Search results for "Back propagation neural network"

showing 3 items of 3 documents

Neural networks for the diagnostics of gas turbine engines

1996

The paper describes the activities carried out for developing and testing Back Propagation Neural Networks (BPNN) for the gas turbine engine diagnostics. One of the aims of this study was to analyze the problems encountered during training using large number of patterns. Each pattern contains information about the engine thermodynamic behaviour when there is a fault in progress. Moreover the research studied different architectures of BPNN for testing their capability to recognize patterns even when information is noised. The results showed that it is possible to set-up and optimize suitable and robust Neural Networks useful for gas turbine diagnostics. The methods of Gas Path Analysis furn…

Back propagation neural networkGas turbinesEngineeringArtificial neural networkNeural computerbusiness.industryDiagonalControl engineeringEncryptionbusiness
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Krill herd algorithm-based neural network in structural seismic reliability evaluation

2018

ABSTRACTIn this research work, the relative displacement of the stories has been determined by means of a feedforward Artificial Neural Network (ANN) model, which employs one of the novel methods for the optimization of the artificial neural network weights, namely the krill herd algorithm. For the purpose of this work, the area, elasticity, and load parameters were the input parameters and the relative displacement of the stories was the output parameter. To assess the precision of the feedforward (FF) model optimized using the Krill Herd Optimization (FF-KH) algorithm, comparison of results has been performed relative to the results obtained by the linear regression model, the Genetic Alg…

Computer scienceGeneral Mathematics02 engineering and technologyBack propagation neural networkkrill herdLinear regression0202 electrical engineering electronic engineering information engineeringMathematics (all)Mechanics of MaterialGeneral Materials Scienceartificial krill herd algorithmCivil and Structural Engineeringregression modelArtificial neural networkMechanical EngineeringFeed forwardseismic reliability assessment of structureKrill herd algorithmRegression analysisArtificial intelligence techniqueKrill herd021001 nanoscience & nanotechnologySettore ICAR/09 - Tecnica Delle CostruzioniMechanics of Materials020201 artificial intelligence & image processingMaterials Science (all)0210 nano-technologyoptimizationRelative displacementAlgorithmartificial neural networkMechanics of Advanced Materials and Structures
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SURFACE ROUGHNESS PREDICTION OF ELECTRO-DISCHARGE MACHINED COMPONENTS USING ARTIFICIAL NEURAL NETWORKS

2016

Electro-Discharge machining (EDM) is a thermal process comprising a complex metal removal mechanism, which involves the formation of a plasma channel between the tool and the workpiece electrodes leading to the melting and evaporation of the material to be removed. EDM is considered especially suitable for machining complex contours with high accuracy, as well as for materials that are not amenable to conventional removal methods. However, several phenomena negatively affecting the surface integrity of EDMed workpieces need to be taken into account and studied in order to achieve the optimization of the process. Recently, artificial neural networks (ANN) have emerged as a novel modeling tec…

Settore ICAR/09 - Tecnica Delle CostruzioniArtificial neural networks (ANNs)electro-discharge machining (EDM)back propagation neural networks (BPNNs)Artificial neural networks (anns) back propagation neural networks (bpnns) mean surface roughness electro-discharge machining (edm)Artificial neural networks (ANNs); back propagation neural networks (BPNNs); mean surface roughness; electro-discharge machining (EDM)mean surface roughness
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