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17 results for “Adaptive Neuro-Fuzzy Inference System (ANFIS)”
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Research ArticleOpen accessIn the abstractNEURO FUZZY BASED PERFORMANCE ANALYSIS OF MULTIBAND ULTRA WIDE BAND ORTHOGONAL FREQUENCY DIVISION MULTIPLEXING SYSTEMG. Joselin Retna Kumar, K. S. ShajiThis study proposes an efficient channel-estimation scheme for Multiband (MB) Orthogonal Frequency Division Multiplexing (OFDM)-based Ultra Wide Band (UWB) communication systems. One of the challenges in wireless system is the frequency selective fading caused due to multipath channel between the transmitter and receiver. The signal bandwidth in broad band cellular wireless systems typically exceeds the coherence bandwidth of the multipath … …Journal of Computer Science, Vol. 10, Issue 8 · 5 Mar 2014 · 6,616 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdaptive Neuro-Fuzzy Inference System-Particle Swarm Optimization Based Stability Maintenance of Power System NetworksR. Latha, J. KanakarajDuring faulty condition voltage instability is one of the major crisis in power system networks. This study proposes a hybrid learning algorithm to improve the stability performance of a power system with Distributed Generations (DGs). Here the distribution system stability is maintained with reduced power loss using an Adaptive Neuro-Fuzzy Inference Systems (ANFIS) and Particle Swarm Optimization (PSO) techniques. In … …American Journal of Applied Sciences, Vol. 10, Issue 8 · 24 Jul 2013 · 6,906 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdaptive Neuro-Fuzzy Inference System Approach for the Automatic Screening of Diabetic Retinopathy in Fundus ImagesS. Kavitha, K. DuraiswamyProblem statement: Diabetic retinopathy is one of the most significant factors contributing to blindness and so early diagnosis and timely treatment is particularly important to prevent visual loss. Approach: An integrated approach for extraction of blood vessels and exudates detection was proposed to screen diabetic retinopathy. An automated classifier was developed based on Adaptive Neuro-Fuzzy Inference System (ANFIS) to differentiate … …Journal of Computer Science, Vol. 7, Issue 7 · 28 Jun 2011 · 6,785 accessesView PDFCite
Research ArticleOpen accessIn the abstractPredicting Packet Transmission Data over IP Networks Using Adaptive Neuro-Fuzzy Inference SystemsSamira Chabaa, Abdelouhab ZeroualProblem statement: The statistical modeling for predicting network traffic has now become a major tool used for network and is of significant interest in many domains: Adaptive application, congestion and admission control, wireless, network management and network anomalies. To comprehend the properties of IP-network traffic and system conditions, many kinds of reports based on measured network traffic data have been … …Journal of Computer Science, Vol. 5, Issue 2 · 28 Feb 2009 · 7,533 accessesView PDFCite
Research ArticleOpen accessIn the abstractQualitative Ferromagnetic Hysteresis ModelingM. Mordjaoui, M. Chabane, B. Boudjema, R. DairaIn determining the electromagnetic properties of magnetic materials, hysteresis modeling is of high importance. Many models are available to investigate those characteristics but they tend to be complex and difficult to implement. A new qualitative hysteresis model for ferromagnetic core presented, based on the function approximation capabilities of adaptive neuro-fuzzy inference system (ANFIS). The proposed ANFIS model combined the neural … …Journal of Computer Science, Vol. 3, Issue 6 · 30 Jun 2007 · 7,076 accessesView PDFCite
Research ArticleOpen accessIn the abstractIntelligent Control for Self-erecting Inverted Pendulum Via Adaptive Neuro-fuzzy Inference SystemA. A. Saifizul, Z. Zainon, N. A.Abu Osman et al.A self-erecting single inverted pendulum (SESIP) is one of typical nonlinear systems. The control scheme running the SESIP consists of two main control loops. Namely, these control loops are swing-up controller and stabilization controller. A swing-up controller of an inverted pendulum system must actuate the pendulum from the stable position. While a stabilization controller must stand the pendulum in the … …American Journal of Applied Sciences, Vol. 3, Issue 4 · 30 Apr 2006 · 7,322 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordA New Self-Adaptive Neuro Fuzzy Inference System for the Removal of Non-Linear Artifacts from the Respiratory SignalA. Bhavani Sankar, D. Kumar, K. SeethalakshmiProblem statement: In this study, a new ANFIS-based adaptive filter is proposed to remove the non-linear artifacts from the respiratory signal measured using MEMS based accelerometer sensor. The data recorded from the abdomen movement includes the respiratory signal, electromyogram, 50Hz power line interference and the random electrode noise. In order to avoid convergence into local extremes, the system employs ANFIS … …Journal of Computer Science, Vol. 8, Issue 5 · 16 Feb 2012 · 6,891 accessesView PDFCite