Ashfaq Ahmad, Muhammad Sulaiman, Poom Kumam, Maharani Abu Bakar, Miftahuddin
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. © 2013 IEEE.
Department of Mathematics, Abdul Wali Khan University Mardan, Mardan, Pakistan; Department of Mathematics, KMUTT Fixed Point Research Laboratory, SCL 802 Fixed Point Laboratory, KMUTT-Fixed Point Theory and Applications Research Group, Faculty of Science, King Mongkut's University of Technology Thonburi (KMUTT), Thung Khru, Bangkok, Thailand; Center of Excellence in Theoretical and Computational Science (TaCS-CoE), King Mongkut's University of Technology Thonburi (KMUTT), Thung Khru, Bangkok, 10140, Thailand; Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, 40402, Taiwan; Faculty of Ocean Engineering Technology and Informatics, Universiti Malaysia Terengganu, Kuala Nerus, Kuala Terengganu, Malaysia; Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Syiah Kuala, Banda Aceh, Indonesia
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