Use Of Fuzzy Logic Research Articles

Systematic Literature Review of the Role of Fuzzy Logic in the Development of Cryptographic and Steganographic Techniques

The rapid technological revolution had an impact on a variety of information security techniques. This will be important because information can be confidential to some entities that communicate with each other. Internet in intelligent technology will be a loophole for cryptanalysts to look for information vulnerabilities. Cryptography is a method of securing data and information which is currently still supported by the development of the method. However, the data and information that are secured will still have vulnerabilities in their delivery. The combination of fuzzy logic techniques with cryptographic techniques has been applied to support the improvement of information security. This study applies a systematic literature review method, to find articles that combine the two fields. The purpose of this study is to see the development of information security techniques with a fuzzy logic approach. As a result, it is found that the development of cryptographic and steganographic techniques that utilize fuzzy logic to help improve information security. In addition, the use of fuzzy logic is also not limited to increasing security. Fuzzy logic also plays a role in selecting the best key and password and issuing random numbers from a Pseudo-Random Number Generator (PRNG).

Analysis of Learning Outcomes in Medical Education with the Use of Fuzzy Logic

Abstract The national curricula of the EU member states are structured around learning outcomes, selected according to Bloom’s Taxonomy. The authors of this paper claim that using Bloom’s Taxonomy to phrase learning outcomes in medical education in terms of students’ achievements is difficult and unclear. This paper presents an efficient method of assessing course learning outcomes using Fuzzy Logic.

APPLICATION OF A FUZZY LOGIC SYSTEM TO DETERMINE THE RESOURCE OF AN ASYNCHRONOUS MOTOR

The article analyzes the method for determining the resource of an asynchronous motor through the use of fuzzy logic, explains the structure of the developed Fuzzy Logic System and the results of experiments on determining the resource of an asynchronous motor. The problems that are necessary to solve unambiguously determine the remaining resource of an asynchronous motor are formulated. In this paper, the developed fuzzy logic system will allow us to reasonably determine the residual life of an asynchronous motor based on the results of measuring the no-load current, air gap, insulation resistance, power factor, winding resistance at direct current, stator winding insulation absorption coefficient, stator winding insulation polarization coefficient, insulation modulus, stator temperature and bearing condition assessment. The results obtained during their implementation will help prevent failure of the asynchronous motor and reduce material damage associated with downtime of technological equipment, elimination of the consequences of accidents and repair of the failed electric motor itself. A method for determining the remaining resource of an asynchronous motor is developed using a fuzzy logic system in the Matlab software environment and the FuzzyLogic package. A fuzzy logic system is developed for determining the remaining resource of an asynchronous motor. A detailed study of the results of computer modeling is carried out , which indicate that the fuzzy logic system for determining the remaining resource of an asynchronous motor functions properly and is ready for operation. A fuzzy logic system normalizer is developed for determining the remaining resource of an asynchronous motor. The launch of the file content in the Matlab command line is analyzed in detail, which showed the result of the entire system of non-clear logic at minimum, maximum and average values of control parameters.

Use of Fuzzy Logic for Reconfigurability Assessment in Supply Chain

Use of Fuzzy Logic for Reconfigurability Assessment in Supply Chain

DYNAMICS OF ASYNCHRONOUS ELECTRIC DRIVE WITH PID-SIMILAR FUZZY CONTROLLER FOR WATER SUPPLY SYSTEMS

in presented paper the transient characteristics of an asynchronous electric drive of a pump unit with PID-similar fuzzy controller are investigated. A comparative analysis of control quality in a system with traditional and fuzzy controllers is performed. The use of fuzzy controller in the asynchronous electric drive of the pump unit for water supply system is substantiated and it is proved that the use of fuzzy logic leads to the improvement of the quality of the transient process of the system. The simulation was performed using the Scilab mathematical application package.

Application of fuzzy logic for adaptability and stability studies in flood‐irrigated rice (Oryza sativa)

AbstractThe aim of this study was to use fuzzy logic as an auxiliary tool in the assessment of adaptability and stability, using grain‐yield data from flood‐irrigated rice, evaluated in different agricultural years. Eighteen rice genotypes belonging to flood‐irrigated rice breeding programme were evaluated over four agricultural years, 2012/2013 to 2015/2016, totalling 12 environments (3 sites × 4 years). The methodologies of Eberhart and Russell (1966), Lin and Binns (1988) modified by Carneiro (1998) and Centroid's were used. Fuzzy logic was applied to the results of these methodologies as a tool for interpretation and decision‐making regarding the recommendation of genotypes. Performances of the different flood‐irrigated rice genotypes were influenced by environmental conditions, thereby justifying the use of multiple adaptability and stability methodologies. The use of fuzzy logic in the selection of flood‐irrigated rice genotypes is a useful and promising tool in breeding programmes, allowing information from different parameters to be used to understand the influence of environmental variations on the performance of crop genotypes.

