On the Efficacy of Ensemble of Constraint Handling Techniques in Self-Adaptive Differential Evolution

Javed, Hassan; Jan, Muhammad Asif; Tairan, Nasser; Khan, Wali Ullah; Khanum, Rashida Adeeb; Sulaiman, Muhammad; Khan, Hidayat Ullah; Shah, Habib

doi:10.3390/math7070635

Cited by 12 publications

(11 citation statements)

References 31 publications

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“…As revealed in the literature, a key aspect of using evolutionary algorithms for optimizing AI models is to study the relationship between population size and problem dimensionality [117][118][119][120]. In many other evolutionary algorithms such as differential evolution, the number in the population is recommended to be 7-10 times the number of inputs [121,122].…”

Section: Optimization Of Weight Parameters Of Fnn Using the Iwo Technmentioning

confidence: 99%

Optimization of Artificial Intelligence System by Evolutionary Algorithm for Prediction of Axial Capacity of Rectangular Concrete Filled Steel Tubes under Compression

Nguyen

Tran

et al. 2020

Materials

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Concrete filled steel tubes (CFSTs) show advantageous applications in the field of construction, especially for a high axial load capacity. The challenge in using such structure lies in the selection of many parameters constituting CFST, which necessitates defining complex relationships between the components and the corresponding properties. The axial capacity (P u ) of CFST is among the most important mechanical properties. In this study, the possibility of using a feedforward neural network (FNN) to predict P u was investigated. Furthermore, an evolutionary optimization algorithm, namely invasive weed optimization (IWO), was used for tuning and optimizing the FNN weights and biases to construct a hybrid FNN-IWO model and improve its prediction performance. The results showed that the FNN-IWO algorithm is an excellent predictor of P u , with a value of R 2 of up to 0.979. The advantage of FNN-IWO was also pointed out with the gains in accuracy of 47.9%, 49.2%, and 6.5% for root mean square error (RMSE), mean absolute error (MAE), and R 2 , respectively, compared with simulation using the single FNN. Finally, the performance in predicting the P u in the function of structural parameters such as depth/width ratio, thickness of steel tube, yield stress of steel, concrete compressive strength, and slenderness ratio was investigated and discussed.Materials 2020, 13, 1205 2 of 25 larger energy absorption capacity [7], convenient construction [11], economy of materials [12][13][14], and excellent seismic and refractory performance [15]. In particular, this type of structure can reduce the environmental burden by removing formwork [16], reusing steel pipes, and using high quality concrete with recycled aggregate [17]. The characteristics of CFST are that the steel material is located far from the central axis so the rigidity of the column is very large, and thus it also contributes to increasing the moment of inertia of the structure [5,18]. The ideal form of concrete core works against the compressive load and hinders the local buckling state of the steel pipe. Therefore, the CFST structures are often used in locations subject to large compressive loads [9,15,19]. The CFST columns are mainly divided into square columns, round columns, and rectangular columns, based on different cross-sectional forms [15]. In particular, the square and rectangular CFST columns have the advantage of easy connection and reliable work with other structural members such as beams, walls, and panels [20]. Compared with square CFST columns, rectangular columns have irregular bending stiffness along different axes, so this type of column is suitable for the mechanical behavior of members including arch ribs, pillars, abutments, and piers, and other structural members under load actions vary greatly from vertical to horizontal [6]. Because the scope of application of rectangular CFST columns is quite wide and this column is mainly subjected to compression, the main purpose of the paper is to analyze and evaluate the ultimate bearing capacity of...

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Section: Optimization Of Weight Parameters Of Fnn Using the Iwo Technmentioning

confidence: 99%

Optimization of Artificial Intelligence System by Evolutionary Algorithm for Prediction of Axial Capacity of Rectangular Concrete Filled Steel Tubes under Compression

Nguyen

Tran

et al. 2020

Materials

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“…where 0 ≤ X ≤ 1 ,ζ n , ψ n and θ n are unknown parameters and λ = −0.9. Since Eq (29) and Eq (36) are twice differentiable. Therefore, first derivative y (η) and second derivative y (η) of Eq (44) are represented by the following equations,…”

Section: Approximate Solutions and Weighted Legendre Polynomialsmentioning

confidence: 99%

“…plugging Eq (44)(45)(46) in governing ordinary differential equations. Eq (29) and Eq (36) will be converted into an equivalent algebraic system of equations that can be solved for unknown parameters ζ n , ψ n and θ n using LeNN-WOA-NM algorithm. Parameter setting for LeNN algorithm are given in TABLE 2.…”

Section: Approximate Solutions and Weighted Legendre Polynomialsmentioning

confidence: 99%

“…It is a summation of mean squared errors at each t ∈ [0 1]. LeNN-WOA-NM algorithm is applied to minimize the fitness function for Eq (29), representing counter-current imbibition phenomenon through…”

Section: Fitness Function Formulationmentioning

confidence: 99%

“…In electrical engineering, several metaheuristics are used to solve complex optimization problems [31]- [34]. Unconstrained single-objective optimization problems are solved by using a hybrid of global and local search procedures [29], [35]. The optimal design of heat fins is proposed in [36].…”

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

et al. 2020

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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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Differential evolution improvement by adaptive ranking-based constraint handling technique

Zhao

Luo

2023

Soft Comput

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On the Efficacy of Ensemble of Constraint Handling Techniques in Self-Adaptive Differential Evolution

Cited by 12 publications

References 31 publications

Optimization of Artificial Intelligence System by Evolutionary Algorithm for Prediction of Axial Capacity of Rectangular Concrete Filled Steel Tubes under Compression

Optimization of Artificial Intelligence System by Evolutionary Algorithm for Prediction of Axial Capacity of Rectangular Concrete Filled Steel Tubes under Compression

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

Differential evolution improvement by adaptive ranking-based constraint handling technique

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