Analysis of a Mathematical Model for Drilling System With Reverse Air Circulation by Using the ANN-BHCS Technique
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Publication Details
Author list: Ashfaq Ahmad, Muhammad Sulaiman, Poom Kumam, Maharani Abu Bakar, Miftahuddin
Publisher: Institute of Electrical and Electronics Engineers
Publication year: 2021
Volume number: 9
Start page: 119188
End page: 119218
Number of pages: 31
ISSN: 2169-3536
eISSN: 2169-3536
URL: https://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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