Fuzzy Logic Theory and Applications in Uncertainty Management of Linguistic Evaluations for Students

Mapping Intimacies ◽

10.4018/978-1-7998-6878-1.ch013 ◽

2022 ◽

pp. 243-266

Author(s):

Ashu M. G. Solo ◽

Madan M. Gupta

Keyword(s):

Decision Making ◽

Fuzzy Logic ◽

Uncertainty Management ◽

Computing With Words ◽

Linguistic Variables ◽

Database Queries ◽

Computational Theory ◽

Fuzzy Math ◽

Fuzzy Database ◽

Fuzzy Logic Theory

Fuzzy logic can deal with information arising from perception and cognition that is uncertain, imprecise, vague, partially true, or without sharp boundaries. Fuzzy logic can be used for assigning linguistic grades and for decision making and data mining with those linguistic grades by teachers, instructors, and professors. Many aspects of fuzzy logic including fuzzy sets, linguistic variables, fuzzy rules, fuzzy math, fuzzy database queries, computational theory of perceptions, and computing with words are useful in uncertainty management of linguistic evaluations for students. This chapter provides many examples of this after describing the theory of fuzzy logic.

Download Full-text

Applying Fuzzy Logic and Fuzzy Methods to Marketing

Supply Chain Management ◽

10.4018/978-1-4666-2625-6.ch062 ◽

2012 ◽

pp. 1056-1068

Author(s):

Laurent Donzé ◽

Andreas Meier

Keyword(s):

Fuzzy Logic ◽

Customer Relationship Management ◽

Relationship Management ◽

Customer Relationship ◽

Future Research ◽

Computing With Words ◽

Linguistic Variables ◽

Research Directions ◽

Fuzzy Methods ◽

Future Research Directions

Marketing deals with identifying and meeting the needs of customers. It is therefore both an art and a science. To bridge the gap between art and science, soft computing, or computing with words, could be an option. This chapter introduces fundamental concepts such as fuzzy sets, fuzzy logic, and computing with linguistic variables and terms. This set of fuzzy methods can be applied in marketing and customer relationship management. In the conclusion, future research directions are given for applying fuzzy logic to marketing and customer relationship management.

Download Full-text

Computing with words using intuitionistic fuzzy logic programming

International Journal of Engineering & Technology ◽

10.14419/ijet.v7i1.9.9815 ◽

2018 ◽

Vol 7 (1.9) ◽

pp. 178 ◽

Cited By ~ 1

Author(s):

Ashit Kumar Dutta

Keyword(s):

Fuzzy Logic ◽

Natural Language ◽

Language Processing ◽

Heavy Traffic ◽

Computing With Words ◽

Computational Theory ◽

Machine Perception ◽

Intuitionistic Fuzzy Logic ◽

Better Than ◽

Real World Problems

Computing with words is the terminology to indicate a set of numbers and words.It is the base for natural language processing and computational theory of perceptions.It is the art to combine both human and machine perception and find a solution for the real world problems left unsolved due to improper mechanism.Animal voice interpreter, lie detector, driving a vehicle in heavy traffic, and natural language interpreter are the applications need to be automated for the next generation.The computational theory is a group of perceptions used to express propositions in a natural language.The concept of the research is to utilize intutionistic fuzzy logic to interpret perceptions to solve vague problems.The output of the research shows that the performance of proposed method is better than the existing methods.

Download Full-text

UAV Flight Safety System Based on Fuzzy Logic

Transactions on Aerospace Research ◽

10.2478/tar-2020-0022 ◽

2020 ◽

Vol 2020 (4) ◽

pp. 71-80

Author(s):

Anastasiia Shcherban ◽

Volodymyr Ieremenko

Keyword(s):

Decision Making ◽

Fuzzy Logic ◽

Battery Life ◽

Flight Safety ◽

Linguistic Variables ◽

Free Flight ◽

Linguistic Terms ◽

Current Voltage ◽

Aerial Vehicle ◽

Input Variables

AbstractThe article proposes a method of deciding on the continuation or termination of the UAV flight on the basis of fuzzy logic to ensure its trouble-free flight, which will be used in the future to build an onboard monitoring system of the power supply of the unmanned aerial vehicle. The developed method of decision-making allows to determine the residual battery life on the basis of data on current voltage, battery temperature, temperature on board the UAV and the direction and strength of the wind, using which the computer system will make recommendations for continuing or terminating the UAV flight task. The method of decision-making using fuzzy logic involves the formation of linguistic variables, which are the input information parameters and the output decision, their linguistic terms and membership functions, as well as a system of rules for decision-making. The voltage at the output of the battery, its surface temperature and the wind direction on board the UAV were used as input variables, and the residual battery life was used as the output linguistic variable.

