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Optimization Of Process Parameters High Impact Factor Journals

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. Impact Factors are wont to measure the importance of a journal by calculating the amount of times selected articles are cited within the previous couple of years. the upper the impact factor, the more highly ranked the journal. it's one tool you'll use to match journals during a subject category.

 

High Impact List of Articles

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