Artificial Neural Network Model for Friction Factor Prediction

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Journal of Materials Science and Chemical Engineering

ISSN Print: 2327-6045
ISSN Online: 2327-6053
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"Artificial Neural Network Model for Friction Factor Prediction"
written by Uchechukwu Herbert Offor, Sunday Boladale Alabi,
published by Journal of Materials Science and Chemical Engineering, Vol.4 No.7, 2016

has been cited by the following article(s):

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[8]	Localización De Fugas Hidráulicas Enductos Aplicando Redes Neuronales Artificiales
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[9]	The Application of Artificial Neural Networks in the Assessment of Pressure Losses in Water Pipes in the Design of Water Distribution Systems
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[10]	A System for Diagnosis of Coronary Artery Disease based on Neural Networks and Machine Learning Algorithms
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[13]	DESIGN OF A NEURAL NETWORK FOR THE PREDICTION OF THE COEFFICIENT OF PRIMARY LOSSES IN UTRBULENT FLOW REGIME
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[14]	PERFORMANCE EVALUATION OF THE EXPLICIT APPROXIMATIONS OF THE IMPLICT COLEBROOK EQUATION
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[16]	A Review of Effects of Oil-Well Parameters in Estimating Annular Pressure Losses

[1]	Recent Advances in Applied Mechanics Lecture Notes in Mechanical Engineering, 2022 DOI:10.1007/978-981-16-9539-1_28

[2]	Leak diagnosis in pipelines using a combined artificial neural network approach Control Engineering Practice, 2021 DOI:10.1016/j.conengprac.2020.104677

[3]	Method of experimental investigation of the friction facility pneumatic wires Avtomatizacìâ virobničih procesìv u mašinobuduvannì ta priladobuduvannì, 2020 DOI:10.23939/istcipa2020.54.026

[4]	Diseño de una red neuronal para la predicción del coeficiente de pérdidas primarias en régimen de flujo turbulento Ingenius, 2018 DOI:10.17163/ings.n20.2018.02

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