Creation of Fuzzy Control Table with Data Mining

2013 ◽  
Vol 760-762 ◽  
pp. 1080-1083
Author(s):  
Jun Gao
Keyword(s):  
Data Mining ◽  
Control System ◽  
Fuzzy Control ◽  
Control Systems ◽  
Association Rule ◽  
New Method ◽  
Data Mining Techniques ◽  
Fuzzy Control System

A good fuzzy control table is the key to a fuzzy control system, and the systems performance mainly depends on the quality of the table. Based on analyzing fully the principles of a typical fuzzy control systems and the procedures of building a fuzzy control table, this paper presents a new method of applying the boolean association rule data mining techniques to mining of fuzzy control table directly from the database of manual operating records.

The Ni-MH Power Battery Electrode Material Admixture Process Fuzzy Control System

2014 ◽  
Vol 887-888 ◽  
pp. 497-500
Author(s):  
Guang Jun Ma ◽  
Shuo Wu ◽  
Ya Dong Gong
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Electrode Material ◽  
Good Control ◽  
Fuzzy Control System ◽  
Power Battery ◽  
Battery Electrode

In the Ni-MH power battery electrodes manufacturing, the quality of the electrode material admixture will affect electrode and the whole function of batteries directly. However, the electrode material admixture process is very complex. It is very difficult to build up a model of precision to carry on control to the system. The traditional electrode material admixture control of the process, mainly according to develop the personnel on trial and the spot experience to complete, That method basically can not reach the good control appearance. The Fuzzy control can resolve the problem of this complication nicely.

Simulation and Application of Fuzzy Control System with Integrator

2011 ◽  
Vol 418-420 ◽  
pp. 1825-1828
Author(s):  
Ping Li ◽  
Chang Feng Yan ◽  
Ling Ke Zeng ◽  
Xiao Su Cheng
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Control Systems ◽  
Practical Experience ◽  
System Stability ◽  
Static Error ◽  
Fuzzy Control System ◽  
Simulation Results ◽  
The Stability

This article simulated fuzzy control system by using MATLAB and compared the normal fuzzy control system with the fuzzy control system which has an integrator. Further more, the influence of quantize factors, proportional factors and integral constants on system was studied. The simulation results show that static error always exists in normal fuzzy control systems and proportional factors influence the stability of the system greatly. Put an integrator into a fuzzy control system, and static error can be eliminated and the system stability can be improved. The conclusion of simulation and practical experience, use fuzzy control system with integrator in reality. It can get good results.

scholarly journals ANALISIS POLA PERMINTAAN PUBLIKASI DATA BADAN PUSAT STATISTIK MENGGUNAKAN ASSOCIATION RULE APRIORI

2020 ◽  
Vol 7 (2) ◽  
pp. 187
Author(s):  
Farid Ridho ◽  
Fachruddin Mansyur
Keyword(s):  
Data Mining ◽  
Association Rule ◽  
Web Usage Mining ◽  
Mining Method ◽  
Data Mining Techniques ◽  
Web Usage ◽  
Usage Patterns ◽  
Mining Association Rule ◽  
The Web

<p><em>BPS is a data provider body in Indonesia. In publishing, BPS uses a variety of media, one of which is the BPS website. To get data through the BPS website, users can visit the website then download the data they need. The services obtained by data users on the BPS website depend on the quality of the website. The better the quality, the better the service experience gained by data users. The method that can be used to improve the quality of a website is the web usage mining method. Web usage mining is the application of data mining techniques on web repositories to study usage patterns. The purpose of this study is to determine the pattern of data publication requests on the BPS website which can later be used as a reference to improve the quality of BPS website services. Based on the results of the study, it was found that data users tend to access the same data with different years simultaneously. For results by grouping data by title without year, obtained quite diverse rules.</em></p><p><em><strong>Keywords</strong></em><em>: </em><em>web usage mining, association rule, apriori</em></p><p><em>BPS merupakan badan penyedia data di Indonesia. Dalam mempublikasikan datanya, BPS menggunakan berbagai media, salah satunya adalah website BPS. Untuk mendapatkan data melalui website BPS, pengguna dapat mengunjungi website kemudian mengunduh data yang mereka butuhkan. Layanan yang didapatkan oleh pengguna data pada website BPS tergantung dari kualitas website tersebut. Semakin baik kualitasnya, semakin baik pula pengalaman pelayanan yang didapatkan oleh pengguna data. Metode yang dapat digunakan untuk meningkatkan kualitas suatu website adalah metode web usage mining. Web usage mining merupakan penerapan tekhnik data mining pada web repositori untuk mempelajari pola penggunaan</em><em>. </em><em>Tujuan dari penelitian ini adalah untuk mengetahui pola permintaan publikasi data pada website BPS yang nantinya dapat digunakan sebagai acuan untuk meningkatkan kualitas layanan website BPS. Berdasarkan hasil penelitian, didapatkan bahwa pengguna data cenderung mengakses data yang sama dengan tahun yang berbeda secara bersamaan. Untuk hasil dengan mengelompokan data berdasarkan judul tanpa tahun, diperoleh rules yang cukup beragam.</em></p><p><em><strong>Kata kunci</strong></em><em>: </em><em>web usage mining, association rule, apriori</em></p>

