IKTINOS: An Expert Mathematical Model for the Restoration of the Wall Faces of the Parthenon, using Fuzzy Logic Techniques

2009 ◽  
Author(s):  
L.S. Vamvakeridou-Lyroudia
Keyword(s):  
Mathematical Model ◽  
Fuzzy Logic

Theoretical Investigation of a Structure for Active Vibration Control with Fuzzy Logic Approach

2014 ◽  
Vol 598 ◽  
pp. 529-533
Author(s):  
Erdi Gülbahçe ◽  
Mehmet Çelik ◽  
Mustafa Tinkir
Keyword(s):  
Mathematical Model ◽  
Fuzzy Logic ◽  
Vibration Control ◽  
Modal Analysis ◽  
Prediction Models ◽  
Block Diagram ◽  
Active Vibration Control ◽  
Control Block ◽  
Inference System ◽  
Active Vibration

The main purpose of this study is to prepare mathematical model for active vibration control of a structure. This paper presents the numerical and experimental modal analysis of aluminum cantilever beam in order to investigate the dynamic characteristics of the structure. The results will be used for active vibration control of structure’s experimental setup. Experimental natural frequencies are obtained and compared to verify the proposed numerical model by using modal analysis results. MATLAB System Identification Toolbox and ANSYS harmonic response function are used together to estimate beam’s equations of motion which include its amplitude, frequency and phase angle values. Moreover, the mathematical model of beam is simulated in MATLAB/Simulink software to determine the dynamic behavior of the proposed system. Furthermore, another prediction model approach with multiple input and single output is used to find the realistic behavior of beam via an adaptive neural-network-based fuzzy logic inference system, in addition, impulse responses of the proposed models are compared and the control block diagram for active vibration control is implemented. As a first iteration, PID type controller is designed to suppress vibrations against the disturbance input. The results of modal analysis, the prediction models, controlled and uncontrolled system responses are presented in graphics and tables for obtaining a sample numerical active vibration control.

scholarly journals Using fuzzy logic for evaluating the level of countries’ (regions’) economic development

2012 ◽  
Vol 59 (3) ◽  
pp. 293-310 ◽  
Author(s):  
Gordan Stojic
Keyword(s):  
Mathematical Model ◽  
Economic Development ◽  
Fuzzy Logic ◽  
Developed Countries ◽  
Gdp Per Capita ◽  
Industrial Growth ◽  
The Poor ◽  
The World ◽  
Level Of Economic Development ◽  
Per Capita

There are several divisions of countries and regions in the world. Besides geo-political divisions, there also are economic divisions. The most common economic division is the that on developed countries and the poor ones. These divisions are a consequence of the level of: GDP, GDP per capita, unemployment rate, industrial growth, and so on. The question is how to define a mathematical model based on which the following will be assessed: who is rich and who is poor, or who is economically developed and who is not? How the boundaries of transition from one category to another can be defined? This paper presents a model for evaluating the level of economic development of countries and regions using "fuzzy" logic. The model was tested on a sample of 19 EU member countries and aspirants for membership.

scholarly journals Fuzzy Win-Win: A Novel Approach to Quantify Win-Win Using Fuzzy Logic

2021 ◽  
Author(s):  
Ahmad B. Hassanat ◽  
Ghada A. Altarawneh ◽  
Ahmad S. Tarawneh
Keyword(s):  
Mathematical Model ◽  
Fuzzy Logic ◽  
Iron Ore ◽  
Real Life ◽  
The Other ◽  
Uranium Enrichment ◽  
Single Product ◽  
Novel Approach

Abstract The classic win-win has a key flaw in that it cannot offer the parties with right amounts of winning because each party believes they are winners. In reality, one party may win more than the other. This strategy is not limited to a single product or negotiation; it may be applied to a variety of situations in life. We present a novel way to measure the win-win situation in this paper. The proposed method employs the Fuzzy logic to create a mathematical model that aids negotiators in quantifying their winning percentages. The model is put to the test on real-life negotiation scenarios such as the Iranian uranium enrichment negotiations, the Iraqi-Jordanian oil deal, and the iron ore negotiation (2005-2009). The presented model has shown to be a useful tool in practice and can be easily generalized to be utilized in other domains as well.