A Mamdani Type Fuzzy Inference System to Calculate Employee Susceptibility to Phishing Attacks

It is a well known fact that the weakest link in a cyber secure system is the people who configure, manage or use it. Security breaches are persistently being attributed to human error. Social engineered based attacks are becoming more sophisticated to such an extent where they are becoming increasingly more difficult to detect. Companies implement strong security policies as well as provide specific training for employees to minimise phishing attacks, however these practices rely on the individual adhering to them. This paper explores fuzzy logic and in particular a Mamdani type fuzzy inference system to determine an employees susceptibility to phishing attacks. To negate and identify the susceptibility levels of employees to social engineering attacks a Fuzzy Inference System FIS was created through the use of fuzzy logic. The utilisation of fuzzy logic is a novel way in determining susceptibility due to its ability to resemble human reasoning in order to solve complex inputs, or its Interpretability and simplicity to be able to compute with words. This proposed fuzzy inference system is based on a number of criteria which focuses on attributes relating to the individual employee as well as a companies practices and procedures and through this an extensive rule base was designed. The proposed scoring mechanism is a first attempt towards a holistic solution. To accurately predict an employees susceptibility to phishing attacks will in any future system require a more robust and relatable set of human characteristics in relation to the employee and the employer.

An Investigation into Conversion of a Fleet of Plug-in-Electric Golf Carts into Solar Powered Vehicles Using Fuzzy Logic Control

This paper presents an investigation factors that need to be considered in the design and selection of components for the conversion of a fleet of plug-in electric golf carts at Princess Nourah Bint Abdelrahman University, (PNU), Riyadh, Kingdom of Saudi Arabia (KSA), into solar power energy. Currently, the plug-in electric golf carts are powered by a set of deep-cycle lead-acid battery packs consisting of six units. Solar energy systems (photovoltaics and solar thermal) provide significant environmental benefits and opportunities over the traditional and conventional sources. Therefore, they can contribute positively to many aspects of the built environment and societies. There are many factors that affect the energy generated from the solar panel system. These include type and dimension of the solar panels, weight, speed, acceleration, and other characteristics of the used golf carts, and the energy efficiency of the solar energy system, as main factors that affect the green energy generated to operate the carts. The energy values needed to power the electric cart were calculated and optimized using traction energy calculation and optimized using a fuzzy logic analysis. The fuzzy logic system was developed to assess the impacts of varying dimensions of solar panel, vehicle speed, and weight on the energy generation. Initial calculations show that the replacement cost of the batteries can be up to approximately 75 percent of the operating cost. Together with the indirect cost benefits of achieving zero tail-pipe emission and the comfort of silent operation, the cost of operation using solar energy can be significant when compared with the cost of battery replacement. In order to achieve better efficiency, supercapacitors can be investigated to replace the conventional batteries. The use of fuzzy logic successfully facilitated the optimization of system operation conditions for best performance. In this study, fuzzy logic and calculated data were used as an optimization tool. Future work may be able to use fuzzy logic with experimental data to demonstrate feasibility of utilizing fuzzy logic systems to assess energy generation processes. Future investigations could also include investigation of other factors and methodologies, such as various types of batteries, supercapacitors, solar panels, and types of golf carts, together with different techniques of artificial intelligence to assess the optimum system specifications.

Learner to Learner Fuzzy Profiles Similarity Using a Hybrid Interaction Analysis Grid

The analysis of remote discussions is not yet at the same level as the face-to-face ones. The present paper aspires twofold. On the one hand, it attempts to establish a suitable environment of interaction and collaboration among learners by using the speech acts via a semi structured synchronous communication tool. On the other, it aims to define behavioral profiles and interpersonal skills hybrid grid by matching the BALES' IPA and PLETY's analysis system. By applying the fuzzy logic, we formalize human reasoning and, thus, giving very appreciable flexibility to the reasoning that use it, which makes it possible to take into account imprecisions and uncertainties. In addition, the educational data mining techniques are used to optimize the mapping of behaviors to learner's profile, with similarity-based clustering, using Eros and PCA measures. In order to show the validity of our system, we performed an experiment on real-world data. The results show, among others: (1) the usefulness of fuzzy logic to properly translate the profile text descriptions into a mathematical format, (2) an irregularity in the behavior of the learners, (3) the correlation between the profiles, (4) the superiority of Eros method to the PCA factor in precision.

