Materials Sciences and Applications

Materials Sciences and Applications

ISSN Print: 2153-117X
ISSN Online: 2153-1188
www.scirp.org/journal/msa
E-mail: msa@scirp.org
"Modeling and Optimization of Electrical Discharge Machining of SiC Parameters, Using Neural Network and Non-Dominating Sorting Genetic Algorithm (NSGA II)"
written by Ramezan Ali MahdaviNejad,
published by Materials Sciences and Applications, Vol.2 No.6, 2011
has been cited by the following article(s):
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[2] The influences of spark energy density on the electrical discharge machining (EDM)
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[3] Modeling and optimization of the electrical discharge machining process based on a combined artificial neural network and particle swarm optimization algorithm
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[4] Past and current trends in electric discharge based machining of Silicon Carbide
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[5] Multi-objective Optimization of EDM Process with Performance Appraisal of GA based Algorithms in Neural Network Environment
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[6] Using combined artificial neural network and particle swarm optimization algorithm for modeling and optimization of electrical discharge machining process
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[7] Optimization of Process Parameters of Electrical Discharge Machining Process For Performance Improvement
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[9] Findings of performance evaluation of EDM for different materials of electrodes and work pieces-a review
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[10] HYBRID ARTIFICIAL FISH AND GLOWWORM SWARM OPTIMIZATION ALGORITHM FOR ELECTRICAL DISCHARGE MACHINING OF TITANIUM ALLOY
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[11] Findings of performance evaluation of EDM for different materials of electrodes and work pieces–a review
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[12] OPTIMIZATION OF THE PROCESS CONSTRAINTS IN SPARK EROSION MACHINING OF ALUMINIUM ALLOY AA 6061 HYBRID COMPOSITES USING ARTIFICIAL …
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[13] Prediction of EDM process parameters for AISI 1020 steel using RSM, GRA and ANN
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[14] Experimental Investigation of Process Parameters in Drilling EDM using RSM and ANN in Air Hardened Tool Steel (AISI A2)
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[15] Asian Research Consortium
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[16] Artificial neural network modelling of erosion-abrasion-based hybrid machining of aluminium-silicon carbide-boron carbide composite
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[17] Orthogonal based ANN and multiGA for optimization on WEDM of Ti–48Al intermetallic alloys
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[18] Modeling and Optimization of EDM Process Parameters: A
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[19] Multi Objective Machining Estimation Model Using Orthogonal and Neural Network
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[20] Prediction of EDM Process Parameters for a Composite Material using RBFNN and ANN through RSM
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[21] Parametric Optimization of Wear Behavior of Friction Stir Welded Dissimilar Joints Aluminum Alloys (AA6061–AA6082)
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[22] Studies on some aspects of multi-objective optimization: a case study of electrical discharge machining process
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[23] Parametric Optimization of Electric Discharge Drilling Machine Using Al-SiC Metal Matrix Composite
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[24] MODELING AND OPTIMIZATION OF EDM PROCESS PARAMETERS: A REVIEW
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[25] ADHESIVE WEAR BEHAVIOUR OF ALUMINIUM HYBRID METAL MATRIX COMPOSITES USING GENETIC ALGORITHM
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[26] ANN MODELING AND MULTI OBJECTIVE OPTIMIZATION OF ELECTRICAL DISCHARGE MACHINING PROCESS
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[27] An optimised back propagation neural network approach and simulated annealing algorithm towards optimisation of EDM process parameters
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[28] MODELING AND OPTIMIZATION OF PROCESS PARAMETERS USING NEURAL NETWORKS AND SIMULATED ANNEALING ALGORITHM FOR ELECTRICAL DISCHARGE MACHINING OF AISI2312 HOT WORKED STEEL
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[29] A review of research on improvement and optimization of performance measures for electrical discharge machining
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[30] Application of response surface methodology and genetic algorithm for optimisation of electro–discharge diamond face grinding of tungsten carbide–cobalt composite
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[31] An approach to optimize the EDM process parameters using desirability-based multi-objective PSO
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[32] www. ijera. com 433| P age A Review of Research on Improvement and Optimization of Performance Measures for Electrical Discharge Machining
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[33] Modeling and Optimization of Process Parameters Using Neural Networks and Simulated Algorithm for Electrical Discharge Machining of AISI2312 Hot Worked Steel
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[37] Non-conventional optimization techniques in optimizing non-traditional machining processes: a review
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[38] Multi-objective optimization of process parameters in Electro-Discharge Diamond Face Grinding based on ANN-NSGA-II hybrid technique
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[39] HYBRID MODELING OF PROCESS PARAMETERS PRODUCED BY ELECTRIC DISCHARGE MACHINING USING DIFFERENTIAL EVALUATION AND PARTICLE SWARM OPTIMIZATION
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[40] Multiobjective optimization of slotted electrical discharge abrasive grinding of metal matrix composite using artificial neural network and nondominated sorting genetic algorithm
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[41] A Review on optimization of Dry Electro Discharge Machining Process Parameters
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[42] Application of ANN-NSGA-II hybrid methodology for modeling and optimization of electrical discharge diamond face grinding of tungsten carbide-cobalt (WC-Co) composite
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[43] Assessing/Optimising Bio-fuel Combustion Technologies for Reducing Civil Aircraft Emissions
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[44] Neural Network Modelling and Multi-Objective Optimization of EDM Process
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[45] An intelligent approach for multi-response optimization: a case study of non-traditional machining process
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[46] Application of ANN-NSGA-II hybrid methodology for modeling and optimization of electrical discharge diamond face grinding of tungsten carbide-cobalt (WC-Co) …
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