Application of ‘most’ fuzzy linguistic quantifier to filter impulse noise

2018 ◽  
Vol 11 (1) ◽  
pp. 141-148
Author(s):  
Ruchika Singh ◽  
Munish Vashishath ◽  
S. Qamar
Keyword(s):  
Impulse Noise ◽  
Linguistic Quantifier ◽  
Fuzzy Linguistic

scholarly journals Fuzzy Simple Additive Weighting Untuk Diagnosis Penyakit Pneumonia

2013 ◽  
Vol 1 (1) ◽  
Author(s):  
Muhammad Syaukani ◽  
Suryo Guritno
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Medical Personnel ◽  
Group Decision Support System ◽  
Forward Chaining ◽  
Linguistic Quantifier ◽  
Health Community ◽  
Simple Additive Weighting ◽  
Fuzzy Linguistic

Abstract. Pneumonia is an infection of the lungs that is caused by bacteria, viruses, fungi, or parasites. It is characterized primarily by inflammation of the alveoli in the lungs or by alveoli that are filled with fluid (alveoli are microscopic sacs in the lungs that absorb oxygen). The shortage of medical personnel at health community centers to serve a population often results in care delays for pneumonia patients. The purpose of this research is to make a modelling of group decision support system in diagnosing pneumonia in adult patients. The system is designed as a tool for medical personnel in diagnosing pneumonia patients.Group Decision Support System (GDSS) is developed by using Fuzzy Simple Additive weighting methods. The preference scoring of three experts i.e. a pulmonary specialist, an internist and a pharmacist is carried out by applying triangular fuzzy numbers. In the aggregation stage, preferences makes use of Fuzzy Linguistic quantifier, stage rangking employs Simple Additive Weighting while Forward Chaining is employed in the inference process. The system is tested by inputting the symptoms of pneumonia without the involvement of an expert. The results shows that the system is capable in diagnosing pneumonia.Keywords: GDSS, Fuzzy, Simple Additive Weighting, Pneumonia Abstrak. Pneumonia adalah infeksi paru-paru yang disebabkan oleh bakteri, virus, jamur, atau parasit. Hal ini ditandai terutama oleh peradangan alveoli di paru-paru atau alveoli yang berisi cairan (alveoli adalah kantung mikroskopis di paru-paru yang menyerap oksigen), terbatasnya tenaga medis di puskesmas disbanding dengan jumlah penduduk berakibat sering terlambatnya pelayanan terhadap pasien pneumonia. Tujuan penelitian ini adalah membuat pemodelan sistem pendukung keputusan kelompok untuk mendiagnosis pasien pneumonia pada orang dewasa. Sistem ini dirancang sebagai alat bantu tenaga medis dalam mendiagnosis pasien pneumonia. Sistem Pendukung Keputusan Kelompok (SPKK) dikembangkan menggunakan metode Fuzzy Simple Additive Weighting. Pemberian nilai preferensi tiga orang pakar antara lain ahli paru-paru, ahli internis dan ahli farmasi menggunakan bilangan fuzzy segitiga. Pada tahap agregasi preferensi digunakan Fuzzy Linguistic Quantifier, tahap perangkingan menggunakan Simple Additive Weighting dan proses inferensi menggunakan Forward Chaining. Sistem diuji dengan cara memasukkan gejala-gejala pneumonia tanpa melibatkan seorang pakar. Hasil penelitian menunjukkan bahwa sistem dapat mendiagnosis penyakit pneumonia.Kata Kunci: SPKK, Fuzzy, Simple Additive Weighting, Pneumonia

INTUITIONISTIC FUZZY LINGUISTIC QUANTIFIERS BASED ON INTUITIONISTIC FUZZY-VALUED FUZZY MEASURES AND INTEGRALS

2009 ◽  
Vol 17 (03) ◽  
pp. 427-448 ◽  
Author(s):  
LICONG CUI ◽  
YONGMING LI ◽  
XIAOHONG ZHANG
Keyword(s):  
Artificial Intelligence ◽  
Fuzzy Integral ◽  
Fuzzy Measures ◽  
Intuitionistic Fuzzy ◽  
Norm Form ◽  
Form Theorem ◽  
Linguistic Quantifier ◽  
Fuzzy Linguistic Quantifiers ◽  
Linguistic Quantifiers ◽  
Fuzzy Linguistic

In this paper, we generalize Ying's model of linguistic quantifiers [M.S. Ying, Linguistic quantifiers modeled by Sugeno integrals, Artificial Intelligence, 170 (2006) 581-606] to intuitionistic linguistic quantifiers. An intuitionistic linguistic quantifier is represented by a family of intuitionistic fuzzy-valued fuzzy measures and the intuitionistic truth value (the degrees of satisfaction and non-satisfaction) of a quantified proposition is calculated by using intuitionistic fuzzy-valued fuzzy integral. Description of a quantifier by intuitionistic fuzzy-valued fuzzy measures allows us to take into account differences in understanding the meaning of the quantifier by different persons. If the intuitionistic fuzzy linguistic quantifiers are taken to be linguistic fuzzy quantifiers, then our model reduces to Ying's model. Some excellent logical properties of intuitionistic linguistic quantifiers are obtained including a prenex norm form theorem. A simple example is presented to illustrate the use of intuitionistic linguistic quantifiers.

An Effective FPGA Implementation of Denoising of Impulse Noise in Images

2016 ◽  
Vol 1 (3) ◽  
pp. 19-25
Author(s):  
Jeniffer A ◽  
Haripasath S ◽  
Chinthamani S ◽  
Chitra G ◽  
Karthiga V
Keyword(s):  
Impulse Noise ◽  
Fpga Implementation

Removal of Mixed Poisson and Impulse Noise in 1-D Signals by Non-Adaptive and Adaptive Nonlinear Filters

2008 ◽  
Vol 67 (14) ◽  
pp. 1247-1267
Author(s):  
V. V. Lukin ◽  
S. Peltonen ◽  
P. Ye. Yeltsov ◽  
S. K. Abramov ◽  
A. N. Besedin ◽  
...  
Keyword(s):  
Impulse Noise ◽  
Nonlinear Filters
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