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20 articles for “neuro fuzzy technique”
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Research ArticleOpen accessPhrase in the titleA Genetic Based Neuro Fuzzy Technique for Process Grain Sized Scheduling of Parallel JobsSadasivam Vijayakumar Sudha, Keppanagowder ThanushkodiProblem statement: In this study, we present the development of genetic algorithm based neuro fuzzy technique for process grain sized in scheduling of parallel jobs with the help of real lIfe workload data. Approach: The study uses the rule based scheduling strategy for the scheduling and classIfies all possible scheduling strategies. The rule bases are developed with the help of … …Journal of Computer Science, Vol. 8, Issue 1 · 26 Oct 2011 · 7,339 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleA Neuro Fuzzy Technique for Process Grain Scheduling of Parallel JobsS. V. Sudha, K. ThanushkodiProblem statement: We present development of neural network based fuzzy inference system for scheduling of parallel Jobs with the help of a real life workload data. The performance evaluation of a parallel system mainly depends on how the processes are co scheduled? Various co scheduling techniques available are First Come First Served, Gang Scheduling, Flexible Co Scheduling and Agile Algorithm … …Journal of Computer Science, Vol. 7, Issue 8 · 14 Jul 2011 · 6,457 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleAn Improved Implementation of Brain Tumor Detection Using Segmentation Based on Neuro Fuzzy TechniqueS. Murugavalli, V. RajamaniImplementation of a neuro-fuzzy segmentation process of the MRI data is presented in this study to detect various tissues like white matter, gray matter, csf and tumor. The advantage of hierarchical self organizing map and fuzzy c means algorithms are used to classify the image layer by layer. The lowest level weight vector is achieved by the abstraction level. We … …Journal of Computer Science, Vol. 3, Issue 11 · 30 Nov 2007 · 7,107 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleApplication 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 abstractPrediction of Data Traffic in Telecom Networks based on Deep Neural NetworksQuang Hung Do, Thi Thanh Hang Doan, Thi Van Anh Nguyen et al.Accurate prediction of data traffic in telecom network is a challenging task for a better network management. It advances dynamic resource allocation and power management. This study employs deep neural networks including Long Short-Term Memory (LSTM) and Gated Recurrent Units (GRU) techniques to one-hour-ahead forecast the volume of expected traffic and compares this approach to other methods including Adaptive Neuro-Fuzzy … …Journal of Computer Science, Vol. 16, Issue 9 · 30 Sep 2020 · 8,059 accessesView PDFCite
Research ArticleOpen accessIn the abstractAutomatic Recognition System of Vehicle Plate for Recording Incoming Vehicles to the University Campus and the OutgoingA.A. El-Harby, G.M. Behery, A.A. Al-DhawiAutomatic recognition of vehicle plate characters became a very important in our daily life because of the unlimited increase of vehicles that enter or leave a supervised area. This paper describes an automatic intelligent system that captures the images of vehicles and has the ability to recognize the plates of vehicles entering the university campus or leaving. A camera is … …American Journal of Applied Sciences, Vol. 14, Issue 4 · 12 Apr 2017 · 7,680 accessesView PDFCite
Research ArticleOpen accessIn the abstractSOFT COMPUTING APPROACH TO PREDICT INTRACRANIAL PRESSURE VALUESMario VersaciThe estimation and the prediction of the values related to the Intracranial Pression (ICP) represents an important step for the evaluation of the compliance of the human brain, above all in those cases in which the increase of the ICP values determines high risk conditions for the patient. The regular therapy is neuro-surgical but, waiting for it, it is needed … …American Journal of Applied Sciences, Vol. 11, Issue 5 · 7 Mar 2014 · 6,674 accessesView PDFCite
Research ArticleOpen accessIn the abstractA HYBRID INTELLIGENT MODEL FOR SOFTWARE COST ESTIMATIONWei Lin Du, Luiz Fernando Capretz, Ali Bou Nassif, Danny HoAccurate software development effort estimation is critical to the success of software projects. Although many techniques and algorithmic models have been developed and implemented by practitioners, accurate software development effort prediction is still a challenging endeavor in the field of software engineering, especially in handling uncertain and imprecise inputs and collinear characteristics. In this study, a hybrid intelligent model combining … …Journal of Computer Science, Vol. 9, Issue 11 · 28 Sep 2013 · 7,745 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 abstractOptimal Control Algorithms for Second Order SystemsDanilo Pelusi, Raffaele MascellaProportional Integral Derivative (PID) controllers are widely used in industrial processes for their simplicity and robustness. The main application problems are the tuning of PID parameters to obtain good settling time, rise time and overshoot. The challenge is to improve the timing parameters to achieve optimal control performances. Remarkable findings are obtained through the use of Artificial Intelligence techniques as … …Journal of Computer Science, Vol. 9, Issue 2 · 2 Apr 2013 · 7,029 accessesView PDFCite