scholarly journals DEVELOPMENT OF A SYSTEM FOR ASSESSING PASSENGER TRAFFIC BASED ON FUZZY LOGIC

2020 ◽  
Vol 4 ◽  
pp. 18-21
Author(s):  
Olha Pronina
Keyword(s):  
Mathematical Model ◽  
Fuzzy Logic ◽  
Public Transport ◽  
Fuzzy Inference ◽  
Technical Condition ◽  
Time Of Day ◽  
Output Variable ◽  
Passenger Traffic ◽  
Transportation Service ◽  
The City

A methodology has been developed for assessing public transport passenger traffic in the city. A mathematical model based on fuzzy logic is presented. The main criteria for assessing the attractiveness of passenger traffic are: the interval between vehicles, technical condition of the vehicle, route length, time of day. In the mathematical model, all input linguistic variables and output variable, their terms and membership functions are described. A fragment of a fuzzy knowledge base presented in the form of production rules is presented. At the exit, the dispatcher receives an output variable – the degree of confidence in the attractiveness of the route. Based on this assessment, the dispatcher can make a number of necessary changes to improve the functioning of the route. The software is implemented as a web service. This software will be convenient for dispatchers to use for planning public transport routes. Fifteen selected routes were taken for research, which are the most popular in the city. These routes were proposed for evaluation by three controllers. The results obtained from dispatchers were compared with the results of the fuzzy inference implemented in the software. The main advantage of using this software product is the ability to build a dynamic schedule based on the analysis of the dispatcher. This, in turn, will allow passengers to receive a better transportation service within the city

Application of Fuzzy Logic and Fuzzy Optimization Techniques in Medical Image Processing

Biometrics ◽  
2017 ◽  
pp. 907-932 ◽  
Author(s):  
Niladri Sekhar Datta ◽  
Himadri Sekhar Dutta ◽  
Koushik Majumder
Keyword(s):  
Mathematical Model ◽  
Fuzzy Logic ◽  
Optimization Technique ◽  
Fuzzy Optimization ◽  
Fuzzy Model ◽  
Optimization Method ◽  
Fuzzy Modeling ◽  
Optimization Techniques ◽  
Fuzzy Variables ◽  
Truth Value

Fuzzy logic deals with approximate rather than fixed and exact reasoning. Fuzzy variables may have a truth value that ranges in degree between 0 and 1; extended to handle the concept of partial truth where the truth value may range between completely true or completely false. This computational logic uses truth degrees as a mathematical model of the vagueness phenomenon while probability is a mathematical model of ignorance. A huge number of complex problems may be solve using Fuzzy logic specifically Fuzzy modeling and optimization method. Fuzzy modeling is the understanding of the problem and analysis of the Fuzzy information where the Fuzzy optimization solves Fuzzy model optimally using optimization techniques via membership functions. In this research article authors describe the Fuzzy rules and its application and the different types of well known problems solved by the Fuzzy optimization technique.

scholarly journals MATHEMATICAL ALGORITHM OF FUZZY LOGIC CONTROLLER FOR MULTILEVEL INVERTER CREATING VERTICAL DIVIDED VOLTAGE

2019 ◽  
Vol 59 (1) ◽  
pp. 1-11 ◽  
Author(s):  
Erol Can
Keyword(s):  
Mathematical Model ◽  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Pid Controller ◽  
Output Voltage ◽  
Fuzzy Logic Controller ◽  
Boost Converter ◽  
Multilevel Inverter ◽  
Logic Control ◽  
Multi Level

