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Research on the Algorithm of Avionic Device Fault Diagnosis Based on fuzzy expert system

Chinese Journal of Aeronautics 2007年第3期20卷 223-229页

作者： LI Jie SHEN Shi-tuan School of Electronics and Information Engineering Beijing University of Aeronautics and Astronautics Beijing 100083 China

Based on the fuzzy expert system fault diagnosis theory, the knowledge base architecture and inference engine algorithm are put forward for avionic device fault diagnosis. The knowledge base is constructed by fault query network, of which the basic ele- ment is the test-diagnosis fault unit. Every underlying fault cause＇s membership degree is calculated using fuzzy product inference algorithm, and the fault answer best selection algorithm is developed, to which the deep knowledge is applied. Using some examples the proposed algorithm is analyzed for its capability of synthesis diagnosis and its improvement compared to greater membership degree first principle.

关键词： fuzzy expert system fault query network fault answer best selection algorithm fuzzy theory test-diagnosis fault unit

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Prediction system for Diagnosis and Detection of Coronavirus Disease-2019(COVID-19):A fuzzy-Soft expert system

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Computer Modeling in Engineering & Sciences 2023年第6期135卷 2715-2730页

作者： Wencong Liu Ahmed Mostafa Khalil Rehab Basheer Yong Lin School of Science Xi’an Technological UniversityXi’an710021China Department of Mathematics Faculty of ScienceAl-Azhar UniversityAssiut71524Egypt Department of Mathematics Faculty of ScienceAssiut UniversityAssiut71516Egypt Respiratory Department of Nanjing Chest Hospital Affiliated to Southeast University Nanjing210000China

In early December 2019,a new virus named“2019 novel coronavirus(2019-nCoV)”appeared in Wuhan,*** disease quickly spread worldwide,resulting in the COVID-19 *** the currentwork,we will propose a novel fuzzy softmodal(i.e.,fuzzy-soft expert system)for early detection of *** construction of the fuzzy-soft expert systemconsists of five *** exploratory study includes sixty patients(i.e.,fortymales and twenty females)with symptoms similar to COVID-19 in(Nanjing Chest Hospital,Department of Respiratory,China).The proposed fuzzy-soft expert systemdepended on five symptoms of COVID-19(i.e.,shortness of breath,sore throat,cough,fever,and age).We will use the algorithm proposed by Kong et *** detect these patients who may suffer from *** this way,the present system is beneficial to help the physician decide if there is any patient who has COVID-19 or ***,we present the comparison between the present system and the fuzzy expert system.

关键词： Coronavirus disease-2019(COVID-19) fuzzy-soft expert system fuzzy expert system diagnosed results

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Variable universe fuzzy expert system for aluminum electrolysis

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Transactions of Nonferrous Metals Society of China 2011年第2期21卷 429-436页

作者：曹丹阳曾水平李晋宏北方工业大学信息工程学院北京100144 北方工业大学机电工程学院北京100144

In aluminum electrolytic process, the variables affect the current efficiency and the stability of electrolysis cells. AIF3 addition and aluminum tapping volume are two important factors that affect economic benefits of aluminum electrolytic production. fuzzy logic provides a suitable mechanism to describe the relationship between the process variables and the current efficiency. fuzzy expert system based on Mamdani fuzzy inference process for aluminum electrolysis was adopted to adjust A1F3 addition and aluminum tapping volume. A novel variable universe approach was applied in the system to solve the problem that different electrolysis cells have different universes of variables. The system was applied to 300 kA aluminum electrolysis cells in a aluminum plant. Experimental results showed that the electrolyte temperature was kept stably between 945 and 955℃, the current efficiency reached 93.5%, and the DC power consumption was 13 000 kW.h per ton aluminum.

关键词： variable universe fuzzy expert system aluminum electrolysis

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Power Consumption Prediction for an Intelligent Air-Cushion Track Vehicle： fuzzy expert system

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Journal of Energy and Power Engineering 2010年第5期4卷 10-17页

作者： H. Altab R. Ataur A.K.M. Mohiuddin A. Yulfian Department of Mechanical Engineering Faculty of Engineering International Islamic University Malaysia Kuala Lumpur 50728 Malaysia Department of Mechanical Engineering Faculty of Engineering Universiti lndustri Selangor Kuala Selangor 45600 Malaysia

This paper describes the unique structure of an intelligent air-cushion system of a hybrid electrical air-cushion track vehicle working on swamp terrain. fuzzy expert system （FES） is used in this study to control the swamp tracked vehicle＇s intelligent air cushion system while it operates in the swamp peat. The system will be effective to control the intelligent air-cushion system with total power consumption （PC）, cushion clearance height （CCH） and cushion pressure （CP）. Ultrasonic displacement sensor, pull-in solenoid electromagnetic switch, pressure sensor, micro controller and battery pH sensor will be incorporated with the FES to investigate experimentally the PC, CCH and CP. In this study, we provide illustration how FES might play an important role in the prediction of power consumption of the vehicle＇s intelligent air-cushion system. The mean relative error of actual and predicted values from the FES model on total power consumption is found as 10.63 %, which is found to be alomst equal to the acceptable limits of 10%. The goodness of fit of the prediction values from the FES model on PC is found as 0.97.

关键词： Power consumption fuzzy expert system ultrasonic displacement sensor.

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fuzzy Logic-Based system for Liver Fibrosis Disease

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Computer systems Science & Engineering 2023年第9期46卷 3559-3582页

作者： Tamim Alkhalifah Jimmy Singla Fahad Alurise Department of Computer College of Science and Arts in Ar RassQassim UniversityAr RassQassim52571Saudi Arabia Department of Computer Science and Engineering Lovely Professional UniversityPhagwara 144001India

The diagnosis of liver fibrosis(LF)is crucial as it is a deadly and life-threatening *** intelligence techniques aid doctors by using the previous data on health and making a diagnostic system,which helps to take decisions about patients’health as experts *** historical data of a patient’s health can have vagueness,inaccurate,and can also have missing *** fuzzy logic theory can deal with these issues in the *** this paper,a multilayer fuzzy expert system is developed to diagnose *** model is created by using multiple layers of the fuzzy logic *** system aids in classifying the health of patients into different *** proposed method has two layers,i.e.,layer 1 and layer *** input variables used in layer 1 for diagnosing liver fibrosis are Appetite,Jaundice,Ascites,Age,and ***,in layer 2,the input variables are Platelet count,White blood cell count,spleen,SGPT ALT(Serum Glutamic Pyruvic Transaminase Alanine Aminotransferase),SGOT ALT(Serum Glutamicoxalacetic Transaminase Alanine Aminotransferase),Serum bilirubin,and Serum *** output variables for this developed system are no damage,minimal damage,significant damage,severe damage,and *** research work also presents the examination of results based on performance *** proposed system achieves a classification accuracy of 95%.Moreover,other performance parameters such as sensitivity,specificity,and precision are calculated as 97.14%,92%,and 94.44%,respectively.

关键词： Artificial intelligence fuzzy expert system liver fibrosis multilayer inference system a medical diagnostic system

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