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  • Open Access

    ARTICLE

    A Novel Quantum-Behaved Particle Swarm Optimization Algorithm

    Tao Wu1, Lei Xie1, Xi Chen2, Amir Homayoon Ashrafzadeh3, Shu Zhang4, *

    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 >

  • Open Access

    ARTICLE

    A Finite Difference Method and Effective Modification of Gradient Descent Optimization Algorithm for MHD Fluid Flow Over a Linearly Stretching Surface

    Yasir Nawaz1, Muhammad Shoaib Arif 1, Mairaj Bibi2, *, 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 >

  • Open Access

    ARTICLE

    An Improved Whale Optimization Algorithm for Feature Selection

    Wenyan Guo1, *, 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 >

  • Open Access

    ARTICLE

    Feature Selection with a Local Search Strategy Based on the Forest Optimization Algorithm

    Tinghuai Ma1,*, 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 >

  • Open Access

    ARTICLE

    Analysis of OSA Syndrome from PPG Signal Using CART-PSO Classifier with Time Domain and Frequency Domain Features

    N. Kins Burk Sunil1, *, 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 >

  • Open Access

    ARTICLE

    Weight-Minimization of Sandwich Structures by a Heuristic Topology Optimization Algorithm

    C. Tapp1, W. Hansel, C. Mittelstedt, W. Becker2

    CMES-Computer Modeling in Engineering & Sciences, Vol.5, No.6, pp. 563-574, 2004, DOI:10.3970/cmes.2004.005.563

    Abstract A heuristic algorithm for the weight minimization of sandwich plates is presented. The method is based on a preexisting algorithm for the layerwise topology optimization of symmetric laminates under in-plane loads. The presented algorithm uses structural analyses based on finite elements and explicitly accounts for the special sandwich situation. During the optimization procedure the algorithm adds or subtracts material from the layers of the face sheets and the core of the sandwich plate in regions of high or low stresses respectively. The orientation angles of the layers of the sandwich facings are not varied inorder to alloweasy manufacturing. Several variantsofthe… More >

  • Open Access

    ARTICLE

    An Ant Colony Optimization Algorithm for Stacking Sequence Design of Composite Laminates

    F. Aymerich1, M. Serra2

    CMES-Computer Modeling in Engineering & Sciences, Vol.13, No.1, pp. 49-66, 2006, DOI:10.3970/cmes.2006.013.049

    Abstract The study reported in this paper explores the potential of Ant Colony Optimization (ACO) metaheuristic for stacking sequence optimization of composite laminates. ACO is a recently proposed population-based search approach able to deal with a wide range of optimization problems, especially of a combinatorial nature, and inspired by the natural foraging behavior of ant colonies. ACO search processes, in which the activities of real ants are simulated by means of artificial agents that communicate and cooperate through the modification of the local environment, were implemented in a specifically developed numerical algorithm aimed at the lay-up optimization (based on a strain… More >

  • Open Access

    ARTICLE

    Improved Teaching-Learning-Based Optimization Algorithm for Modeling NOX Emissions of a Boiler

    Xia Li1,2, Peifeng Niu1,*, Jianping Liu2, Qing Liu2

    CMES-Computer Modeling in Engineering & Sciences, Vol.117, No.1, pp. 29-57, 2018, DOI:10.31614/cmes.2018.04020

    Abstract An improved teaching-learning-based optimization (I-TLBO) algorithm is proposed to adjust the parameters of extreme learning machine with parallel layer perception (PELM), and a well-generalized I-TLBO-PELM model is obtained to build the model of NOX emissions of a boiler. In the I-TLBO algorithm, there are four major highlights. Firstly, a quantum initialized population by using the qubits on Bloch sphere replaces a randomly initialized population. Secondly, two kinds of angles in Bloch sphere are generated by using cube chaos mapping. Thirdly, an adaptive control parameter is added into the teacher phase to speed up the convergent speed. And then, according to… More >

  • Open Access

    ARTICLE

    A Novel Image Categorization Strategy Based on Salp Swarm Algorithm to Enhance Efficiency of MRI Images

    Mohammad Behrouzian Nejad1, Mohammad Ebrahim Shiri Ahmadabadi1, 2, *

    CMES-Computer Modeling in Engineering & Sciences, Vol.119, No.1, pp. 185-205, 2019, DOI:10.32604/cmes.2019.01838

    Abstract The main target of this paper is presentation of an efficient method for MRI images classification so that it can be used to diagnose patients and non-patients. Image classification is one of the prominent subset topics of machine learning and data mining that the most important image technique is the auto-categorization of images. MRI images with high resolution and appropriate accuracy allow physicians to decide on the diagnosis of various diseases and treat them. The auto categorization of MRI images toward diagnosing brain diseases has been being used to accurately diagnose hospitals, clinics, physicians and medical research centers. In this… More >

  • Open Access

    ARTICLE

    Directional Antenna Intelligent Coverage Method Based on Traversal Optimization Algorithm

    Jialuan He1,2, Zirui Xing2, Rong Hu2, Jing Qiu3,*, Shen Su3,*, Yuhan Chai3, Yue Wu4

    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 527-544, 2019, DOI:10.32604/cmc.2019.05586

    Abstract Wireless broadband communication is widely used in maneuver command communications systems in many fields, such as military operations, counter-terrorism and disaster relief. How to reasonably formulate the directional antenna coverage strategy according to the mobile terminal dynamic distribution and guide the directional antenna dynamic coverage becomes a practical research topic. In many applications, a temporary wireless boardband base station is required to support wireless signal communications between many terminals from nearby vehicles and staffs. It is therefore important to efficiently set directional antenna while ensuring large enough coverage over dynamically distributed terminals. The wireless broadband base station mostly uses two… More >

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