Analysis of a Mathematical Model for Drilling System With Reverse Air Circulation by Using the ANN-BHCS Technique

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Author listAshfaq Ahmad, Muhammad Sulaiman, Poom Kumam, Maharani Abu Bakar, Miftahuddin

PublisherInstitute of Electrical and Electronics Engineers

Publication year2021

Volume number9

Start page119188

End page119218

Number of pages31

ISSN2169-3536

eISSN2169-3536

URLhttps://ieeexplore.ieee.org/document/9521498


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Abstract

In the present article, mathematical analysis of drilling system with reverse air circulation is presented by a novel hybrid technique of feedforward artificial neural network (ANN) and biogeography based cuckoo search (BHCS) algorithm. A series solution is constructed with unknown weights for the differential equations representing the drilling problem. Five numerical cases are analysed to show the effectiveness of our method for the solution of differential equations. From the experimental outcomes, it is investigated that our soft computing procedure has a better rate of convergence to the best solution as compared to state-of-the-art techniques. From solution graphs, it is established that our results are in agreement with the reference solutions. It is noted that our technique is easy to implement and can be used for any mathematical model containing nonlinear differential equations. The graphical abstract of this article is given in Figure (1) . FIGURE 1.

Graphical illustration of the soft computing procedure followed in this paper.


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Last updated on 2023-03-10 at 07:36