Download Full-text

Estimation of the comprehension criterion for rule base in fuzzy logic theory sistems

Azerbaijan Oil Industry ◽

10.37474/0365-8554/2021-1-35-36 ◽

2021 ◽

pp. 35-36

Author(s):

N.E. Adilova ◽

Keyword(s):

Decision Making ◽

Fuzzy Logic ◽

Knowledge Acquisition ◽

Management System ◽

Rule Base ◽

A Value ◽

Fuzzy Logic Theory

The paper deals with the estimation of comprehension criterion for the rule base in the fuzzy logic theory systems. The conception level of management system for the user is defined with a value due to the comprehension criterion. It allows using properly in the issues of decision-making and knowledge acquisition as well.

Download Full-text

Behavioural Aspects of the Financial Decision-Making

Organizacija ◽

10.2478/orga-2019-0003 ◽

2019 ◽

Vol 52 (1) ◽

pp. 22-31 ◽

Cited By ~ 12

Author(s):

Katarina Valaskova ◽

Viera Bartosova ◽

Pavol Kubala

Keyword(s):

Decision Making ◽

Fuzzy Logic ◽

Financial Management ◽

Decision Making Process ◽

Linguistic Variables ◽

Behavioural Finance ◽

Financial Decision Making ◽

Economic Decision Making ◽

Financial Decision ◽

Behavioural Aspects

Abstract Background and Purpose: Behavioural finance is a relatively new, but rapidly evolving field that provides explanations of an economic decision-making by cognitive psychology, conventional economic and financial theory. Behavioural finance searches the influence of psychology on the behaviour of financial practitioners and the subsequent effects on the financial markets. The purpose of the paper is the research on behavioural aspects of financial decision-making as they help explain why and how markets might be inefficient. Design/Methodology/Approach: Fuzzy logic is an excellent tool for working with linguistic variables that are often found when working with behavioural data. Thus, we analyse the financial decision-making process from the perspective of behavioural finance aimed at better understanding of the decision-making process of investors applying the principles of fuzzy logic to solve various financial problems. Results: The results of the study indicate that fuzzy logic is applicable when solving problems of financial management and financial decision-making problems. The urgency of the fuzzy logic application for managerial and financial decisions should be emphasized. Research in this area indicates that in some cases, as in the case of behavioural financing, the use of fuzzy logic is far more suitable than the use of other methods (Peters, Aguiar and Sales). Conclusion: The novelty of the paper is to extend the application of fuzzy sets in the area of financial decision-making. The paper demonstrates that despite the fact, that fuzzy logic is currently used mainly in technical directions, it is applicable also in financial management, especially, in cases where it is necessary to consider the influence of human and the occurrence of linguistic variables.

Download Full-text

Improving Decision-Making in a Business Simulator Using TOPSIS Methodology for the Establishment of Reactive Stratagem

Advances in Data Mining and Database Management - Web Data Mining and the Development of Knowledge-Based Decision Support Systems ◽

10.4018/978-1-5225-1877-8.ch002 ◽

2017 ◽

pp. 12-21

Author(s):

Carlos Alberto Ochoa Ortiz Zezzatti

Keyword(s):

Decision Making ◽

Fuzzy Logic ◽

Group Decision Making ◽

Hydraulic Excavator ◽

Linguistic Variables ◽

Topsis Method ◽

High Productivity ◽

Construction Company ◽

Quantitative Studies ◽

Expert’S Opinion

This study combines Fuzzy Logic and multicriteria TOPSIS method for the selection, from three different alternatives, which machines of high productivity is more convenient to a construction company. The evaluation of each alternative is made through group decision making which identifies the most important criteria according to the requirements presented by the company. To assess the selected criteria in the TOPSIS method is weighted by a group of experts who, based on their experience and knowledge of this type of machinery, assess the relevance of these in the operation and functioning of the hydraulic excavator. Both qualitative and quantitative studies are used in this work, however the experts evaluate, through surveys based on Likert scale all the criteria in which they want to measure the perception. Data provided from the surveys is used for the construction and association of the groups of expert's opinion through the use of fuzzy sets to avoid ambiguity problems of the linguistic variables.

