نتایج جستجو برای: fuzzy nearest neighbor

تعداد نتایج: 129377  

2017
Neeraj Julka

Data Mining has great scope in the field of medicine. In this article we introduced one new fuzzy approach for prediction of hepatitis disease. Many researchers have proposed the use of K-nearest neighbor (KNN) for diabetes disease prediction. Some have proposed a different approach by using K-means clustering for reprocessing and then using KNN for classification. In our approach Naive Bayes c...

Iman Sahraei Dehmajnoonie Keivan Borna vahid Hajihashemi Zeinab Hassani,

Spam is an unwanted email that is harmful to communications around the world. Spam leads to a growing problem in a personal email, so it would be essential to detect it. Machine learning is very useful to solve this problem as it shows good results in order to learn all the requisite patterns for classification due to its adaptive existence. Nonetheless, in spam detection, there are a large num...

2009
Dinesh Acharya

The recognition of handwritten numeral is an important area of research for its applications in post office, banks and other organizations. This paper presents automatic recognition of handwritten Kannada numerals using both unsupervised and supervised classifiers. Four different types of structural features, namely, direction frequency code, water reservoir, end points and average boundary len...

1995
Lalla Merieme Zouhal

Recently, a new pattern classiier using neighborhood information in the framework of the Dempster-Shafer theory of evidence was introduced 3, 2]. This approach consists in considering each neighbor of a pattern to be classiied as an item of evidence supporting certain hypotheses concerning the class membership of that pattern. In this paper, an adaptive version of this method is proposed, in wh...

2005
D. Unay B. Gosselin

In this paper, a novel method to recognize stem or calyx regions of ‘Jonagold’ apples by pattern recognition is proposed. The method starts with background removal and object segmentation by thresholding. Statistical, textural and shape features are extracted from each segmented object and these features are introduced to several supervised classification algorithms. Linear discriminant, neares...

ربانی, حسن, سلیمانی فرد, فاطمه , مردانی, محمد,

 In this paper, we investigate the phonon transmission coefficient of a mass-spring in the presence of Kohn interaction by using Green’s function method within the harmonic approximation. This system is embedded between two simple phononic leads including only the nearest neighbor interactions. The results show that the presence of Kohn and the nearest neighbor interactions in the center wire m...

Journal: :Int. J. Approx. Reasoning 2008
Ashish Ghosh Bijnan Parai

De novo structure determination of proteins is a significant research issue of bioinformatics. Biochemical procedures for protein structure determination are costly. Use of different pattern classification techniques are proved to ease this task. In this article, the secondary structure prediction task has been mapped into a three-class problem of pattern classification, where the classes are h...

Rahil hosseini

 Edge Detection is an important task for sharpening the boundary of images to detect the region of interest. This paper applies a linear cellular automata rules and a Mamdani Fuzzy inference model for edge detection in both monochromatic and the RGB images. In the uniform cellular automata a transition matrix has been developed for edge detection. The Results have been compared to the ...

A. Sayadiyan, K. Badi, M. Moin and N. Moghadam,

Hidden Markov Model is a popular statisical method that is used in continious and discrete speech recognition. The probability density function of observation vectors in each state is estimated with discrete density or continious density modeling. The performance (in correct word recognition rate) of continious density is higher than discrete density HMM, but its computation complexity is very ...

1997
VOLODYMYR V. KINDRATENKO BORIS A. TREIGER PIERRE J. M. VAN ESPEN

A method for the classification of tabular grain silver halide microcrystals according to their shape is presented. Various approaches of shape analysis and recognition and their applicability for the given problem are discussed. Shape descriptors obtained from Fourier power spectra are used to describe the shape of microcrystals. The classification of the shapes is based on nearest neighborhoo...

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