An Artificial Neural Network as a Process Modelling
Thermomechanical process modelling of 40NICRMO8-4 alloy by artificial neural networks
... an artificial neural network every member is connected to some of the neurons of its vicinity with varying coefficients called weights (Bahrami et ...feed-forward network with back-propagation ...
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Modelling the convective drying process of pumpkin (Cucurbita moschata) using an artificial neural network
... alternative modelling method in describing the drying behaviour of ...the artificial neural networks can be successfully applied for the online monitoring and control of industrial drying processes ...
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Artificial Neural Network Modelling for Polyethylene FSSW Parameters
... (FSSW) process in 2001 to join aluminium parts together ...welding process was successfully applied to thermoplastic sheets ...FSSW process is applied to thermoplastic sheets in four stages: (1) ...
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Numerical and artificial neural network modelling of friction stir welding
... In the next chapter, the hybrid method was applied to a FSW process model developed for the Flexi-stir FSW machine. This machine has been used to analyse the complex phase changes that occur during FSW with ...
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Pavement Condition Forecasting Through Artificial Neural Network Modelling
... a process by which the connection weights of an ANN are adapted through a continuous process of stimulation by the environment in which the network is ...the artificial neural ...
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Artificial Neural Network Modelling of Vibration in the Milling of AZ91D Alloy
... assessing process stability by measuring acceleration sig- ...milling process for such elements, often made of EN AW-7075 T6, has been inves- tigated using a genetic search ...
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Rainfall-runoff modelling using artificial neural network method
... rainfall-runoff process constitutes one of the most important problems in hydrology, in order to predict or forecast streamflow for purposes such as water supply, power generation, flood control, water quality, ...
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Neural network modelling of the process of methylbutene dehydranation into isoprene
... The process of C 5 H 10 hydrocarbon dehydrogenation consists of turning isopenthane into methylbutene and its compounds, or into isoprene with an oxide ferric potassium ...an artificial neural ...
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Artificial Neural Network Methodology for Modelling and Forecasting Maize Crop Yield
... nodes/neurons). The processing ability of network is stored in the inter-unit connection strengths or weights obtained by a process of learning from a set of training patterns. A typical ANN consists of one ...
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Modelling BOD and COD using Artificial Neural Network with Factor Analysis
... Human activities give impacts on river water quality, whether by direct disposal or indirectly. The action of direct disposal polluted the river by illegal garbage dumping or chemical disposal from nearby factory. ...
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Artificial Neural Network Modelling of Traffic Noise in Agra Firozabad Highway
... of process variables which holds complex non-linear relationship, any simple feed forward network may not be sufficient to handle the prediction ...the network to compute the output value of each ...
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An artificial neural network-based rainfall runoff model for improved drainage network modelling
... In the case of option 3, the model evaluated on event 2 again showed the best results; the model identifies the shape of the main peak in the flo w data, and its prediction of the peak’s magnitude is only slightly below ...
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Neural Network Modelling and Multi-Objective Optimization of EDM Process
... on Artificial Neural Network (ANN) ANN refers to the computing systems whose fundamental concept is taken from analogy of biological neural ...The neural network of an animal is ...
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Artificial Neural Networks in Financial Modelling
... the network with the reduced database. This process tends to identify the optimal data sets depending on the analyzed problem, according to an iterative scheme that must guarantee the maximum net- work ...
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Artificial Neural Networks in Finance Modelling
... the neural network joins to the new weight. In this way the network can learn also to a high rate but it does not risk to oscillate because it recovers a high quota of the last caught up ...learning ...
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Optimization of EDM Process Parameters by Using Artificial Neural Network: A Review
... [28] Dragan Rodic, Marin Gostimirovic, Pavel Kovac, Miroslav Radovanovic, Borislav Savkovic, “ Comparison of Fuzzy logic and neural network for modelling Surface Roughness in EDM”, IJMECH, Vol.3, ...
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Prediction of forming limit diagram for AA5754 using artificial neural network modelling
... the tool is relatively cool. Temperature and strain rate are changed dynamically with both time and location in the sheet metal. In warm forming condition, it is exceptionally challenging to determine the FLD of the ...
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Prediction of forming limit diagram for AA5754 using artificial neural network modelling
... the tool is relatively cool. Temperature and strain rate are changed dynamically with both time and location in the sheet metal. In warm forming condition, it is exceptionally challenging to determine the FLD of the ...
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Artificial Neural Network Modelling for the Study of pH on the Fungal Treatment of Red mud
... the process of aluminium production the compounds in the bauxite are dissolved chemically, using caustic soda, in an alumina refinery to produce aluminium oxide 6 ...
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Modelling the Single Chamber Solid Oxide Fuel Cell by Artificial Neural Network
... As a clean and efficient energy conversion device, the fuel cell is currently considered as one of the most promising technologies for future energy demand. Solid oxide fuel cells (SOFCs) have several advantages over ...
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