Haitao Yue¹, Chenguang Guo^1,*, Qiang Li¹, Lijuan Zhao¹, Guangbo Hao²

CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 937-952, 2020, DOI:10.32604/cmes.2020.010565

Abstract To improve the milling surface quality of the Al-Li alloy thin-wall workpieces and reduce the cutting energy consumption. Experimental research on the milling processing of AA2195 Al-Li alloy thin-wall workpieces based on Response Surface Methodology was carried out. The single factor and interaction of milling parameters on surface roughness and specific cutting energy were analyzed, and the multi-objective optimization model was constructed. The Multiobjective Particle Swarm Optimization algorithm introducing the Chaos Local Search algorithm and the adaptive inertial weight was applied to determine the optimal combination of milling parameters. It was observed that surface roughness was mainly influenced by feed… More >

Julius Beneoluchi Odili^1,*, A. Noraziah², Mohd Helmy Abd Wahab³

Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 41-51, 2020, DOI:10.31209/2018.100000059

Abstract This paper presents the African Buffalo Optimization algorithm for collision avoidance among electric fishes. Collision-avoidance in electric fish finds correlation with the Travelling Salesman avoiding the cities he has earlier visited. Collision avoidance in electric is akin to collision-avoidance in modern day driverless cars being promoted by Google Incorporation and other similar companies. The concept of collision-avoidance is also very useful to persons with visual impairment as it will help them avoid collision with objects, vehicles, persons, especially other visually-impaired. After a number of experimental procedures using the concept of the travelling salesman’s problem to simulate collision-avoidance in electric fish,… More >

Jilin Zhang^1,4,5, Xuechao Liu^1,5, Jian Wan^2,1,5, Yongjian Ren^1,5, Binglin Xu^1,5, Jianfan He^1,5, Yuchen Fan^1,5, Li Zhou^1,5, Zhenguo Wei⁶, Juncong Zhang⁶, Jue Wang³

Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 527-546, 2019, DOI:10.31209/2019.100000109

Abstract A numerical optimization algorithm for unsteady flows of rotor based on web service is proposed. Space discretization uses the finite volume method, time discretization uses the implicit dual-time steps method, and turbulence model uses the Spalart–Allmaras (S–A) model. In order to efficiently use the computing resources of the cluster, a service-oriented service computing architecture is used in a parallel computing service program. In order to realize the load balance of hybrid grid partition, the grid is partitioned by Metis Library. Meanwhile, data communication based on Message Passing Interface (MPI) technology guarantees the consistency of convergence between parallel algorithm and serial… More >

Peizhong Liu¹, Xiaofang Liu¹, Yanming Luo², Yongzhao Du¹, Yulin Fan¹, Hsuan‐Ming Feng³

Intelligent Automation & Soft Computing, Vol.25, No.2, pp. 385-394, 2019, DOI:10.31209/2019.100000100

Abstract Aiming at the drawback of artificial bee colony algorithm (ABC) with slow convergence speed and weak exploitation capacity, an enhanced exploitation artificial bee colony algorithm is proposed, EeABC for short. Firstly, a generalized opposition-based learning strategy (GOBL) is employed when initial population is produced for obtaining an evenly distributed population. Subsequently, inspired by the differential evolution (DE), two new search equations are proposed, where the one is guided by the best individuals in the next generation to strengthen exploitation and the other is to avoid premature convergence. Meanwhile, the distinction between the employed bee and the onlooker bee is not… More >

Yue Ruan^{1, *}, Samuel Marsh², Xilin Xue¹, Zhihao Liu³, Jingbo Wang^{2, *}

CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1237-1247, 2020, DOI:10.32604/cmc.2020.010001

Abstract The Quantum Approximate Optimization Algorithm (QAOA) is an algorithmic framework for finding approximate solutions to combinatorial optimization problems. It consists of interleaved unitary transformations induced by two operators labelled the mixing and problem Hamiltonians. To fit this framework, one needs to transform the original problem into a suitable form and embed it into these two Hamiltonians. In this paper, for the well-known NP-hard Traveling Salesman Problem (TSP), we encode its constraints into the mixing Hamiltonian rather than the conventional approach of adding penalty terms to the problem Hamiltonian. Moreover, we map edges (routes) connecting each pair of cities to qubits,… More >

