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...

Clustering of web user sessions is extremely significant to comprehend their surfing activities on the internet. Users with similar browsing behaviour are grouped together, and further analysis of discovered user groups by domain experts may generate usable and actionable knowledge. In this paper, a conglomerative clustering approach is presented to identify web user session clusters from web s...

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) is presented. Sample audio signals were edited to remove the silent part. Audio signals were divided into frames and represented by its feature. Twelve mel frequency cepstral coefficients ...

Kernelized Fuzzy C-Means clustering technique is an attempt to improve the performance of the conventional Fuzzy C-Means clustering technique. Recently this technique where a kernel-induced distance function is used as a similarity measure instead of a Euclidean distance which is used in the conventional Fuzzy C-Means clustering technique, has earned popularity among research community. Like th...

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...

Üst ekstremite hareketi tam olarak sağlanamadığında, yapay zeka (artificial intelligence/AI) sistemleri kullanıcılara amaçlanan hareketin uygulanması konusunda yardımcı olurlar. Kas aktivitesinin temsili olan elektromiyografi (EMG), sanal gerçeklik uygulamaları ve protez kontrolleri gibi AI-tabanlı sistemlerde kullanıldığında çeşitli faydalar sağlar. Bu çalışmada, bahsedilen sistemlere etkin ko...

An Algorithm to Model Paradigm Shifting in Fuzzy Clustering p. 70 ANFIS Synthesis by Hyperplane Clustering for Time Series Prediction p. 77 Generalized Splitting 2D Flexible Activation Function p. 85 Face Localization with Recursive Neural Networks p. 99 Multi-class Image Coding via EM-KLT Algorithm p. 106 A Face Detection System Based on Color and Support Vector Machines p. 113 A Neural Archit...

Grid integration of Renewable Energy Systems (RES) involves various types power electronics-based converters and inverters. The use these electronic-based devices results in inducing both current voltage harmonics to the grid. In order reduce harmonics, especially for large-scale RES, harmonic forecasting is one many techniques used design mitigation devices. core objective this work develop a ...