Fully Completed Spherical Fuzzy Approach-Based Z Numbers(PHIModel)for Enhanced Group Expert Consensus

This study aims to establish an expert consensus and enhance the efficacy of decision-making processes by integrating Spherical Fuzzy Sets(SFSs)and Z-Numbers(SFZs).A novel group expert consensus technique,the PHImodel,is developed to address the inherent limitations of both SFSs and the traditional Delphi technique,particularly in uncertain,complex scenarios.In such contexts,the accuracy of expert knowledge and the confidence in their judgments are pivotal considerations.This study provides the fundamental operational principles and aggregation operators associated with SFSs and Z-numbers,encompassing weighted geometric and arithmetic operators alongside fully developed operators tailored for SFZs numbers.Subsequently,a case study and comparative analysis are conducted to illustrate the practicality and effectiveness of the proposed operators and methodologies.Integrating the PHI model with SFZs numbers represents a significant advancement in decision-making frameworks reliant on expert input.Further,this combination serves as a comprehensive tool for decision-makers,enabling them to achieve heightened levels of consensus while concurrently assessing the reliability of expert contributions.The case study results demonstrate the PHI model’s utility in resolving complex decision-making scenarios,showcasing its ability to improve consensus-building processes and enhance decision outcomes.Additionally,the comparative analysis highlights the superiority of the integrated approach over traditional methodologies,underscoring its potential to revolutionize decision-making practices in uncertain environments.

Prediction System for Diagnosis and Detection of Coronavirus Disease-2019(COVID-19):A Fuzzy-Soft Expert System

In early December 2019,a new virus named“2019 novel coronavirus(2019-nCoV)”appeared in Wuhan,China.The disease quickly spread worldwide,resulting in the COVID-19 pandemic.In the currentwork,we will propose a novel fuzzy softmodal(i.e.,fuzzy-soft expert system)for early detection of COVID-19.Themain construction of the fuzzy-soft expert systemconsists of five portions.The 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 al.to detect these patients who may suffer from COVID-19.In this way,the present system is beneficial to help the physician decide if there is any patient who has COVID-19 or not.Finally,we present the comparison between the present system and the fuzzy expert system.

Multi-Attribute Group Decision-Making Method under Spherical Fuzzy Bipolar Soft Expert Framework with Its Application

Spherical fuzzy soft expert set(SFSES)theory blends the perks of spherical fuzzy sets and group decision-making into a unified approach.It allows solutions to highly complicated uncertainties and ambiguities under the unbiased supervision and group decision-making of multiple experts.However,SFSES theory has some deficiencies such as the inability to interpret and portray the bipolarity of decision-parameters.This work highlights and overcomes these limitations by introducing the novel spherical fuzzy bipolar soft expert sets(SFBSESs)as a powerful hybridization of spherical fuzzy set theory with bipolar soft expert sets(BSESs).Followed by the development of certain set-theoretic operations and properties of the proposed model,important problems,including the selection of non-powered dam(NPD)sites for hydropower conversion are discussed and solved under the proposed approach.These problems mainly focus on the need for an efficient tool capable of considering the bipolarity of parameters,complicated ambiguities,and multiple opinions.Supporting the new approach by a detailed comparative analysis,it is concluded that the proposed model is more comprehensive and reliable for multi-attribute group decisionmaking(MAGDM)than the previous tools,particularly considering the bipolarity of parameters under SFSES environment.

Fuzzy Soft Expert Matrix Theory and Its Application in Decision-Making

A unique mathematical strategy for dealing with uncertainty is fuzzy soft set theory. In this paper, we propose fuzzy soft expert matrices and describe numerous varieties of fuzzy soft expert matrices, as well as specific operations. Finally, by applying these matrices to decision-making scenarios, we widen our methodology.

Variable universe fuzzy expert system for aluminum electrolysis

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.

Research on the Algorithm of Avionic Device Fault Diagnosis Based on Fuzzy Expert System

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.

Study on Missile Intelligent Fault Diagnosis System Based on Fuzzy NN Expert System

In order to study intelligent fault diagnosis methods based on fuzzy neural network (NN) expert system and build up intelligent fault diagnosis for a type of missile weapon system, the concrete implementation of a fuzzy NN fault diagnosis expert system is given in this paper. Based on thorough research of knowledge presentation, the intelligent fault diagnosis system is implemented with artificial intelligence for a large-scale missile weapon equipment. The method is an effective way to perform fuzzy fault diagnosis. Moreover, it provides a new way of the fault diagnosis for large-scale missile weapon equipment.