Інтелектуальний регулятор запасу газодинамічної стійкості компресора авіаційного ГТД

The gas-dynamic stability of compressors of aircraft gas turbine engines is one of the most important conditions that determine their reliability and level of flight safety. Unstable operation of the compressor in the engine system (surge) leads to loss of thrust accompanied by an increase in gas temperature in front of the turbine and increased vibration because of large amplitudes of pressure pulsations and mass flow through the engine path. To improve the parameters of ACS aviation gas turbine engines are increasingly using regulators built using fuzzy logic algorithms. The implementation of fuzzy control algorithms differs from classical algorithms, which are based on the concept of feedback and reproduce a given functional dependence or differential equation. These functions are related to the qualitative assessment of system behavior, analysis of the current changing situation, and the selection of the most appropriate for the situation supervision of the gas turbine engine. This concept is called advanced management. ACS gas turbine engines with fuzzy regulators are nonlinear systems in which stable self-oscillations are possible. Approximate methods are used to solve the problems of analysis of periodic oscillations in nonlinear systems. Among them, the most developed in theoretical and methodological aspects is the method of harmonic linearization. The scientific problem is solved in the work – methods of synthesis of intelligent control system with the fuzzy regulator as a separate subsystem based on the method of harmonic linearization and design on its basis of fuzzy ACS reserve of gas-dynamic stability of aviation gas turbine engine. Based on the analysis of the principles of construction of fuzzy control systems, it is shown that the use of fuzzy logic provides a new approach to the design of control systems for aviation gas turbine engines in contrast to traditional control methods. It is shown that the fuzzy controller, as the only essentially nonlinear element when using numerical integration methods, can be harmonically linearized. Harmonic linearization allows using the oscillation index to assess the quality in the separate channels of fuzzy ACS aviation gas turbine engines. A fuzzy expert system has been developed for optimal adjustment of the functions of belonging of typical fuzzy regulators according to quality criteria to transients.

Differential Evolution with Shadowed and General Type-2 Fuzzy Systems for Dynamic Parameter Adaptation in Optimal Design of Fuzzy Controllers

This work is mainly focused on improving the differential evolution algorithm with the utilization of shadowed and general type 2 fuzzy systems to dynamically adapt one of the parameters of the evolutionary method. Previously, we have worked with both kinds of fuzzy systems in different types of benchmark problems and it has been found that the use of fuzzy logic in combination with the differential evolution algorithm gives good results. In some of the studies, it is clearly shown that, when compared to other algorithms, our methodology turns out to be statistically better. In this case, the mutation parameter is dynamically moved during the evolution process by using shadowed and general type-2 fuzzy systems. The main contribution of this work is the ability to determine, through experimentation in a benchmark control problem, which of the two kinds of the used fuzzy systems has better results when combined with the differential evolution algorithm. This is because there are no similar works to our proposal in which shadowed and general type 2 fuzzy systems are used and compared. Moreover, to validate the performance of both fuzzy systems, a noise level is used in the controller, which simulates the disturbances that may exist in the real world and is thus able to validate statistically if there are significant differences between shadowed and general type 2 fuzzy systems.

UJAmI Location: A Fuzzy Indoor Location System for the Elderly

Due to the large number of elderly people with physical and cognitive issues, there is a strong need to provide indoor location systems that help caregivers monitor as many people as possible and with the best quality possible. In this paper, a fuzzy indoor location methodology is proposed in a smart environment based on mobile devices and Bluetooth Low Energy (BLE) beacons where a set of Received Signal Strength Indicators (RSSI) is received by mobile devices worn by the inhabitants. The use of fuzzy logic and a fuzzy linguistic approach is proposed to deal with the imprecise nature of the RSSI values, which are influenced by external factors such as radio waves, causing significant fluctuations. A case study carried out at the Smart Lab of the University of Jaén (UJAmI Smart Lab) is presented to demonstrate the effectiveness of the proposed methodology, where our proposal is compared with a non-fuzzy logic approach, obtaining an accuracy of 91.63%, approximately 10 points higher than the methodology without using fuzzy logic. Finally, our theoretical proposal is accompanied by a description of the UJAmI Location system, which applies the theory to the functionality of locating elderly people in indoor environments.

