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Optimization Of Process Parameters Open Access Articles

Feed manufacturing faces enormous challenges and with the demand permanently quality feed increasing gradually, it becomes essential to enhance the processes during a feed mill. This text provides a quick overview of the various processes in feed manufacturing and identifies the critical process parameters. Five critical parameters are identified where the assembly rate is that the output parameter. Mash feed size, steam temperature; conditioning time and feed rate are the input parameters. Artificial neural network is that the methodology which is employed to optimize the method parameters. Root mean squared error and coefficient of determination and computation time are used as performance measures and it's observed that Polak–Ribiere conjugate gradient backpropagation training function with log sigmoid – pure linear transfer function combination provided good results among the various available alternatives. The method parameters are then optimized using the acceptable ideal settings of neural network parameters. This model is extremely useful for the prediction of production rate for 1 specific recipe during a feed mill. Open access (OA) may be a set of principles and a variety of practices through which research outputs are distributed online, freed from cost or other access barriers. With open access strictly defined (according to the 2001 definition), or libre open access, barriers to copying or reuse also are reduced or removed by applying an open license for copyright. The most focus of the open access movement is "peer reviewed research literature." Open access are often applied to all or any sorts of published research output, including peer-reviewed and non-peer reviewed academic journal articles, conference papers, theses, book chapters, and monographs.

 

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