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.

Fuzzy C-means Clustering algorithm (FCM) is a method that is frequently used in pattern recognition. It has the advantage of giving good modeling results in many cases, although, it is not capable of specifying the number of clusters by itself. In FCM algorithm most researchers fix weighting exponent (m) to a conventional value of 2 which might not be the appropriate for all applications. Conse...

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...

Data clustering is a recognized data analysis method in data mining whereas K-Means is the well known partitional clustering method, possessing pleasant features. We observed that, K-Means and other partitional clustering techniques suffer from several limitations such as initial cluster centre selection, preknowledge of number of clusters, dead unit problem, multiple cluster membership and pre...

Modeling and control of a solar power plant using support vector learning is considered in this work. The model is based on a radial basis function network architecture and uses subtractive clustering and support vector learning to find the parameters and size of the network. To achieve a more interpretable structure the proposed method proceeds in two phases. Firstly, the input-output data is ...

The main focus of the study is to implement and evaluates the DCT based plant leaf disease recognition using subtractive clustering for automatic recognition and classification. The proposed methodology of the study includes image processing and recognition by classification. The method consists of four phases: First, capturing plant leaf disease images and perform color space transformation, i...

The objective of this study was to investigate fuzzy clustering analysis based on subtractive clustering algorithm for modeling of Soil Cation Exchange Capacity (CEC). In this work, seventy soil samples were collected from different horizons of 15 soil profiles located in the Ziaran region, Qazvin province, Iran. The data set was divided into two subsets. One for calibration (80% data) and seco...

Improving Imbalanced Data Classification Accuracy by using Fuzzy Similarity Measure and Subtractive Clustering