Environment humidity and temperature prediction in agriculture using Mamdani inference systems

<span>This paper presents the results of a humidity and temperature prediction model in the environment for agriculture, using diffuse sets and optimizing their parameters by heuristic methods, such as genetic algorithms, and exact methods such as Quasi-Newton. It has been identified that non-specialized users could have difficulties in understanding the system dynamics and the behavior of variables over time. The aim of this research is obtain models with a high level of interpretability and accuracy that allows predicting the temperature and humidity values for the environment. The use of fuzzy logic to present a solution has great advantages as this system is highly rated for interpretability. Furthermore, by relating the obtained values for environment humidity and temperature to qualitative categories as high, medium or low, it allows non-specialized users to have a better understanding of the system dynamics. Two optimization techniques are applied to two different diffuse sets that allow the prediction of the humidity and temperature. It is found that the best implementation involves a Mamdani fuzzy inference system optimized with Quasi-Newton algorithm that uses a set of initial values attained through a previous optimization process with a genetic algorithm.</span>

Fuzzy Technologies Modeling the Level of Welfare of the Population in the System of Effective Management

Purpose: The article aims to present the use of fuzzy technologies to model the welfare of the population in the system of effective management of the country's economy. In particular, the aim was to develop an approach to assessing the welfare of the country's population based on the use of fuzzy logic and fuzzy set theory. Design/Methodology/Approach: The paper deals with the procedure of fuzzy assessment of the welfare level of the country's population. The expert approach to forming a system of six partial indicators, the value of which is taken into account when calculating the level of welfare of the country's population, is used. After selecting the set of primary indicators, their value is reduced to a fuzzy form. We next find the magnitude of the original integral index of this level in a fuzzy form. Finally, we define the precise value of this integral index, which corresponds to its fuzzy form. Findings: The results obtained indicate the effectiveness of the socio-economic policy of the state during the study period, which resulted in a significant improvement in the welfare of the population of Ukraine despite social and economic instability. Practical Implications: The results obtained indicate the effectiveness of the socio-economic policy of the state during the study period, which resulted in a significant improvement in the welfare of the population of Ukraine despite social and economic instability. Originality/Value: The assessment of the level of welfare of the population, which is based on the use of the theory of fuzzy logic and fuzzy sets and the possibility of taking into account in the calculations of these quantitative and qualitative primary factors that shape this welfare.

MODELLING OF TIME, COST AND RISK OF CONSTRUCTION WITH USING FUZZY LOGIC

The paper presents an overview of the literature from recent years devoted to planning the time, costs and risk of a construction investment using fuzzy logic. It also presents three own original models concerning the issue. The first model is used to build a fuzzy construction schedule taking into account fuzzy norms and the number of workers. The costing model uses fuzzy inference from CBR cases. The aim was to increase the accuracy and correctness of the cost calculation performed for the investor in the construction and investment process with a certain degree of vagueness of the available information about materials. In the last of the presented models, fuzzy sets were used to assess the effects of technological and construction (implementation) risk factors. The presented examples prove the usefulness of fuzzy logic in solving problems in construction, where we have incomplete and imprecise information.

Engineering Inspection Associated Artificial Intelligence for Appraisal of the Property in Niteroi, Rio de Janeiro, Brazil

The construction sector is linked to the general development of a country. There is a lot of data scattered and not properly explored in relation to the buildings constructed. However, if these scattered data on the behavior of the real estate market are organized, combined with knowledge of civil engineering, this merger of information can mitigate some evaluation problems, especially those that are overvalued for unknown or dubious reasons. Thus, there is a need for models capable of working with limited data to analyze the causal relationships between explanatory variables and sales prices and, from there, predict property values. The purpose of this article is the innovative use of simple building inspection strategies to predict the market price for residential apartments. For this, 19 samples of residential apartments are used in the city of Niterói, Rio de Janeiro, Brazil, in February 2021. The methodology uses the results of the survey of civil engineering and converts them into heuristic terms predicting the price of the property. With this, the imprecision, uncertainty, and subjectivity of human expression combined with the knowledge of civil engineering result in a plausible solution and easy application in the market. Finally, the use of fuzzy logic in the evaluation of properties is an adequate unconventional method, in addition to avoiding repetition in regression coefficients in binary logic. To check the reliability of the method, the comparison between the market values of the samples and the values predicted by the fuzzy logic is used. The result according to the mean absolute percentage error (MAPE) can be interpreted as a good result (7%).

