Tool Condition Monitoring Using the TSK Fuzzy Approach Based on Subtractive Clustering Method

نویسندگان

  • Qun Ren
  • Marek Balazinski
  • Luc Baron
  • Krzysztof Jemielniak
چکیده

This paper presents a tool condition monitoring approach using Takagi-Sugeno-Kang (TSK) fuzzy logic incorporating a subtractive clustering method. The experimental results show its effectiveness and satisfactory comparisons with several other artificial intelligence methods.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Improving Imbalanced data classification accuracy by using Fuzzy Similarity Measure and subtractive clustering

 Classification is an one of the important parts of data mining and knowledge discovery. In most cases, the data that is utilized to used to training the clusters is not well distributed. This inappropriate distribution occurs when one class has a large number of samples but while the number of other class samples is naturally inherently low. In general, the methods of solving this kind of prob...

متن کامل

Anfis based on quantum subtractive clustering yielded good approximation and generalization capabilities and impressive decrease in the number of fuzzy rules and network

Data mining techniques can be used to discover useful patterns by exploring and analyzing data and it’s feasible to synergistically combine machine learning tools to discover fuzzy classification rules. In this paper, an adaptive neuro fuzzy network with TSK fuzzy type and an improved quantum subtractive clustering has been developed. Quantum clustering (QC) is an intuition from quantum mechani...

متن کامل

Prediction of slope stability using adaptive neuro-fuzzy inference system based on clustering methods

Slope stability analysis is an enduring research topic in the engineering and academic sectors. Accurate prediction of the factor of safety (FOS) of slopes, their stability, and their performance is not an easy task. In this work, the adaptive neuro-fuzzy inference system (ANFIS) was utilized to build an estimation model for the prediction of FOS. Three ANFIS models were implemented including g...

متن کامل

Sensitivity Analysis for Type-1 and Type-2 Tsk Fuzzy Models

In this paper, subtractive clustering method is combined with least squares estimation algorithms to pre-identify a type-1 Takagi-Sugeno-Kang (TSK) fuzzy model from input/output data. Then the type-2 fuzzy theory is used to expand the type-1 model to a type-2 model. A sensitivity analysis is used to ascertain how a type-1 TSK model output depends upon the pre-initialized parameters and determin...

متن کامل

Design of Fuzzy Subtractive Clustering Model using Particle Swarm Optimization for the Permeability Prediction of the Reservoir

Permeability is the key parameter of the reservoir and has a significant impact on petroleum fields operations and reservoir management. In most reservoirs, permeability measurements are rare and therefore permeability must be measured in the laboratory from reservoir core samples or evaluated from well test data. However, core analysis and well test data are usually only available from a few w...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2008