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… More >

Rongge Xiao^a , Yue Zhu^b,*, Wenbo Jin^a , Zheng Dai^a , Shifang Li^a , Fan Zhang^c

Frontiers in Heat and Mass Transfer, Vol.12, pp. 1-6, 2019, DOI:10.5098/hmt.12.28

Abstract In order to accurately obtain the wax deposition rate model, according to the kinetic principle of wax deposition, several factors affecting the wax deposition rate were selected, and by a optimization software of First Optimization(1stOpt), The parameters of two typical wax deposition rate models are solved respectively based on optimization algorithm combined by Levenberg-Marquardt (L-M) algorithm and global optimization and the calculated data were compared. The results show that: compared with the model parameters obtained by least squares method, the model parameters obtained by this optimization algorithm can describe the variation of wax deposition rate… 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 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 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 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 More >

Mohammad Behrouzian Nejad¹, Mohammad Ebrahim Shiri Ahmadabadi^{1, 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… More >

Jialuan He^1,2, Zirui Xing², Rong Hu², Jing Qiu^3,*, Shen Su^3,*, 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 More >

Shang Zhang^{1, *}, Seyedmehdi Karimi², Shahaboddin Shamshirband^{3, 4, *}, Amir Mosavi^5,6

CMC-Computers, Materials & Continua, Vol.58, No.2, pp. 567-583, 2019, DOI:10.32604/cmc.2019.02795

Abstract In the process of eliminating variables in a symbolic polynomial system, the extraneous factors are referred to the unwanted parameters of resulting polynomial. This paper aims at reducing the number of these factors via optimizing the size of Dixon matrix. An optimal configuration of Dixon matrix would lead to the enhancement of the process of computing the resultant which uses for solving polynomial systems. To do so, an optimization algorithm along with a number of new polynomials is introduced to replace the polynomials and implement a complexity analysis. Moreover, the monomial multipliers are optimally positioned More >

Xia Li^1,2, Peifeng Niu^1,*, 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 NO_X 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. More >