4 results for “neuro fuzzy optimization technique”

Set a search alert

Research ArticleOpen accessIn the keywordsA 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 PDF Cite

Research ArticleOpen accessIn the keywordsA 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 PDF Cite

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 PDF Cite

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 PDF Cite