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31 results for “ANFIS”
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Research ArticleOpen accessIn the keywordsQualitative 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 keywordsIntelligent 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 accessIn the keywordsA REVIEW OF INTELLIGENT CONTROL SYSTEMS APPLIED TO THE INVERTED-PENDULUM PROBLEMPedro Ponce, Arturo Molina, Eugenio AlvarezThis study shows the latest advances in the application of intelligent control to the inverted-pendulum problem. A complete review regarding intelligent control design is presented in this study in order to show the most important artificial intelligence methods used for controlling an Inverted-Pendulum. Also this study proposed the use of a neural-fuzzy-with-genetic-algorithms controller for the inverted pendulum problem which gives … …American Journal of Engineering and Applied Sciences, Vol. 7, Issue 2 · 7 Apr 2014 · 8,379 accessesView PDFCite
Research ArticleOpen accessIn the keywordsDuctility Performance of Hybrid Fibre Reinforced ConcreteS. Eswari, P.N. Raghunath, K. SugunaThis study presents a study on the ductility performance of hybrid fibre reinforced concrete. The influence of fibre content on the ductility performance of hybrid fibre reinforced concrete specimens having different fibre volume fractions was investigated. The parameters of investigation included modulus of rupture, ultimate load, service load, ultimate and service load deflection, crack width, energy ductility and deflection ductility. … …American Journal of Applied Sciences, Vol. 5, Issue 9 · 30 Sep 2008 · 7,290 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimization-Based Feature Selection and Ensemble Machine Learning Algorithms for Breast Cancer ClassificationSatyabrata Patro, Jyotirmaya Mishra, Bhavani Sankar PandaBreast cancer, which originates in a woman's breast tissue, is acknowledged to be a significant study topic in the medical field. For a long time, there has been a serious concern with the classification of breast cancer. Thus, to effectively categorize the breast cancer dataset, machine learning methods are designed and implemented. In previous research, the algorithms have classification accuracy … …Journal of Computer Science, Vol. 21, Issue 7 · 17 Jul 2025 · 3,172 accessesView PDFCite
Research ArticleOpen accessIn the abstractImprovement of Rooftop Solar Panels Efficiency using Maximum Power Point Tracking Based on an Adaptive Neural Network Fuzzy Inference SystemI Made Ari Nrartha, I Made Ginarsa, Agung Budi Muljono et al.Rooftop solar panels are a strategy for achieving Indonesia's renewable energy goals, but their non-linear characteristics make them difficult to control, especially in the face of extreme weather changes. An effective controller is needed to optimize the power output of solar panels. This study proposes a Maximum Power Point Tracking (MPPT) controller based on an Adaptive Neural network Fuzzy Inference … …American Journal of Engineering and Applied Sciences, Vol. 16, Issue 1 · 19 Jan 2023 · 5,769 accessesView PDFCite
Research ArticleOpen accessIn the abstractHydrological Forecasting Using Hybrid Data-Driven ApproachYoungmin Seo, Sungwon KimThis study develops a hybrid model, EEMD-FANN, coupling feed Forward Artificial Neural Network (FANN) and Ensemble Empirical Mode Decomposition (EEMD) for improving the accuracy of daily river stage forecasting. An original river stage data is broken down into a residue and Intrinsic Mode Functions (IMFs) using the EEMD and different FANNs are developed as forecasting models for the decomposed IMFs … …American Journal of Applied Sciences, Vol. 13, Issue 8 · 2 Sep 2016 · 8,136 accessesView PDFCite
Research ArticleOpen accessIn the abstractA 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
Research ArticleOpen accessIn the abstractApplication of Neuro-Fuzzy Techniques for Solar RadiationW. A. Rahoma, U. Ali Rahoma, A. H. HassanProblem statement: The prediction is very useful in solar energy applications because it permits to estimate solar data for locations where measurements are not available. The developed artificial intelligence models predict the solar radiation time series more effectively compared to the conventional procedures based on the clearness index. Approach: The forecasting ability of some models could be further enhanced with … …Journal of Computer Science, Vol. 7, Issue 10 · 11 Aug 2011 · 7,077 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