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.

A Fuzzy Logic Approach to Assessing Materiality

2005 ◽  
Vol 2 (1) ◽  
pp. 1-15 ◽  
Author(s):  
Christie L. Comunale ◽  
Thomas R. Sexton
Keyword(s):  
Expert System ◽  
System Approach ◽  
Formal Model ◽  
Assessment Process ◽  
Fuzzy Expert System ◽  
Model Structure ◽  
Fuzzy Logic Approach ◽  
Logic Approach ◽  
Audit Strategy ◽  
Audit Team

Auditors may encounter misstatements during the course of an audit, each of which requires a binary materiality assessment. We propose a fuzzy expert system approach that assesses materiality as a continuous characteristic by allowing a misstatement to possess a degree of materiality between 0 and 1. This potentially allows the auditor more flexibility and precision in materiality assessment, and greater insight regarding subsequent testing and investigation. We demonstrate that a fuzzy expert system can help the auditor incorporate qualitative factors into the materiality assessment of each misstatement and identify which misstatements are most worthy of further investigation. The auditor may compare the materiality assessments of all misstatements to plan an audit strategy. By providing a formal model structure, the fuzzy expert system formalizes and documents the materiality assessment process. This may facilitate better communication within the audit team and with the client, and enhances process consistency across auditors, engagements, and years.

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.

A fuzzy logic approach for the classification of product qualitative characteristics

2002 ◽  
Vol 26 (3) ◽  
pp. 429-438 ◽  
Author(s):  
George Tsekouras ◽  
Haralambos Sarimveis ◽  
Costas Raptis ◽  
George Bafas
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Approach ◽  
Logic Approach ◽  
Qualitative Characteristics

scholarly journals A Novel Fuzzy Logic-Based Medical Expert System for Diagnosis of Chronic Kidney Disease

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Jimmy Singla ◽  
Balwinder Kaur ◽  
Deepak Prashar ◽  
Sudan Jha ◽  
Gyanendra Prasad Joshi ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Chronic Kidney Disease ◽  
Expert System ◽  
Kidney Disease ◽  
Blood Sugar ◽  
Research Work ◽  
Fuzzy Rule ◽  
Inference System ◽  
Input Variables ◽  
Current Stage

Chronic kidney disease is a life-threatening complication. Primary diagnosis and active control avoid its progression. To increase the life span of a patient, it is necessary to detect such diseases in early stages. In this research paper, design and development of a fuzzy expert system (FES) to identify the current stage of chronic kidney disease is proposed. The proposed fuzzy rule-based expert system is developed with the help of clinical practice guidelines, database, and the knowledge of a team of specialists. It makes use of input variables like nephron functionality, blood sugar, diastolic blood pressure, systolic blood pressure, age, body mass index (BMI), and smoke. The normality tests are applied on different input parameters. The input variables, i.e., nephron functionality, blood sugar, and BMI have more impact on the chronic kidney disease as shown by the response of surface analysis. The output of the system shows the current stage of patient’s kidney disease. Totally 80 tests were performed on the FES developed in this research work, and the generated output was compared with expected output. It is observed that this system succeeds in 93.75% of the tests. This system supports the doctors in assessment of chronic kidney disease among patients. The detection of chronic kidney disease is a serious clinical problem that comprises imprecision, and the use of fuzzy inference system is suggested to overcome this issue. The proposed FES is implemented in the MATLAB.

Automated Cloud Classification of Global AVHRR Data Using a Fuzzy Logic Approach

1997 ◽  
Vol 36 (11) ◽  
pp. 1519-1540 ◽  
Author(s):  
Bryan A. Baum ◽  
Vasanth Tovinkere ◽  
Jay Titlow ◽  
Ronald M. Welch
Keyword(s):  
Fuzzy Logic ◽  
Cloud Classification ◽  
Avhrr Data ◽  
Fuzzy Logic Approach ◽  
Logic Approach

Rule based fuzzy logic approach for classification of fibromyalgia syndrome

2016 ◽  
Vol 39 (2) ◽  
pp. 501-515 ◽  
Author(s):  
Evren Arslan ◽  
Sedat Yildiz ◽  
Yalcin Albayrak ◽  
Etem Koklukaya
Keyword(s):  
Fuzzy Logic ◽  
Fibromyalgia Syndrome ◽  
Rule Based ◽  
Fuzzy Logic Approach ◽  
Logic Approach

scholarly journals Forecasting Unsafe Level of Work Stations with Injuries Frequency Measurement Criterion: A Fuzzy Logic Approach

2018 ◽  
Vol 5 (1) ◽  
pp. 109-119
Author(s):  
Hezekiah O. Adeyemi ◽  
Taofeek A. Yusuf ◽  
Martins O. Osifeko
Keyword(s):  
Expert System ◽  
Frequency Measurement ◽  
Work Place ◽  
Output Data ◽  
Significance Level ◽  
Strong Positive Relationship ◽  
Fuzzy Logic Approach ◽  
Logic Approach ◽  
Predicted Values ◽  
Test Result

In this study, a fuzzy-based expert system called Accident Prone Workstations Prediction Expert System (APWAPES) was developed to forecast unsafe level of work stations. APWAPES used fuzzy set theory to make decisions based on the “Total-hours-worked” and “Injury-Count” as inputs and “Workstation-unsafe-ratings” as the output. Data collected from subjects in 20 workstations were run with APWAPES. The results were compared with an Existing Mathematical Model (EME). The validation result showed that there was a strong positive relationship between the EME and the developed APWAPES with a correlation coefficient of 0.710. The t-test result for mean difference showed that EME had a statistically significantly higher level of rating (0.60 ± 0.30, SEM=0.004) compared to APWAPES (0.50 ± 0.02, SEM= 0.007), t(38) = 1.613, p = 0.115. With a significance level of 0.001 at 95% confidence, the APWAPES and the EME predicted values were not significantly different. The study developed an expert system, APWAPES, which can find its applications in any work place where hazards occur and capable of helping managers of industries, to measure work places and/or activities disposed to accidents.

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

A Fuzzy Logic Approach for the Assessment of Online Customers

2012 ◽  
pp. 252-270
Author(s):  
Nicolas Werro ◽  
Henrik Stormer
Keyword(s):  
Fuzzy Logic ◽  
Global Economy ◽  
Relational Databases ◽  
Customer Relationships ◽  
Customer Equity ◽  
Fuzzy Classification ◽  
Loyalty Programs ◽  
Fuzzy Logic Approach ◽  
Logic Approach

A key challenge for companies in the e-business era is to manage customer relationships as an asset. In today’s global economy this task is becoming simultaneously more difficult and more important. In order to retain the potentially good customers and to improve their buying attitude, this chapter proposes a hierarchical fuzzy classification of online customers. A fuzzy classification, which is a combination of relational databases and fuzzy logic, allows customers to be classified into several classes at the same time and can therefore precisely determine the customers’ value for an enterprise. This approach allows companies to improve the customer equity, to launch loyalty programs, to automate mass customization, and to refine marketing campaigns in order to maximize the customers’ value and, this way, the companies’ profit.

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