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Optimization Of Process Parameters Review 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. A research article may be a primary source...that is, it reports the methods and results of an ingenious study performed by the authors. The type of study may vary (it could are an experiment, survey, interview, etc.), but altogether cases, data are collected and analyzed by the authors, and conclusions drawn from the results of that analysis. Research articles follow a specific format. Search for a quick introduction will often include a review of the prevailing literature on the subject studied, and explain the rationale of the author's study. this is often important because it demonstrates that the authors are conscious of exisiting studies, and are getting to contribute to the present existing body of research during a meaningful way (that is, they are not just doing what others have already done).