems Using Hybrid Evolutionary Data Analysis Techniques
Real-world electrical engineering problems can take advantage of the last Data Analysis methodologies. In this paper we will show that Genetic Fuzzy Rule-Based Systems and Genetic ...
Oscar Cordón, Francisco Herrera, Luciano S&...
102
Voted
IJIT
2004
15 years 1 months ago
On the Noise Distance in Robust Fuzzy C-Means
In the last decades, a number of robust fuzzy clustering algorithms have been proposed to partition data sets affected by noise and outliers. Robust fuzzy C-means (robust-FCM) is c...
Mario G. C. A. Cimino, Graziano Frosini, Beatrice ...