scholarly journals User Knowledge, Data Modelling, and Visualization: Handling through the Fuzzy Logic-Based Approach

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Xiaoqun Liao ◽  
Shah Nazir ◽  
Yangbin Zhou ◽  
Muhammad Shafiq ◽  
Xuelin Qi
Keyword(s):  
Fuzzy Logic ◽  
Data Structure ◽  
User Modelling ◽  
Experimental Setup ◽  
Data Modelling ◽  
Data User ◽  
Level Of Knowledge ◽  
User Knowledge ◽  
Day By Day ◽  
Web Repository

In modern day technology, the level of knowledge is increasing day by day. This increase is in terms of volume, velocity, and variety. Understanding of such knowledge is a dire need of an individual to extract meaningful insight from it. With the advancement in computer and image-based technologies, visualization becomes one of the most significant platforms to extract, interpret, and communicate information. In data modelling, visualization is the process of extracting knowledge to reveal the detail data structure and process of data. The proposed study aim is to know about the user knowledge, data modelling, and visualization by handling through the fuzzy logic-based approach. The experimental setup is validated through the data user modelling dataset available in the UCI web repository. The results show that the model is effective and efficient in situations where uncertainty and complexity arise.

scholarly journals Rough Set Approach toward Data Modelling and User Knowledge for Extracting Insights

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Xiaoqun Liao ◽  
Shah Nazir ◽  
Junxin Shen ◽  
Bingliang Shen ◽  
Sulaiman Khan
Keyword(s):  
Transfer Function ◽  
Rough Set ◽  
High Performance ◽  
Performance Metrics ◽  
Decision Rules ◽  
Experimental Setup ◽  
Data Modelling ◽  
Knn Classifier ◽  
User Knowledge ◽  
Local Transfer

Information is considered to be the major part of an organization. With the enhancement of technology, the knowledge level is increasing with the passage of time. This increase of information is in volume, velocity, and variety. Extracting meaningful insights is the dire need of an individual from such information and knowledge. Visualization is a key tool and has become one of the most significant platforms for interpreting, extracting, and communicating information. The current study is an endeavour toward data modelling and user knowledge by using a rough set approach for extracting meaningful insights. The technique has used different rough set algorithms such as K-nearest neighbours (KNN), decision rules (DR), decomposition tree (DT), and local transfer function classifier (LTF-C) for an experimental setup. The approach has found its accuracy for the optimal use of data modelling and user knowledge. The experimental setup of the proposed method is validated by using the dataset available in the UCI web repository. Results of the proposed study show that the model is effective and efficient with an accuracy of 96% for KNN, 87% for decision rules, 91% for decision trees, 85.04% for cross validation architecture, and 94.3% for local transfer function classifier. The validity of the proposed classification algorithms is tested using different performance metrics such as F-score, precision, accuracy, recall, specificity, and misclassification rates. For all these performance metrics, the KNN classifier outperformed, and this high performance shows the applicability of the KNN classifier in the proposed problem.

scholarly journals DEVELOPMENT OF A MOBILE APPLICATION FOR LEARNING THE KAZAKH LANGUAGE

2020 ◽  
Vol 72 (4) ◽  
pp. 208-213
Author(s):  
S.K. Kozhakhmet ◽  
◽  
E.P. Makashev ◽  
K.S. Dalbekova ◽  
A.K. Iskakova ◽  
...  
Keyword(s):  
Distance Learning ◽  
Mobile Applications ◽  
Mobile Application ◽  
Mobile App ◽  
Free Time ◽  
Educational Application ◽  
Speed Up ◽  
High Level ◽  
User Knowledge ◽  
Day By Day

