This paper focuses on an analysis of demand response in a smart grid context, presenting the model considerations and architecture. Domestic consumption is divided into groups in order to cover the adequate modeling. A fuzzy subtractive clustering method is applied to demand response on several domestic consumption scenarios and results analyses are presented. The demand response developed mode...

Speaker identification is the computing task to identify an unknown identity based on the voice. A good speaker identification system must have a high accuracy rate to avoid invalid identity. Despite of last few decades’ efforts, accuracy rate in speaker identification is still low. In this paper, we propose a hybrid approach of unsupervised and supervised learning i.e. subtractive clustering a...

This paper presents the simulation of audio surveillance system in a public transport vehicle that detects event like screams and gunshots by classifying signals as normal or in crisis condition using adaptive neuro fuzzy inference system (ANFIS). Audio signals were divided into frames and represented by its feature. Feature is extracted using mel frequency cepstral coefficients. Eight audio fi...

Pyrite oxidation, Acid Rock Drainage (ARD) generation, and associated release and transport of toxic metals are a major environmental concern for the mining industry. Estimation of the metal loading in ARD is a major task in developing an appropriate remediation strategy. In this study, an expert system, the Multi-Output Adaptive Neuro-Fuzzy Inference System (MANFIS), was used for estimation of...

This paper presents an adaptive neuro-fuzzy inference system (ANFIS) for USD/JPY exchange rates forecasting. Previous work often used time series techniques and neural networks (NN). ANFIS can be used to better explain solutions to users than completely black-box models, such as NN. The proposed neurofuzzy rule based system applies some technical and fundamental indexes as input variables. In o...

Supplier selection is a key task for firms, enabling them to achieve the objectives of a supply chain. Selecting a supplier is based on multiple conflicting factors, such as quality and cost, which are represented by a multi-criteria description of the problem. In this article, a new approach based on Adaptive Neuro-Fuzzy Inference System (ANFIS) is presented to overcome the supplier selection ...

This Article describes the perspective analysis and study on Pattern Recognition of the Retinal Nerve Fibers. The articles published in recent years are considered for observing the analytical techniques as well as approaches used for implementing the image-based processes of our Proposed System. The various Process Implementation Systems play important role for obtaining the accuracy in the pe...

This paper presents a diagnosis system, based on an adaptive neuro-fuzzy inference system (ANFIS) algorithm, for applications in biomedical fields. This paper deals specifically with skin cancer diagnosis. Our system can be divided into two main parts: feature selection, using the Greedy feature flip algorithm (G-flip), and Classification method using ANFIS algorithm. The ANFIS algorithm could ...

In this paper, subtractive clustering based fuzzy inference system approach is used for early detection of faults in the function oriented software systems. This approach has been tested with real time defect datasets of NASA software projects named as PC1 and CM1. Both the code based model and joined model (combination of the requirement and code based metrics) of the datasets are used for tra...

In this paper, subtractive clustering based fuzzy inference system approach is used for early detection of faults in the function oriented software systems. This approach has been tested with real time defect datasets of NASA software projects named as PC1 and CM1. Both the code based model and joined model (combination of the requirement and code based metrics) of the datasets are used for tra...