A 9-level inverter with a boost converter has been controlled with a fuzzy logic controller and a PID controller for regulating output voltage applications on resistive (R) and inductive (L), capacitance (C). The mathematical model of this system is created according to the fuzzy logic controlling new high multilevel inverter with a boost converter. The DC-DC boost converter and the multi-level inverter are designed and explained, when creating a mathematical model after a linear pulse width modulation (LPWM), it is preferred to operate the boost multi-level inverter. The fuzzy logic control and the PID control are used to manage the LPWM that allows the switches to operate. The fuzzy logic algorithm is presented by giving necessary mathematical equations that have second-degree differential equations for the fuzzy logic controller. After that, the fuzzy logic controller is set up in the 9-level inverter. The proposed model runs on different membership positions of the triangles at the fuzzy logic controller after testing the PID controller. After the output voltage of the converter, the output voltage of the inverter and the output current of the inverter are observed at the MATLAB SIMULINK, the obtained results are analysed and compared. The results show the demanded performance of the inverter and approve the contribution of the fuzzy logic control on multi-level inverter circuits.

scholarly journals Determination of the type of repair work based on the results of survey and monitoring of the technical condition of buildings

2020 ◽  
Vol 157 ◽  
pp. 06023 ◽  
Author(s):  
Aleksandr Birjukov ◽  
Anatoly Lebedkin ◽  
Yurii Birjukov ◽  
Viktor Pchelkin
Keyword(s):  
Mathematical Model ◽  
Fuzzy Logic ◽  
Set Theory ◽  
Fuzzy Set Theory ◽  
Technical Condition ◽  
Capital Investments ◽  
Repair Work ◽  
Fuzzy Logic Method ◽  
Maintenance Work

This article is devoted to structural scrutiny of a building. The technical condition of buildings affects such characteristics of a building as safety, reliability, durability and maintainability. However, in the absence of reliable information on the technical condition of buildings, structural survey or monitoring of а building in order to determine the category of technical condition is necessary. The purpose of this work is to develop an economic and mathematical model for determining the type of maintenance work based on the results of structural scrutiny and monitoring of a building. The article is of importance because the final stage of the survey gives a qualified opinion on the level of structural scrutiny of a building, and on the basis of this opinion repair work eliminating physical and moral deterioration and providing in accordance with specifications renovation of the building are planned. The scientific novelty of the economic and mathematical model developed by the authors on the results of building structural scrutiny lies in the application of the fuzzy set theory and fuzzy logic method for determining of the level of physical and moral deterioration of a building consistent with a certain type of repair work and followed by the necessary capital investments.

Artificial intelligence with fuzzy logic system for learning management evaluation in higher educational systems

2020 ◽  
pp. 1-11
Author(s):  
ZhiYuan Lv ◽  
Hengyun Shen
Keyword(s):  
Artificial Intelligence ◽  
Mathematical Model ◽  
Fuzzy Logic ◽  
Evaluation System ◽  
Learning Experience ◽  
Training Model ◽  
Colleges And Universities ◽  
Teaching Evaluation ◽  
Higher Learning ◽  
The Mathematical Model

In this paper, the mathematical model and algorithm based on knowledge forgetting curve are studied. Through the analysis of the current mathematical modeling and application of “knowledge forgetting curve”, the artificial intelligence method of fuzzy mathematics knowledge and differential modeling is adopted. This paper puts forward the mathematical model and algorithm design of the new “knowledge forgetting curve”, which aims to improve the intelligence of the software and bring a new learning experience for the teaching evaluation of the education system in colleges and universities. The fuzzy logic theory is applied to the teaching evaluation system of higher learning pedagogy, according to pedagogy and other related theories, combined with the current teaching evaluation indicators of colleges and universities, the teaching evaluation indicators of higher learning education are set according to certain requirements. The sample wood data is divided into two parts by using the fuzzy logic principle, and the training model is obtained by training the sample data in the evaluation system, and the training model is used to intelligently evaluate and analyze the prediction data.

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