Intrusion Detection System (IDS) provides additional security for the most vulnerable Mobile Adhoc Networks (MANET). Use of Fuzzy Inference System (FIS) in the design of IDS is proven to be efficient in detecting routing attacks in MANETs. Clustering is a vital means in the detection process of FIS based hybrid IDS. This study describes the design of such a system to detect black hole attack in...

In this paper, Neuro-Fuzzy based Fuzzy Subtractive Clustering Method (FSCM) and Self Tuning Fuzzy PD-like Controller (STFPDC) were used to solve non-linearity and trajectory problems of pitch AND yaw angles of Twin Rotor MIMO system (TRMS). The control objective is to make the beams of TRMS reach a desired position quickly and accurately. The proposed method could achieve control objectives wit...

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 ...

This paper proposes a new hybrid method named SCFE-PNN, which integrates effective subtractive clustering based features enhancement and probabilistic neural network (PNN) classifier, had been introduced for isolated Malay word recognition. The proposed method of subtractive clustering features weighting is used as a data preprocessing tool, which designs at diminishing the divergence in featur...

The Chiu’s method which generates a Takagi-Sugeno Fuzzy Inference System (FIS) is a method of fuzzy rules extraction. The rules output is a linear function of inputs. In addition, these rules are not explicit for the expert. In this paper, we develop a method which generates Mamdani FIS, where the rules output is fuzzy. The method proceeds in two steps: first, it uses the subtractive clustering...

The design of a support vector machine with Gaussian kernels is considered for modeling nonlinear processes. The structure is equivalent to a neuro-fuzzy system based on radial basis function network considering some restrictions. To improve the interpretability and reduce the complexity of the structure a hybrid learning scheme is proposed. First, the input-output data is supervised clustered ...

Speaker identification is the process of determining which registered speaker provides a given utterance. Speaker identification required to make a claim on the identity of speaker from the Ns trained speaker in its user database. In this study, we propose the combination of clustering algorithm and the classification technique – subtractive and Radial Basis Function (RBF). The proposed techniq...

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...