Jingyi Fang¹, Xueguan Song², Nianmin Yao³, Maolin Shi^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.126, No.1, pp. 397-417, 2021, DOI:10.32604/cmes.2021.012895

Abstract Fuzzy clustering theory is widely used in data mining of full-face tunnel boring machine. However, the traditional fuzzy clustering algorithm based on objective function is difficult to effectively cluster functional data. We propose a new Fuzzy clustering algorithm, namely FCM–ANN algorithm. The algorithm replaces the clustering prototype of the FCM algorithm with the predicted value of the articial neural network. This makes the algorithm not only satisfy the clustering based on the traditional similarity criterion, but also can effectively cluster the functional data. In this paper, we rst use the t-test as an evaluation index and apply the FCM–ANN algorithm… More >

Shouzhou Gu^1,*, Jinzhong Bei¹, Chuang Shi², Yaming Dang¹, Zuoya Zheng⁴, Congcong Cui⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.119, No.2, pp. 281-293, 2019, DOI:10.32604/cmes.2019.04421

Abstract With the development of various navigation systems (such as GLONASS, Galileo, BDS), there is a sharp increase in the number of visible satellites. Accordingly, the probability of multiply gross measurements will increase. However, the conventional RAIM methods are difficult to meet the demands of the navigation system. In order to solve the problem of checking and identify multiple gross errors of receiver autonomous integrity monitoring (RAIM), this paper designed full matrix of single point positioning by QR decomposition, and proposed a new RAIM algorithm based on fuzzy clustering analysis with fuzzy c-means (FCM). And on the condition of single or… More >

Guangming Yao¹, Siraj-ul-Islam², Božidar Šarler²

CMES-Computer Modeling in Engineering & Sciences, Vol.59, No.2, pp. 127-154, 2010, DOI:10.3970/cmes.2010.059.127

Abstract This paper focuses on the comparative study of global and local meshless methods based on collocation with radial basis functions for solving two dimensional initial boundary value diffusion-reaction problem with Dirichlet and Neumann boundary conditions. A similar study was performed for the boundary value problem with Laplace equation by Lee, Liu, and Fan (2003). In both global and local methods discussed, the time discretization is performed in explicit and implicit way and the multiquadric radial basis functions (RBFs) are used to interpolate diffusion-reaction variable and its spatial derivatives. Five and nine nodded sub-domains are used in the local support of… More >

Mohammed Kaddi^1,3,*, Khelifa Benahmed², Mohammed Omari³

CMC-Computers, Materials & Continua, Vol.58, No.3, pp. 603-624, 2019, DOI:10.32604/cmc.2019.05341

Abstract Wireless Sensor Networks (WSNs) have hardware and software limitations and are deployed in hostile environments. The problem of energy consumption in WSNs has become a very important axis of research. To obtain good performance in terms of the network lifetime, several routing protocols have been proposed in the literature. Hierarchical routing is considered to be the most favorable approach in terms of energy efficiency. It is based on the concept parent-child hierarchy where the child nodes forward their messages to their parent, and then the parent node forwards them, directly or via other parent nodes, to the base station (sink).… More >

Lili He^1,2, Dantong Ouyang^1,2, Meng Wang^1,2, Hongtao Bai^1,2, Qianlong Yang^1,2, Yaqing Liu^3,4, Yu Jiang^1,2,*

CMC-Computers, Materials & Continua, Vol.57, No.3, pp. 549-570, 2018, DOI:10.32604/cmc.2018.03840

Abstract In this paper, the clustering analysis is applied to the satellite image segmentation, and a cloud-based thunderstorm cloud recognition method is proposed in combination with the strong cloud computing power. The method firstly adopts the fuzzy C-means clustering (FCM) to obtain the satellite cloud image segmentation. Secondly, in the cloud image, we dispose the ‘high-density connected’ pixels in the same cloud clusters and the ‘low-density connected’ pixels in different cloud clusters. Therefore, we apply the DBSCAN algorithm to the cloud image obtained in the first step to realize cloud cluster knowledge. Finally, using the method of spectral threshold recognition and… More >