During the research, a mobile educational application was developed. Using a mobile app is a key tool for improving user knowledge. The app helps users to study without a teacher in their free time. The app was built using the Xcode IDE. The optional quiz includes many features such as reading, grammar, verbs, and speaking. This will be of great help for users who want to learn more Kazakh. The Kazakh language is developing rapidly. Therefore, the pace of learning the Kazakh language is growing day by day. Currently, it is beneficial to use mobile applications related to distance learning. The application helps to learn the Kazakh language anytime, anywhere. The grammar of the Kazakh language is more complex than other languages. With this in mind, each section of the appendix describes the rules of 1-2 grammars. At the end of each section there is a set of dictionaries to speed up the construction of user sentences. That is, the user who has passed all the sections speaks the Kazakh language at a high level.

scholarly journals Maturity and level of knowledge management in the company: an application of Nonaka and Takeuchi model and Fuzzy Logic

2021 ◽  
Vol 28 (2) ◽  
Author(s):  
Lídia Silveira Arantes ◽  
Orlando Martinelli Junior ◽  
Thales de Oliveira Costa Viegas ◽  
Júlio Eduardo Rohenkoh
Keyword(s):  
Fuzzy Logic ◽  
Knowledge Management ◽  
Fuzzy Sets ◽  
Rio De Janeiro ◽  
Organizational Knowledge ◽  
Minas Gerais ◽  
Sao Paulo ◽  
Management Guidelines ◽  
Level Of Knowledge ◽  
Degree Of Maturity

Abstract: This paper aims to understand how the interconnection between the tacit and explicit dimensions of knowledge impacts knowledge management and its degree of maturity. Knowledge management maturity is understood as the ability firms are expected to have in order to exercise (to some degree) the skills required to manage knowledge internally. Nonaka and Takeuchi (N&T) model of organizational knowledge management was applied to a sample of companies (segmented by size) from the states of São Paulo, Minas Gerais, and Rio de Janeiro, by using the logic of fuzzy sets. The results have shown that small and medium companies have lower levels of knowledge management maturity when compared to large companies. However, in large companies, knowledge management is at medium levels. In this context, this paper suggests, as management guidelines, that companies measure their professionals' perception regarding the company level of knowledge management, pursuing to identify which of their components should be developed.

scholarly journals MODELLING SUPPORT SYSTEMS FOR SELECTING PROFESSIONS FOR APPLICANTS IN THE CONTENT OF PERSONALIZATION OF EDUCATION

2020 ◽  
Vol 2 ◽  
pp. 83-97
Author(s):  
Huseyn Gasimov
Keyword(s):  
Neural Networks ◽  
Fuzzy Logic ◽  
Initial Level ◽  
Knowledge And Skills ◽  
Individual Approach ◽  
Input Layer ◽  
Level Of Knowledge ◽  
The Individual ◽  
High Level ◽  
Education Process

Various methods are currently being used in examining the initial “START” knowledge of applicants and their placement for specialties. Studies show that applicants are placed on the decreasing principle in terms of their overall scores at universities. In this case, applicants with a high level of knowledge are placed in the prestigious specialties as medicine and law as they require high results. Though, while applying for other professions, the applicants do not perform enough results on the key disciplines for the profession, they are placed in those professions when the general results enable it. This causes them to face a number of problems while working both in education process and in the industry. To avoid this problem and to place applicants in a specialty that is more relevant to their level of knowledge, the introduction of an individual approach to the evaluation of initial level of knowledge may be more promising. This article presents a modeling of the "evaluation – placement" support system for the individual approach to assessing applicants' knowledge and positioning them in relevant specialties. The main goal of the system is to give each applicant the opportunity to choose and study the specialty that is more relevant to their knowledge and skills, as well as to analyze the results for each discipline along with the overall results. The system is implemented using fuzzy logic based artificial neural networks. The network consists of 100 neurons in the input layer, two hidden layers and one output layer. The number of neurons at the output is the same as the number of specialties taught at university.