Fuzzy expert system for diagnosing diabetic neuropathy

AIM To design a fuzzy expert system to help detect and diagnose the severity of diabetic neuropathy. METHODS The research was completed in 2014 and consisted of two main phases. In the first phase, the diagnostic parameters were determined based on the literature review and by investigating specialists' perspectives(n= 8). In the second phase, 244 medical records related to the patients who were visited in an endocrinology and metabolism research centre during the first six months of 2014 and were primarily diagnosed with diabetic neuropathy, were used to test the sensitivity, specificity, and accuracy of the fuzzy expert system.RESULTS The final diagnostic parameters included the duration of diabetes, the score of a symptom examination based on the Michigan questionnaire, the score of a sign examination based on the Michigan questionnaire, the glycolysis haemoglobin level, fasting blood sugar, blood creatinine, and albuminuria. The output variable was the severity of diabetic neuropathy which was shown as a number between zero and 10, had been divided into four categories: absence of the disease,(the degree of severity) mild, moderate, and severe. The interface of the system was designed by ASP.Net(Active Server Pages Network Enabled Technology) and the system function was tested in terms of sensitivity(true positive rate)(89%), specificity(true negative rate)(98%), and accuracy(a proportion of true results, both positive and negative)(93%).CONCLUSION The system designed in this study can help specialistsand general practitioners to diagnose the disease more quickly to improve the quality of care for patients.

Fuzzy Soft Expert Set and Its Application

In 1999, Molodtsov introduced the concept of soft set theory as a general mathematical tool for dealing with uncertainty. Alkhazaleh and Salleh (2011) define the concept of soft expert sets where the user can know the opinion of all experts in one model and give an application of this concept in decision making problem. So in this paper, we generalize the concept of a soft expert set to fuzzy soft expert set, which will be more effective and useful. We also define its basic operations, namely complement, union, intersection, AND and OR. We give an application of this concept in decision making problem. Finally, we study a mapping on fuzzy soft expert classes and its properties.

Educational Advisor System Implemented by Web-Based Fuzzy Expert Systems

Using of the Internet technology and the field of Fuzzy expert systems has proposed new branches of sharing and distributing knowledge. However, there has been a general lack of investigation in the area of web-based Fuzzy expert systems (FES). In this paper the issues associated with the design, development, and use of web-based FES from a standpoint of the benefits and challenges of developing and using them. The original theory and concepts in conventional FES were reviewed and a knowledge engineering framework for developing them was revisited. Student in an educational place need an educational advisor for solve problems. Some of educational circulars order changing because advisor must update information away. The student's request is linguistic and crisp Expert System cannot solve problems completely. In my approach we build Web-Based Fuzzy Expert System for Student Education Advisor (FES-SEA) and stays in university portal. This system implemented with ASP.NET, SQL-SERVER 2008.

A FUZZY MATCH BASED EXPERT SYSTEM FOR SYNTHESIS OF SEPARATION PROCESSES

A predictive parallel search algorithm,the fuzzy match inference strategy,is implemented ina prototype expert system.Selection of separation technologies and sequencing of separators are beingapproached in an integrated manner.The fuzzy match mechanism results in a relatively smaller subsetof favored schemes,constituting a hyperstructure for further quantitative evaluation and combinationoptimization.An industrial application example of aromatics extraction separation is presented.

A BENCHMARK EXERCISE ON FUZZY SET THEORY BASED EXPERT JUDGEMENT TECHNIQUE

It is sometimes impossible to make a correct decision in a certain engineering task without the help from professional expert judgments. Even though there are different expert opinions available, however, they should be appropriately aggregated to a useful form for making an acceptable engineering decision. This paper proposed a technique which utilizes the fuzzy set theory in the aggregation of expert judgments. In the technique, two main key concepts are employed: linguistic variables and fuzzy numbers. Linguistic variables first represent the relative importance of evaluation criteria under consideration and the degree of confidence on each expert perceived by the decision maker, and then are replaced by suitable triangular fuzzy numbers for arithmetic manipulation. As a benchmark problem, the pressure increment in the containment of Sequoyah nuclear power plant due to reactor vessel breach was estimated to verify and validate the proposed technique.

EXPERT SYSTEM FOR COMPREHENSIVE ASSESSMENT TOBRIDGE SERVICE PROPERTY USING FUZZY THEORY

In this paper, based on consultation to tens of bridge exberts and a vast amount of investigation and study, experts knowledge on bridge assessment has been sorted out. A new concept Damage Value (DV) is put forward to measure bridge damage, and Fuzzy theory is used to create comprehensive Fuzzy system to assess bridge service property. The setup of an experts system for bridge assessment is tried as well. This system is programmed in Turbo C 2.0 and has been run successfully at IBM-PC (AT/XT).

