Chung Wen Hung, Wei Lung Mao, Han Yi Huang

Intelligent Automation & Soft Computing, Vol.25, No.2, pp. 329-341, 2019, DOI:10.31209/2019.100000093

Abstract Nonlinear system modeling and identification is the one of the most important areas in engineering problem. The paper presents the recurrent fuzzy neural network (RFNN) trained by modified particle swarm optimization (MPSO) methods for identifying the dynamic systems and chaotic observation prediction. The proposed MPSO algorithms mainly modify the calculation formulas of inertia weights. Two MPSOs, namely linear decreasing particle swarm optimization (LDPSO) and adaptive particle swarm optimization (APSO) are developed to enhance the convergence behavior in learning process. The RFNN uses MPSO based method to tune the parameters of the membership functions, and it More >

Qi Wang^1,*, Wei Liu¹, Hualong Yu¹, Shang Zheng¹, Shang Gao¹, Fabrizio Granelli²

CMES-Computer Modeling in Engineering & Sciences, Vol.121, No.1, pp. 83-103, 2019, DOI:10.32604/cmes.2019.06897

Abstract The wireless sensor network (WSN) is widely employed in the application scenarios of the Internet of Things (IoT) in recent years. Extending the lifetime of the entire system had become a significant challenge due to the energy-constrained fundamental limits of sensor nodes on the perceptual layer of IoT. The clustering routing structures are currently the most popular solution, which can effectively reduce the energy consumption of the entire network and improve its reliability. This paper introduces an enhanced hybrid intelligential algorithm based on particle swarm optimization (PSO) and ant colony optimization (ACO) method. The enhanced 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 >

Gongyu Hou¹, Zhedong Xu^1,*, Xin Liu¹, Cong Jin¹

CMES-Computer Modeling in Engineering & Sciences, Vol.118, No.2, pp. 317-337, 2019, DOI:10.31614/cmes.2019.04693

Abstract This article proposes an exponential adjustment inertia weight immune particle swarm optimization (EAIW-IPSO) to enhance the accuracy and reliability regarding the selection of shield tunneling parameter values. According to the iteration changes and the range of inertia weight in particle swarm optimization algorithm (PSO), the inertia weight is adjusted by the form of exponential function. Meanwhile, the self-regulation mechanism of the immune system is combined with the PSO. 12 benchmark functions and the realistic cases of shield tunneling parameter value selection are utilized to demonstrate the feasibility and accuracy of the proposed EAIW-IPSO algorithm. Comparison More >

Zhe Liu^1,2,*, Bao Xiang^1,3, Yuqing Song¹, Hu Lu¹, Qingfeng Liu¹

CMC-Computers, Materials & Continua, Vol.58, No.2, pp. 451-461, 2019, DOI:10.32604/cmc.2019.04069

Abstract Most image segmentation methods based on clustering algorithms use single-objective function to implement image segmentation. To avoid the defect, this paper proposes a new image segmentation method based on a multi-objective particle swarm optimization (PSO) clustering algorithm. This unsupervised algorithm not only offers a new similarity computing approach based on electromagnetic forces, but also obtains the proper number of clusters which is determined by scale-space theory. It is experimentally demonstrated that the applicability and effectiveness of the proposed multi-objective PSO clustering algorithm. More >

Carlos Lopez-Franco¹, Javier Gomez-Avila², Nancy Arana-Daniel³, Alma Y. Alanis

Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 431-442, 2018, DOI:10.31209/2018.100000000

Abstract This paper presents a method for 3D pose estimation using visual information and a soft-computing algorithm. The algorithm uses quaternions to represent rotations, and Particle Swarm Optimization to estimate such quaternion. The rotation estimation problem is cast as a minimization problem, which finds the best quaternion for the given data using the PSO algorithm. With this technique, the algorithm always returns a valid quaternion, and therefore a valid rotation. During the estimation process, the algorithm is able to detect and reject outliers. The simulations and experimental results show the robustness of algorithm against noise and More >

Dongping Tian^a,b

Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 331-342, 2018, DOI:10.1080/10798587.2017.1293881

Abstract Particle swarm optimization (PSO) is a population based swarm intelligence algorithm that has been deeply studied and widely applied to a variety of problems. However, it is easily trapped into the local optima and premature convergence appears when solving complex multimodal problems. To address these issues, we present a new particle swarm optimization by introducing chaotic maps (Tent and Logistic) and Gaussian mutation mechanism as well as a local re-initialization strategy into the standard PSO algorithm. On one hand, the chaotic map is utilized to generate uniformly distributed particles to improve the quality of the… More >

Jin Wang^1,2, Chunwei Ju², Yu Gao², Arun Kumar Sangaiah³, Gwang-jun Kim^4,*

CMC-Computers, Materials & Continua, Vol.56, No.3, pp. 433-446, 2018, DOI:10.3970/cmc.2018.04132

Abstract Wireless Sensor Networks (WSNs) are large-scale and high-density networks that typically have coverage area overlap. In addition, a random deployment of sensor nodes cannot fully guarantee coverage of the sensing area, which leads to coverage holes in WSNs. Thus, coverage control plays an important role in WSNs. To alleviate unnecessary energy wastage and improve network performance, we consider both energy efficiency and coverage rate for WSNs. In this paper, we present a novel coverage control algorithm based on Particle Swarm Optimization (PSO). Firstly, the sensor nodes are randomly deployed in a target area and remain More >

Zichun Yang^1,2,3, Wencai Sun²

CMES-Computer Modeling in Engineering & Sciences, Vol.92, No.2, pp. 193-212, 2013, DOI:10.3970/cmes.2013.092.193

Abstract The set-based structural eigenvalue problem is defined, by expressing the uncertainties of the structural parameters in terms of various convex sets. A new method based on Kriging model and Particle Swarm Optimization (PSO) is proposed for solving this problem. The introduction of the Kriging model into this approach can effectively reduce the computational burden especially for largescale structures. The solutions of the non-linear and non-monotonic problems are more accurate than those obtained by other methods in the literature with the PSO algorithm. The experimental points for Kriging model are sampled according to Latin hypercube sampling More >

Jiawei Xiang¹, Toshiro Matsumoto², Yanxue Wang³, Zhansi Jiang⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.81, No.3&4, pp. 269-294, 2011, DOI:10.3970/cmes.2011.081.269

Abstract Damages occurred in a structure will lead to changes in modal parameters (natural frequencies and modal shapes). The relationship between modal parameters and damage parameters (locations and depths) is very complicated. Single detection method using natural frequencies or modal shapes can not obtain robust damage detection results from the inevitably noise-contaminated modal parameters. To eliminate the complexity, a hybrid approach using both of wavelets on the interval (interval wavelets) method and wavelet finite element model-based method is proposed to detect damage locations and depths. To avoid the boundary distortion phenomenon, Interval wavelets are employed to… More >