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ARTIFICIAL NEURAL NETWORK AND ITS APPLICATION IN SLURRY FLOW MODELLING

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Pipeline transport has been a progressive technology for conveying a large quantity of bulk materials. The modern way of pipelining prefers the concentrated slurries since hydraulic transport of dense hydro-mixtures can bring several advantages.
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  ARTIFICIAL NEURAL NETWORK AND ITS APPLICATION IN CHEMICAL ENGINEERING PRESENTED BY : ATANU KUMAR PAUL 11/CHE/411 GUIDED BY : PROFESSOR K. C. GHANTA  [1] Tambe, S. S., B. D. Kulkarni, P. B. Deshpande, Elements of Artificial Neural  Networks with Selected Applications in Chemical Engineering, and Chemical And Biological Sciences, Simulation & Advanced Controls, Inc., USA, (1996) What is ANN ?  An artificial neural network (ANN), usually called neural network (NN).    It is a mathematical model or computational model that is inspired by the structure and functional aspects of biological neural networks. [1]    A neural network consists of an interconnected group of artificial neurons, and it processes information using a connectionist approach to computation.      2    In most cases an ANN is an adaptive system that changes its structure based on external or internal information that flows through the network during the learning phase.  Modern neural networks are non-linear statistical data modeling tools. They are usually used to model complex relationships between inputs and outputs or to find patterns in data. CONTD    3    The srcinal inspiration for the term Artificial Neural Network came from examination of central nervous systems and their neurons, axons, dendrites, and synapses, which constitute the processing elements of biological neural networks investigated by neuroscience.  In an artificial neural network, simple artificial nodes, variously called neurons , neurodes , processing elements (PEs) or units , are connected together to form a network of nodes similar to the biological neural networks  —   hence the term artificial neural network . Background of ANN    4 
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