Fuzzy Expert System based on a Novel Hybrid Stem Cell (HSC) Algorithm for Classification of Micro Array Data

2018 ◽  
Vol 42 (4) ◽  
Author(s):  
S. Arul Antran Vijay ◽  
P. GaneshKumar
Keyword(s):  
Stem Cell ◽  
Expert System ◽  
Fuzzy Expert System ◽  
Array Data ◽  
Micro Array

A Fuzzy–Expert System For Classification Of Short Duration Voltage Disturbances

2012 ◽  
Author(s):  
Ghafour Amouzad Mahdiraji ◽  
Azah Mohamed
Keyword(s):  
Expert System ◽  
Power Quality ◽  
Short Duration ◽  
Automated Detection ◽  
Voltage Sag ◽  
Fuzzy Expert System ◽  
Correct Classification Rate ◽  
Classification Rate ◽  
Fast Fourier Transform Analysis

Satu aspek penting dalam penilaian kualiti kuasa adalah pengesanan dan pengkelasan gangguan kualiti kuasa secara automatik yang memerlukan penggunaan teknik kepintaran buatan. Kertas kerja ini membentangkan penggunaan sistem pakar-kabur untuk pengkelasan gangguan voltan jangka masa pendek yang termasuk lendut voltan, ampul dan sampukan. Untuk memperolehi sifat unik bagi gangguan voltan, analisis jelmaan Fourier pantas dan teknik purataan punca min kuasa dua digunakan untuk menentukan parameter gangguan seperti tempoh masa, magnitud voltan pmk maksimum dan minimum. Berasaskan pada parameter ini, sebuah sistem pakar–kabur telah dibangunkan dengan mengset aturan kabur yang menimbangkan lima masukan dan tiga keluaran. Sistem ini direka bentuk untuk mengesan dan mengkelaskan tiga jenis gangguan voltan tempoh masa pendek dengan menentukan sama ada gangguan adalah gangguan ketika, gangguan seketika dan bukan gangguan lendut, ampul dan sampukan. Untuk mengesahkan kejituan sistem yang dicadangkan, ia telah diuji dengan gangguan voltan yang diperolehi dari pengawasan. Keputusan ujian menunjukkan bahawa sistem pakar–kabur yang dibangunkan telah memberikan kadar pengkelasan yang betul sebanyak 98.4 %. Kata kunci: Kualiti kuasa, sistem pakar–kabur, lendut, ampul dan sampukan One of the important aspects in power quality assessment is automated detection and classification of power quality disturbances which requires the use of artificial intelligent techniques. This paper presents the application of fuzzy–expert system for classification of short duration voltage disturbances which include voltage sag, swell and interruption. To obtain unique features of the voltage disturbances, fast Fourier transform analysis and root mean square averaging technique are utilized so as to determine the disturbance parameters such as duration, maximum and minimum rms voltage magnitudes. Based on these parameters, a fuzzy-expert system has been developed to set the fuzzy rules incorporating five inputs and three outputs. The system is designed for detecting and classifying the three types of short duration voltage disturbances, so as to determine whether the disturbance is instantaneous, momentary and non sag, swell and interruption. To verify the accuracy of the proposed system, it has been tested with recorded voltage disturbances obtained from monitoring. Tests results showed that the developed fuzzy–expert system gives a correct classification rate of 98.4 %. Key words: Power quality, fuzzy–expert system, sag, swell and interruption.

scholarly journals Classification of Micro-array Data in Apache Spark Framework

2020 ◽  
Vol 928 ◽  
pp. 032067
Author(s):  
Wafaa S. Albaldawi ◽  
Rafah M. Almuttairi
Keyword(s):  
Apache Spark ◽  
Array Data ◽  
Micro Array ◽  
Spark Framework

Classification of Power Quality Problems by Wavelet Fuzzy Expert System

2012 ◽  
Vol 463-464 ◽  
pp. 1573-1578
Author(s):  
N. Karthik ◽  
Shaik Abdul Gafoor ◽  
M. Surya Kalavathi
Keyword(s):  
Expert System ◽  
Power Quality ◽  
Intelligent System ◽  
Fuzzy Expert System ◽  
Quality Problem ◽  
Electric Power Quality ◽  
Transient Disturbances ◽  
Key Issues ◽  
Power Utilities

Electric power quality, which is a current interest to several power utilities all over the world, is often severely affected by harmonics and transient disturbances. There is no unique model which can assess the power quality problem and to identify and classify them properly. Existing automatic recognition methods need improvement in terms of their versatility, reliability, and accuracy. The FUZZY LOGIC based tools have been applied for the PQ classification. This paper addresses Power quality problem classification by wavelet and fuzzy expert system. Major Key issues and challenges related to these advanced techniques in automatic classification of PQ problems are highlighted. New intelligent system technologies using DSP, expert systems, AI and machine learning provide some unique advantages in intelligent classification of PQ distortions

CLASSIFICATION AND ANALYSIS OF BLOOD PRESSURE CHARACTERISTICS USING FUZZY LOGIC APPROACH

2022 ◽  
Author(s):  
EMMANUEL OLUOKUN
Keyword(s):  
Blood Pressure ◽  
Expert System ◽  
Antihypertensive Medication ◽  
Research Work ◽  
Secondary Data ◽  
Fuzzy Expert System ◽  
Treatment Of Hypertension ◽  
Fuzzy Logic Approach ◽  
Logic Approach

The idea of Fuzzy Expert System (FES) used in this research work is proposed to assist the medical experts to make right diagnosis for patients that are suffering from hypertension. The only sure way to monitor high blood pressure is through regular checkups. Majority of the researchers that have worked in this field only focused on using fuzzy expert system for classification of hypertension data, while few of them dealt with data analysis. This research work further checked for the efficacy of medication on the patients and the exact time the effect began to have impact on the patients using secondary data collected from questionnaire. It was gathered from the sampled respondents that the antihypertensive medication (Dieuretic) has been reliable in the treatment of hypertension.

Classification of power system disturbances using a fuzzy expert system and a Fourier linear combiner

2000 ◽  
Vol 15 (2) ◽  
pp. 472-477 ◽  
Author(s):  
P.K. Dash ◽  
S. Mishra ◽  
M.A. Salama ◽  
A.C. Liew
Keyword(s):  
Expert System ◽  
Power System ◽  
Fuzzy Expert System ◽  
Power System Disturbances
Sign in / Sign up

Export Citation Format

Share Document