A Fuzzy Recommendation System for the Automatic Personalization of Physical Rehabilitation Exercises in Stroke Patients

Stroke is among the top 10 leading causes of death and disability around the world. Patients who suffer from this disease usually perform physical exercises at home to improve their condition. These exercises are recommended by therapists based on the patient’s progress level, and may be remotely supervised by them if technology is an option for both. At this point, two major challenges must be faced. The first one is the lack of specialized medical staff to remotely handle the growing number of stroke patients. The second one is the difficulty of dynamically adapt the patient’s therapy plan in real time whilst they rehabilitate at home, since their evolution varies as the rehabilitation process progresses. In this context, we present a fuzzy system that is able to automatically adapt the rehabilitation plan of stroke patients. The use of fuzzy logic greatly facilitates the monitoring and guidance of stroke patients. Moreover, the system is capable of automatically generating modifications of existent exercises whilst considering their particularities at any given time. A preliminary experiment was conducted to show the advantages of the proposal, and the results suggest that the application of fuzzy logic may help make correct decisions based on the patient’s progress level.

A Fuzzy Model to Manage Water in Polymer Electrolyte Membrane Fuel Cells

In this paper, a fuzzy model is presented to determine in real-time the degree of dehydration or flooding of a proton exchange membrane of a fuel cell, to optimize its electrical response, and, consequently, its autonomous operation. By applying load, current, and flux variations in the dry, normal, and flooded states of the membrane, it was determined that the temporal evolution of the fuel cell voltage is characterized by changes in slope and by its voltage oscillations. The results were validated using electrochemical impedance spectroscopy and show slope changes from 0.435 to 0.52 and oscillations from 3.6 to 5.2 mV in the dry state, and slope changes from 0.2 to 0.3 and oscillations from 1 to 2 mV in the flooded state. The use of fuzzy logic is a novelty and constitutes a step towards the progressive automation of the supervision, perception, and intelligent control of fuel cells, allowing them to reduce their risks and increase their economic benefits.

FEATURES OF DESIGNING FUZZY REGULATORS IN THE COMPOSITION OF AUTOMATIC CONTROL SYSTEMS OF SEMICONDUCTOR COMPENSATORS

The article discusses the design features of fuzzy controllers as part of automatic control systems for semiconductor compensators. Tendencies to the use of fuzzy logic and neural networks to solve problems with a large number of variables that are random are analyzed. The functional scheme of the automatic control system on the basis of fuzzy logic is considered. Some features of the fuzzy regulator are given. Questions of optimization of parameters of digital fuzzy controllers are investigated. The importance of the choice of the method of parametric adjustment of the fuzzy controller is shown. The options for choosing the quality criterion for fuzzy controllers are considered. The market of commercial software products for working with fuzzy logic is analyzed.

Estimation of cost overrun in construction projects using Fuzzy Logic

In recent years, the impact of the construction industry on the economy of India is increasing. However, there are a number of problems that are being faced by the construction companies or contractors or other relevant stakeholders, in the completion of a construction project. One of the major problems being faced is time and cost overrun. Thus, it is important to find ways of mitigating this critical problem. One of the solutions that is being used is the prediction of the amount and time that a project might overrun beforehand i.e. estimating the overrun during the design phase itself. This prediction can be done using a number of different techniques, the important one of which used in this paper is through the use of Fuzzy Logic. It also provides a brief description about the factors that are responsible for causing this cost overrun. The factors are identified by conducting a questionnaire survey and gathering responses from the relevant stakeholders which include contractors, project engineers, architects and consultants. The responses collected are further processed and analysed using SPSS software. The top 5 factors have been selected after the analysis and further used in preparation of the fuzzy logic model in the fuzzy toolbox of MATLAB. Further, the validation of this model has been done with real-time data of projects from various published research papers. Thus, the model developed provided prediction of the percentage of the cost overrun based on the percentage input of the top five factors.