Computer Simulations for Design and Optimization of a Fuzzy Control System

1994 ◽  
Author(s):  
Dean B. Edwards ◽  
John R. Canning ◽  
Anthony de Sam Lazaro
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Control Systems ◽  
Computer Simulations ◽  
Fuzzy Systems ◽  
Linear Control ◽  
Control Problems ◽  
Trial And Error ◽  
Fuzzy Control System ◽  
Design And Optimization

Abstract The use of fuzzy logic in control systems is becoming increasingly popular as a method of handling non-linear control problems. The design of fuzzy systems is generally undertaken using intuition and a trial-and-error approach for tuning. A system so developed may be less than optimum as no accepted evaluation norms are available. In this paper a generic method to design and to optimize a fuzzy control system is developed. The results of computer simulations of a system constructed using this technique are submitted and discussed. The experimental verification of the method is presented.

The Temperature and Humidity Based on the Embedded Implementation of Fuzzy Control System

2011 ◽  
Vol 58-60 ◽  
pp. 749-754
Author(s):  
Jun Zhang
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Control Systems ◽  
Humidity Control ◽  
Fuzzy Control System ◽  
Temperature And Humidity ◽  
Cut Set ◽  
Transition Rules ◽  
And Control ◽  
Embedded Implementation

For the characteristics and needs of temperature and humidity control in current industrial environment, the paper proposes a fuzzy-based embedded temperature and humidity control system，which enables consumers monitor and control temperature and humidity parameters through the PDA when moving. The article first introduces the hardware structure of the temperature and humidity fuzzy control system, then based on the theory of fuzzy set and the fuzzy number operations of l - cut set, focusing on the transition rules of fuzzy controlling fuzzy conditions of the temperature and humidity control systems, and finally introduce the key technologies of embedded software system of the PDA,. The experimental results show that the system is very practical and flexible.

The Spinning Quality Control Management Based on Decision Making by Data Mining Techniques

2018 ◽  
Vol 7 (1) ◽  
pp. 72
Author(s):  
Khalid AA Abakar ◽  
Chongwen Yu
Keyword(s):  
Data Mining ◽  
Kernel Functions ◽  
Support Vector ◽  
Ann Model ◽  
Data Mining Techniques ◽  
Yarn Quality ◽  
Yarn Properties ◽  
Svm Model ◽  
Rbf Kernel

This work demonstrated the possibility of using the data mining techniques such as artificial neural networks (ANN) and support vector machine (SVM) based model to predict the quality of the spinning yarn parameters. Three different kernel functions were used as SVM kernel functions which are Polynomial and Radial Basis Function (RBF) and Pearson VII Function-based Universal Kernel (PUK) and ANN model were used as data mining techniques to predict yarn properties. In this paper, it was found that the SVM model based on Person VII kernel function (PUK) have the same performance in prediction of spinning yarn quality in comparison with SVM based RBF kernel. The comparison with the ANN model showed that the two SVM models give a better prediction performance than an ANN model.

Design and Implementation of a Fuzzy Control System Applied to a 6 × 4 SRG

2021 ◽  
Vol 57 (1) ◽  
pp. 528-536
Author(s):  
Ghunter Paulo Viajante ◽  
Eric Nery Chaves ◽  
Luis Carlos Miranda ◽  
Marcos Antonio A. de Freitas ◽  
Carlos Antunes de Queiroz ◽  
...  
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Fuzzy Control System ◽  
Design And Implementation
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