A Soft Computing Approach Based on Fractional Order DPSO Algorithm Designed to Solve the Corneal Model for Eye Surgery

Waseem, W.; Sulaiman, Muhammad; Alhindi, Ahmad; Alhakami, Hosam

doi:10.1109/access.2020.2983823

Cited by 32 publications

(23 citation statements)

References 44 publications

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“…Results obtained by our technique are presented for homogeneous and heterogeneous porous media. The mathematical model for heterogeneous porous media is presented in Eq (29)(30)(31), and for homogeneous porous media, the ordinary differential equation together with its conditions is given in Eq (40)(41)(42). It is obvious from both models (for homogeneous and heterogenous media) that saturation depends on time T and distance X.…”

Section: Numerical Resultsmentioning

confidence: 99%

“…h and h is a step size. Similarly, fitness function for the ODE in Eq (40) and boundary conditions in Eqs (41)(42) representing the secondary oil recovery process through homogenous porous media, is given as,…”

Section: Fitness Function Formulationmentioning

confidence: 99%

“…The approximate solution of ordinary differential equation (40) describes the saturation of injected fluid through homogenous media, when water is injected in water flooding or secondary oil recovery process during counter-current imbibition phenomenon. Since, the saturation depends on time T and distance X.…”

Section: B Homogenous Porous Mediummentioning

confidence: 99%

“…An interesting study of financial market forecasting is accomplished by the ARFIMA-LSTM technique [39]. Fractional order DPSO algorithm is used to solve the corneal model for eye surgery [40]. A novel initialization strategy is introduced in a multi-verse optimization technique, and different design engineering problems are solved in [41].…”

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Analysis of Multi-Phase Flow Through Porous Media for Imbibition Phenomena by Using the LeNN-WOA-NM Algorithm

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The flow of fluids in multi-phase porous media results due to many interesting natural phenomena. The counter-current water imbibition phenomena, that occur during oil extraction through a cylindrical well is an interesting problem in petroleum engineering. During the secondary oil recovery process, water is injected into a porous media having heterogenous and homogenous characteristics. Due to the difference in viscosities of fluids in oil wells, the counter-current imbibition phenomenon occurs. At that moment, the imbibition equation V i = −V n is satisfied by the viscosities of oil and water. In this paper, we have analyzed the governing mathematical model of the imbibition phenomenon occurring during the secondary oil recovery process. A new soft computing algorithm is designed and adapted to analyze the mathematical model of dual-phase flow in detail. Weighted Legendre polynomials based artificial neural networks are hybridized with an efficient global optimizer the Whale Optimization Algorithm (WOA) and a local optimizer the Nelder-Mead algorithm. It is established, that our algorithm LeNN-WOA-NM is efficient and reliable in calculating high-quality solutions in less time. We have compared our experimental outcome with state-of-the-art results. The quality of our solutions is judged based on values of absolute errors, MAD, TIC, and ENSE. It is obvious that LeNN-WOA-NM algorithm can solve real application problems efficiently and accurately. INDEX TERMS Counter-current imbibition phenomena, homogeneous porous media, heterogeneous porous media, capillary pressure, soft computing algorithm, weighted Legendre neural networks, Nelder-Mead algorithm, whale optimization algorithm. I. INTRODUCTION T HIS paper models the phenomena of counter-current imbibition in the multi-phase flow of two immiscible fluids through heterogeneous and homogenous porous mediums that occurs during the secondary oil recovery process or water flooding [1]. In applied sciences, various changes occur in porous mediums having multi-phase flows of different fluids. In the past few decades, researchers are focused on studying the flows in underground petroleum reservoirs [2]. The primary recovery process includes the production of oil by simple natural decompression with no effect of external forces at wells [3]. In secondary oil recovery or water flooding process, fluids like water, polymer, steam are injected into a reservoir through injection wells located in rocks that have fluid communication with production wells. This process is called the immiscible displacement process [3].

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Section: Numerical Resultsmentioning

confidence: 99%

Section: Fitness Function Formulationmentioning

confidence: 99%

Section: B Homogenous Porous Mediummentioning

confidence: 99%

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Analysis of Multi-Phase Flow Through Porous Media for Imbibition Phenomena by Using the LeNN-WOA-NM Algorithm

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“…A theoretical analysis of PPA is discussed with details in [37]. A hybrid soft computing technique combining the artificial neural networks and fractional-order DPSO algorithm is applied to analyze the corneal shape model of eye surgery [28]. A neuroevolutionary approach is used to analyze the oscillatory behavior of heart [27].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Temperature Profiles in Longitudinal Fin Designs by a Novel Neuroevolutionary Approach

et al. 2020

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Real application problems in physics, engineering, economics, and other disciplines are often modeled as differential equations. Classical numerical techniques are computationally expensive when we require solutions to our mathematical problems with no prior information. Hence, researchers are more interested in developing numerical methods that can obtain better solutions with fewer efforts and computational time. Heuristic algorithms are considered suitable candidates for such type of problems. In this research, we have developed a new neuroevolutionary algorithm that combines the power of feed-forward artificial neural networks (ANNs) and a modern metaheuristic, the Symbiotic Organism Search (SOS) algorithm. With our new approach, we have analyzed the simultaneous surface convection and radiation during heat transfer in different models of fins/ heat exchangers. Longitudinal fins are considered with concave parabolic, rectangular and trapezoidal shapes. We have analyzed our problem in two scenarios and six sub-cases. Our solutions are of high quality, with minimum residual errors in all cases. We have established the quality of our results by calculating values of different performance indicators like Root-mean-square error (RMSE), Absolute error (AE), Generational distance (GD), Mean absolute deviation (MAD), Nash-Sutcliffe efficiency (NSE), Error in Nash-Sutcliffe efficiency (ENSE). Statistical and graphical analysis of our results suggests that our approach is suitable for handling real application problems. We have compared our results with state-of-the-art results, and the outcome of our analysis points to the superiority of our approach. INDEX TERMS Approximate solutions, Artificial neural networks, Heat transfer analyses, Longitudinal fins, Metaheuristics, Symbiotic organism search optimizer.

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Heat transfer analysis of an inclined longitudinal porous fin of trapezoidal, rectangular and dovetail profiles using cascade neural networks

Khan

Sulaiman

Alshammari

2022

Struct Multidisc Optim

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A Soft Computing Approach Based on Fractional Order DPSO Algorithm Designed to Solve the Corneal Model for Eye Surgery

Cited by 32 publications

References 44 publications

Analysis of Multi-Phase Flow Through Porous Media for Imbibition Phenomena by Using the LeNN-WOA-NM Algorithm

Analysis of Multi-Phase Flow Through Porous Media for Imbibition Phenomena by Using the LeNN-WOA-NM Algorithm

Analysis of Temperature Profiles in Longitudinal Fin Designs by a Novel Neuroevolutionary Approach

Heat transfer analysis of an inclined longitudinal porous fin of trapezoidal, rectangular and dovetail profiles using cascade neural networks

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