Download Full-text

Applying Fuzzy Logic and Fuzzy Methods to Marketing

Fuzzy Methods for Customer Relationship Management and Marketing ◽

10.4018/978-1-4666-0095-9.ch001 ◽

2012 ◽

pp. 1-14 ◽

Cited By ~ 1

Author(s):

Laurent Donzé ◽

Andreas Meier

Keyword(s):

Fuzzy Logic ◽

Customer Relationship Management ◽

Relationship Management ◽

Customer Relationship ◽

Future Research ◽

Computing With Words ◽

Linguistic Variables ◽

Research Directions ◽

Fuzzy Methods ◽

Future Research Directions

Download Full-text

ALGORITHM FOR USING FUZZY LOGIC IN MANAGEMENT AND DECISION-MAKING MODELS

Collection of scientific works of the Military Institute of Kyiv National Taras Shevchenko University ◽

10.17721/2519-481x/2020/69-08 ◽

2020 ◽

pp. 75-81

Author(s):

V.A. Druzhynin ◽

M.M. Stepanov ◽

G.B. Zhyrov ◽

L.O. Rіaba

Keyword(s):

Decision Making ◽

Fuzzy Logic ◽

Complex Systems ◽

Mathematical Formulation ◽

Control Process ◽

External Factors ◽

Linguistic Variables ◽

Control Actions ◽

Decision Making Models ◽

Fuzzy Logical

In real conditions, when the task of formally describing the control process of a rather complex process arises, it is necessary to take into account several external factors (parameters) and their values, which potentially tend to Infinity. At the same time, the system's response is not limited to just one control action. To automate the process of composing all possible combinations of linguistic descriptions of variables at the stage of fuzzy conditional statements and the decision-making mechanism on the use of control actions in the development of control and decision-making models, it is proposed to use fuzzy logical models. Ways to construct algorithms for converting input perturbations of complex systems into conceptual relations for automating the control process and supporting decision-making are considered. The fuzzy logic apparatus relation is used to formalize, process, and make decisions about the use of system control signals in response to external disturbances. Fuzzy control systems combine information from human experts (natural language) with measurements and mathematical models. Fuzzy Systems will turn the knowledge base into a mathematical formulation that has proven very effective in many applications. When designing a fuzzy system, many questions need to be answered, in particular in creating linguistic models to describe the functioning of complex systems, in particular radar mapping systems with recognition of objects on the ground and making decisions for controlling unmanned systems. Thus, at the stage of composing a set of fuzzy instructions (statements), it is of interest to formalize the following processes, such as determining all possible combinations of terms of linguistic variables and making a decision on the application of control actions, depending on external factors. In the process of formalizing the process of determining all possible combinations and terms of linguistic variables, it is necessary to create fuzzy instructions (rules) for managing a system or object for fuzzy-logical control models and decision-making in the process of developing models for the functioning of complex systems.

Download Full-text

Design and Simulation of Smart Control System for Internet Traffic Distribution on Servers by Using Fuzzy Logic System

Al-Kitab Journal for Pure Sciences ◽

10.32441/kjps.v2i1.138 ◽

2018 ◽

Vol 2 (1) ◽

Author(s):

Raid Daoud ◽

Yaareb Al-Khashab

Keyword(s):

Fuzzy Logic ◽

Control System ◽

Input Parameter ◽

Traffic Density ◽

The Internet ◽

Linguistic Variables ◽

Internet Service ◽

Traffic Distribution ◽

Smart Control ◽

High Level

The internet service is provided by a given number of servers located in the main node of internet service provider (ISP). In some cases; the overload problem was occurred because a demand on a given website goes to very high level. In this paper, a fuzzy logic control (FLC) has proposed to distribute the load into the internet servers by a smart and flexible manner. Three effected parameters are tacked into account as input for FLC: link capacity which has three linguistic variables with Gaussian membership function (MF): (small, medium and big), traffic density with linguistic variables (low, normal and high) and channel latency with linguistic variables (empty, half and full); with one output which is the share server status (single, simple and share). The proposed work has been simulated by using MATLAB 2016a, by building a structure in the Fuzzy toolbox. The results were fixed by two manners: the graphical curves and the numerical tables, the surface response was smoothly changed and translates the well-fixed control system. The numerical results of the control system satisfy the idea of the smart rout for the incoming traffics from the users to internet servers. So, the response of the proposed system for the share of server ratio is 0.122, when the input parameter in the smallest levels; and the ratio is 0.879 when the input parameters are in highest level. The smart work and flexible use for the FLC is the main success solution for most of today systems control.

Download Full-text