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...

Inverse kinematics of robots is a critical topic in the robotics field. Although there are conventional ways solving inverse kinematics, soft computing an important technology that has lately gained prominence due to its ability reduce complexity problem. This paper presents solution using multiple adaptive neuro-fuzzy inference systems (MANFIS). Different models were established by employing v...

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...

Hand gestures play an important role in communication between people during their daily lives. But the extensive use of hand gestures as a mean of communication can be found in sign languages. Sign language is the basic communication method between deaf people. A translator is usually needed when an ordinary person wants to communicate with a deaf one. The work presented in this paper aims at d...

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

A new algorithm for training radial basis function neural networks is presented in this paper. The algorithm, which is based on the subtractive clustering technique, has a number of advantages compared to the traditional learning algorithms, including faster training times and more accurate predictions. Due to these advantages the method proves suitable for developing discrete-time models for c...

The clustering algorithm hybridization scheme has become of research interest in data partitioning applications in recent years. The present paper proposes a Hybrid Fuzzy clustering algorithm (combination of Fuzzy C-means with extension and Subtractive clustering algorithm) for data classifications applications. The fuzzy c-means (FCM) and subtractive clustering (SC) algorithm has been widely d...

The aim of this paper is to propose an exploratory study on simple, accurate and 19 computationally efficient movement classification technique for prosthetic hand application. The 20 surface myoelectric signals were acquired from 2 muscles – Flexor Carpi Ulnaris and Extensor Carpi 21 Radialis of 4 normal-limb subjects. These signals were segmented and the features extracted using a 22 new comb...

Incorporating solar energy into a grid necessitates an accurate power production forecast for photovoltaic (PV) facilities. In this research, output PV was predicted at hour ahead on yearly basis three different plants based polycrystalline (p-si), monocrystalline (m-si), and thin-film (a-si) technologies over four-year period. Wind speed, module temperature, ambiance, irradiation were among th...

There is an increasing interest in modeling groundwater contamination, particularly geogenic contaminant, on a large scale both from the researcher’s as well as policy maker’s point of view. However, modeling large scale groundwater contamination is very challenging due to the incomplete understanding of geochemical and hydrological processes in the aquifer. Despite the incomplete understanding...