Tao Wu¹, Lei Xie¹, Xi Chen², Amir Homayoon Ashrafzadeh³, Shu Zhang^{4, *}

CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 873-890, 2020, DOI:10.32604/cmc.2020.07478

Abstract The efficient management of ambulance routing for emergency requests is vital to save lives when a disaster occurs. Quantum-behaved Particle Swarm Optimization (QPSO) algorithm is a kind of metaheuristic algorithms applied to deal with the problem of scheduling. This paper analyzed the motion pattern of particles in a square potential well, given the position equation of the particles by solving the Schrödinger equation and proposed the Binary Correlation QPSO Algorithm Based on Square Potential Well (BCQSPSO). In this novel algorithm, the intrinsic cognitive link between particles’ experience information and group sharing information was created by using normal Copula function. After… More >

Yasir Nawaz¹, Muhammad Shoaib Arif ¹, Mairaj Bibi^{2, *}, Javeria Nawaz Abbasi², Umer Javed³, Amna Nazeer²

CMC-Computers, Materials & Continua, Vol.62, No.2, pp. 657-677, 2020, DOI:10.32604/cmc.2020.08584

Abstract Present contribution is concerned with the construction and application of a numerical method for the fluid flow problem over a linearly stretching surface with the modification of standard Gradient descent Algorithm to solve the resulted difference equation. The flow problem is constructed using continuity, and Navier Stoke equations and these PDEs are further converted into boundary value problem by applying suitable similarity transformations. A central finite difference method is proposed that gives third-order accuracy using three grid points. The stability conditions of the present proposed method using a Gauss-Seidel iterative procedure is found using VonNeumann stability criteria and order of… More >

Wenyan Guo^{1, *}, Ting Liu¹, Fang Dai¹, Peng Xu¹

CMC-Computers, Materials & Continua, Vol.62, No.1, pp. 337-354, 2020, DOI:10.32604/cmc.2020.06411

Abstract Whale optimization algorithm (WOA) is a new population-based metaheuristic algorithm. WOA uses shrinking encircling mechanism, spiral rise, and random learning strategies to update whale’s positions. WOA has merit in terms of simple calculation and high computational accuracy, but its convergence speed is slow and it is easy to fall into the local optimal solution. In order to overcome the shortcomings, this paper integrates adaptive neighborhood and hybrid mutation strategies into whale optimization algorithms, designs the average distance from itself to other whales as an adaptive neighborhood radius, and chooses to learn from the optimal solution in the neighborhood instead of… More >

Tinghuai Ma^1,*, Honghao Zhou¹, Dongdong Jia¹, Abdullah Al-Dhelaan², Mohammed Al-Dhelaan², Yuan Tian³

CMES-Computer Modeling in Engineering & Sciences, Vol.121, No.2, pp. 569-592, 2019, DOI:10.32604/cmes.2019.07758

Abstract Feature selection has been widely used in data mining and machine learning. Its objective is to select a minimal subset of features according to some reasonable criteria so as to solve the original task more quickly. In this article, a feature selection algorithm with local search strategy based on the forest optimization algorithm, namely FSLSFOA, is proposed. The novel local search strategy in local seeding process guarantees the quality of the feature subset in the forest. Next, the fitness function is improved, which not only considers the classification accuracy, but also considers the size of the feature subset. To avoid… More >

N. Kins Burk Sunil^{1, *}, R. Ganesan², B. Sankaragomathi³

CMES-Computer Modeling in Engineering & Sciences, Vol.118, No.2, pp. 351-375, 2019, DOI:10.31614/cmes.2018.04484

Abstract Obstructive Sleep Apnea (OSA) is a respiratory syndrome that occurs due to insufficient airflow through the respiratory or respiratory arrest while sleeping and sometimes due to the reduced oxygen saturation. The aim of this paper is to analyze the respiratory signal of a person to detect the Normal Breathing Activity and the Sleep Apnea (SA) activity. In the proposed method, the time domain and frequency domain features of respiration signal obtained from the PPG device are extracted. These features are applied to the Classification and Regression Tree (CART)-Particle Swarm Optimization (PSO) classifier which classifies the signal into normal breathing signal… More >