Power Consumption Prediction for an Intelligent Air-Cushion Track Vehicle： Fuzzy Expert System

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.

Knowledge Representation and Fuzzy Reasoning of an Agricultural Expert System

The design scheme of an agricultural expert system based on longan and cauliflower planting techniques is presented. Using an object-oriented design and a combination of the techniques in multimedia, database, expert system and artificial intelligence, an in-depth analysis and summary are made of the knowledge features of die agricultural multimedia expert system and data models involved. According to the practical problems in agricultural field, the architectures and functions of the system are designed, and some design ideas about the hybrid knowledge representation and fuzzy reasoning are proposed.

Possibility Fuzzy Soft Expert Set

In this paper we introduce the concept of possibility fuzzy soft expert set .We also define its basic operations, namely complement, union, intersection, AND and OR, and study some of their properties. Finally, we give an application of this theory in solving a decision making problem.

Analysis of Potential Failure Modes in an Assembly Line by Fuzzy Expert Systems

The failure modes and effects analysis （FMEA） is widely applied in manufacturing industries in various phases of the product life cycle to evaluate the system, its design and processes for failures that can occur. The FMEA team often demonstrates different opinions and these different types of opinions are very difficult to incorporate into the FMEA by the traditional risk priority number model. In this paper, for each of the Occurrence, Severity and Detectivity parameters a fuzzy set is defined and the opinion of each FMEA team members is considered. These opinions are considered simultaneously with weights that are given to each individual based on their skills and experience levels. In addition, the opinion of the costumer is considered for each of the FMEA parameters. Then, the Risk Priority Numbers （RPN） is calculated using a Multi Input Single Output （MISO） fuzzy expert system. The proposed model is applied for prioritizing the failures of Peugeot 206 Engine assembly line in IKCo （Iran Khodro Company）.

A Fuzzy Expert System Architecture for Intelligent Tutoring Systems:A Cognitive Mapping Approach

An Intelligent Tutoring System (ITS) is a computer based instruction tool that attempts to provide individualized instructions based on learner’s educational status. Advances in development of these systems have rose and fell since their emergence. Perhaps the main reason for this is the absence of appropriate framework for ITS development. This paper proposes a framework for designing two main parts of ITSs. Besides development framework, the second main reason for lack of significant advances in ITS development is its development cost. In general, this cost for instructional material is quite high and it becomes more in ITS development. The proposed method can significantly reduce the development cost. The cost reduction mainly is because of characteristics of applied mapping techniques. These maps are human readable and easily understandable by people who are not aware of knowledge representation techniques. The proposed framework is implemented for a graduate course at a technical university in Asia. This experiment provides an individualized instruction which is the main designing purpose of the ITSs.

Fuzzy Logic-Based System for Liver Fibrosis Disease

The diagnosis of liver fibrosis(LF)is crucial as it is a deadly and life-threatening disease.Artificial 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 can.The historical data of a patient’s health can have vagueness,inaccurate,and can also have missing values.The fuzzy logic theory can deal with these issues in the dataset.In this paper,a multilayer fuzzy expert system is developed to diagnose LF.The model is created by using multiple layers of the fuzzy logic approach.This system aids in classifying the health of patients into different classes.The proposed method has two layers,i.e.,layer 1 and layer 2.The input variables used in layer 1 for diagnosing liver fibrosis are Appetite,Jaundice,Ascites,Age,and Fatigue.Similarly,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 albumin.The output variables for this developed system are no damage,minimal damage,significant damage,severe damage,and cirrhosis.This research work also presents the examination of results based on performance parameters.The 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.

Fuzzy Logic Inference System for Managing Intensive Care Unit Resources Based on Knowledge Graph

With the rapid growth in the availability of digital health-related data,there is a great demand for the utilization of intelligent information systems within the healthcare sector.These systems can manage and manipulate this massive amount of health-related data and encourage different decision-making tasks.They can also provide various sustainable health services such as medical error reduction,diagnosis acceleration,and clinical services quality improvement.The intensive care unit(ICU)is one of the most important hospital units.However,there are limited rooms and resources in most hospitals.During times of seasonal diseases and pandemics,ICUs face high admission demand.In line with this increasing number of admissions,determining health risk levels has become an essential and imperative task.It creates a heightened demand for the implementation of an expert decision support system,enabling doctors to accurately and swiftly determine the risk level of patients.Therefore,this study proposes a fuzzy logic inference system built on domain-specific knowledge graphs,as a proof-of-concept,for tackling this healthcare-related issue.The system employs a combination of two sets of fuzzy input parameters to classify health risk levels of new admissions to hospitals.The proposed system implemented utilizes MATLAB Fuzzy Logic Toolbox via several experiments showing the validity of the proposed system.