New Trends in Fuzzy Clustering

2013 ◽  
pp. 248-288 ◽  
Author(s):  
Zekâi Sen
Keyword(s):  
Time Series ◽  
Fuzzy Logic ◽  
Fuzzy Clustering ◽  
Social Engineering ◽  
Innovative Cluster ◽  
Earthquake Modeling ◽  
Effective Manner ◽  
Information Problem ◽  
Inference Systems ◽  
Day By Day

Fuzzy methodologies show progress day by day towards better explanation of various natural, social, engineering and information problem solutions in the best, economic, fast and effective manner. This chapter provides cluster analyses from probabilistic, statistical and especially fuzzy methodology points of view by consideration of various classical and innovative cluster modeling and inference systems. After the conceptual assessment explanation of fuzzy logic thinking fundamentals various clustering methodologies are presented with brief revisions but innovative trend analyses as k-mean-standard deviation, cluster regression, relative clustering for depiction of trend components that fall within different clusters. The application of fuzzy clustering methodology is presented for lake time series and earthquake modeling for rapid hazard assessment of existing buildings.

An overview of artificial intelligence applications for power electronics

2020 ◽  
Author(s):  
Shuai Zhao ◽  
Frede Blaabjerg ◽  
Huai Wang
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Fuzzy Logic ◽  
Data Structure ◽  
Power Electronics ◽  
Practical Implementation ◽  
Electronic Systems ◽  
Power Electronic ◽  
Implementation Challenges ◽  
The Common

<div>This is a preprint version of the manuscript submitted to IEEE on June 4, 2020.</div><div><br></div><div>This paper gives an overview of the Artificial Intelligence (AI) applications for power electronic systems. The three distinctive life-cycle phases, design, control, and maintenance are correlated with one or more tasks to be addressed by AI, including optimization, classification, regression, and data structure exploration. The applications of four categories of AI are discussed, which are expert system, fuzzy logic, metaheuristic method, and machine learning. More than 500 publications have been reviewed to identify the common understandings, practical implementation challenges, and research opportunities in the application of AI for power electronics.<br></div>

scholarly journals Advanced optimal by PSO-PI for DC motor

2019 ◽  
Vol 16 (1) ◽  
pp. 165 ◽  
Author(s):  
Salam Waley Jeaeb ◽  
Abbas Zghair Salman ◽  
Qusay A. Jawad ◽  
Haider Shareef
Keyword(s):  
Fuzzy Logic ◽  
Control Strategy ◽  
Fuzzy Logic Controller ◽  
System Simulation ◽  
Dynamic Performance ◽  
Dc Motor ◽  
Drive System ◽  
System Control ◽  
And Control ◽  
Day By Day

<p>Interest in the drive system which used in many applications is increasing day by day. So, many researchers have focused on the analyses, design and control of these systems. In this study, Optimal for Dc motor in drive system control strategy has been proposed for PSO-PI and fuzzy logic controller (FLC) based Dc motor in drive system. In order to test dynamic performance of PSO-PI based drive System, simulation study was carried out by MATLAB/Simulink. The results obtained from the PSO-PI based drive system are not only superior in the rise time, settling time and overshoot but can prevent from voltage and has improved power quality. </p>

Fuzzy Takagi-Sugeno Method in Microcontroller Based Water Tank System

2018 ◽  
Vol 7 (1) ◽  
pp. 1
Author(s):  
Nur Maisarah Mohd Sobran ◽  
Munirah Mohd Salmi ◽  
Mohd Bazli Bahar ◽  
Md Nazri Othman ◽  
Siti Halma Johari
Keyword(s):  
Fuzzy Logic ◽  
Mathematical Modelling ◽  
Real Time ◽  
System Performance ◽  
Fuzzy Logic Controller ◽  
Experimental Setup ◽  
Water Tank ◽  
Tank System ◽  
Initial Idea ◽  
Takagi Sugeno

This paper present the performance of Fuzzy logic controller in maintain level of water in water tank system. The mathematical modelling was developed to get the initial idea of the system performance. Later, the prototype of water tank system were constructed and tested to get the real time results. The Takagi-Sugeno “on” and “off” interference technique method was implemented due to the control limitation of the pump motor that being used in the experimental setup. The fuzzy logic controller was realized by embedded the algorithm in microcontroller of the water tank system. The experimental results show acceptable level of water within the range of 18cm to 20.5cm and settling time 59 seconds with 20 cm set point.

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