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23 results for “neural fuzzy systems”
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Research ArticleOpen accessIn the abstractDevelopment of Priority Oriented Scheduling Method to Increase the Reliability of Manufacturing SystemsSeyedehfarzaneh Nojabaei, Z. Leman, S. H. Tang, S. SulaimanScheduling occurs in every organization without considering the nature of its activities. In this regard, numerous scholars have attempted to schedule via divergent methods including classical scheduling, genetic algorithm, neural network and fuzzy logic and so on. Studies in manufacturing scheduling mostly deal with priority rules without any consideration of the system states. An appropriate scheduling leads to significant enhancement … …American Journal of Applied Sciences, Vol. 9, Issue 9 · 31 Jul 2012 · 7,015 accessesView PDFCite
Research ArticleOpen accessIn the abstractApplication of Adaptive Neuro-Fuzzy Inference System for Information SecuirtyAltyeb Altaher, Ammar Almomani, Sureswaran RamadassProblem statement: Computer networks are expanding at very fast rate and the number of network users is increasing day by day, for full utilization of networks it need to be secured against many threats including malware, which is harmful software with the capability to damage data and systems. Fuzzy rule based classification systems considered as an active research area in … …Journal of Computer Science, Vol. 8, Issue 6 · 23 Apr 2012 · 7,747 accessesView PDFCite
Research ArticleOpen accessIn the abstractDermoscopic Image Segmentation using Machine Learning AlgorithmL. Padma Suresh, K.L. Shunmuganathan, S.H. Krishna VeniProblem statement: Malignant melanoma is the most frequent type of skin cancer. Its incidence has been rapidly increasing over the last few decades. Medical image segmentation is the most essential and crucial process in order to facilitate the characterization and visualization of the structure of interest in medical images. Approach: This study explains the task of segmenting skin lesions in … …American Journal of Applied Sciences, Vol. 8, Issue 11 · 7 Oct 2011 · 7,342 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 abstractUsing an Adaptative Fuzzy-Logic System to Optimize the Performances and the Reduction of Chattering Phenomenon in the Control of Induction MotorM. M. Krishan, L. Barazane, A. KhwaldehProblem statement: Neural networks and fuzzy inference systems are becoming well-recognized tools of designing an identifier/controller capable of perceiving the operating environment and imitating a human operator with high performance. Also, by combining these two features, more versatile and robust models, called “neuro-fuzzy” architectures have been developed. The mo Approach: Motivation behind the use of neuro-fuzzy approaches was based on … …American Journal of Applied Sciences, Vol. 7, Issue 1 · 31 Jan 2010 · 7,523 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 abstractData-Driven Forecasting Schemes: Evaluation and ApplicationsJosip Vrbanek Jr, Wilson WangA reliable multi-step predictor is very useful to a wide array of applications to forecast the behavior of dynamic systems. The objective of this paper is to develop a more robust data-driven predictor for time series forecasting. Based on simulation analysis, it is found that multi-step-ahead forecasting schemes based on step inputs perform better than those based on sequential inputs. … …Journal of Computer Science, Vol. 3, Issue 9 · 30 Sep 2007 · 6,565 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordOptimal 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
Research ArticleOpen accessAll words, across the recordA 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 accessAll words, across the recordImplementation and Evaluation of Evolutionary Connectionist Approaches to Automated Text SummarizationUday Kulkarni, Rajesh Shardanand PrasadProblem statement: Text summarization takes care of choosing the most significant portions of text and generates coherent summaries that express the main intent of the given document. This study aims to compare the performances of the three text summarization systems developed by the authors with some of the existing Summarization systems available. These three approaches to text summarization are based … …Journal of Computer Science, Vol. 6, Issue 11 · 23 Oct 2010 · 8,489 accessesView PDFCite