Paper Info
Title
Novel applications of intelligent computing paradigms for the analysis of nonlinear reactive transport model of the fluid in soft tissues and microvessels
Abstract
This article presents a methodology to solve a one-dimensional steady-state nonlinear reactive transport model (RTM) that is meant for fluid and solute transport model of soft tissues and microvessels. The methodology integrates the artificial neural network (ANN), genetic algorithms (GAs), and pattern search (PS) aided by active-set technique (AST) and interior-point technique (IPT). The RTM is represented with nonlinear second-order system based on the boundary value problem of ordinary differential equation. The ANN modeling is used for governing expression of RTM to form a fitness function in mean square sense, and optimization solvers based on the GA, PS, GA-AST, GA-IPT, PS-AST, PS-IPT are used for viable learning of weights. Proposed techniques are applied to different nonlinear RTMs based on variation in the characteristic reaction rate and half-saturation concentration. The proposed stochastic numerical solutions are compared with state-of-the-art solvers in order to check the accuracy and convergence based on sufficient large multiple runs of the algorithms.
Year
DOI
Venue
2019
10.1007/s00521-019-04203-y
NEURAL COMPUTING & APPLICATIONS
Keywords
Field
DocType
Nonlinear reactive transport model,Artificial neural networks,Genetic algorithms,Pattern search,Interior-point technique,Active-set technique
Convergence (routing),Boundary value problem,Mathematical optimization,Nonlinear system,Ordinary differential equation,Algorithm,Fitness function,Artificial neural network,Genetic algorithm,Pattern search,Mathematics
Journal
Volume
Issue
ISSN
31.0
12
0941-0643
Citations 
PageRank 
References 
1
0.43
0
Authors
6
Name
Order
Citations
PageRank
Iftikhar Ahmad1282.99
Hira Ilyas210.43
Aysha Urooj310.43
Muhammad Saeed Aslam4618.30
Muhammad Shoaib5126388.37
Muhammad Asif Zahoor Raja655145.88