He Ni^1,*, Yongqiao Wang¹, Buyun Xu²

Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 227-236, 2020, DOI:10.31209/2019.100000068

Abstract The paper presents a probabilistic clustering approach based on self-organizing learning algorithm and recursive Bayesian estimation. The model is built upon the principle that the market data space is multimodal and can be described by a mixture of Gaussian distributions. The model parameters are approximated by a stochastic recursive Bayesian learning: searches for the maximum a posterior solution at each step, stochastically updates model parameters using a “dualneighbourhood” function with adaptive simulated annealing, and applies profile likelihood confidence interval to avoid prolonged learning. The proposed model is based on a number of pioneer works, such as Mixture Gaussian Autoregressive Model,… More >

Yonghong Zhang^1,2, Guangyi Ma^1,2,*, Wei Tian³, Jiangeng Wang⁴, Shiwei Chen^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 1149-1165, 2020, DOI:10.32604/cmes.2020.010932

Abstract Snow cover is an important parameter in the fields of computer modeling, engineering technology and energy development. With the extensive growth of novel hardware and software compositions creating smart, cyber physical systems’ (CPS) efficient end-to-end workflows. In order to provide accurate snow detection results for the CPS’s terminal, this paper proposed a snow cover detection algorithm based on the unsupervised Gaussian mixture model (GMM) for the FY-4A satellite data. At present, most snow cover detection algorithms mainly utilize the characteristics of the optical spectrum, which is based on the normalized difference snow index (NDSI) with thresholds in different wavebands. These… More >

M. Carmel Sobia¹, A. Abudhahir²

Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 869-881, 2018, DOI:10.31209/2018.100000014

Abstract In this paper, an efficient facial expression recognition system using ANFIS-MHS (Adaptive Network-based Fuzzy Inference System with Mosquito Host-Seeking) has been proposed. The features were extracted using MLDA (Modified Linear Discriminant Analysis) and then the optimized parameters are computed by using mGSO (modified Glow-worm Swarm Optimization).The proposed system recognizes the facial expressions using ANFIS-MHS. The experimental results demonstrate that the proposed technique is performed better than existing classification schemes like HAKELM (Hybridization of Adaptive Kernel based Extreme Learning Machine), Support Vector Machine (SVM) and Principal Component Analysis (PCA). The proposed approach is implemented in MATLAB. 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 initial population. On the other… More >

Ke Jin, Shunfeng Wang^*

Journal on Internet of Things, Vol.2, No.1, pp. 1-11, 2020, DOI:10.32604/jiot.2020.09071

Abstract In recent years, image restoration has become a huge subject, and finite hybrid model has been widely used in image denoising because of its easy modeling and strong explanatory results. The gaussian mixture model is the most common one. The existing image denoising methods usually assume that each component of the natural image is subject to the gaussian mixture model (GMM). However, this approach is not entirely reasonable. It is well known that most natural images are complex and their distribution is not entirely gaussian. As a result, there are still many problems that GMM cannot solve. This paper tries… More >

Fatma Mallouli

Intelligent Automation & Soft Computing, Vol.25, No.2, pp. 243-248, 2019, DOI:10.31209/2019.100000069

Abstract Density estimation via Gaussian mixture modelling has been successfully applied to image segmentation. In this paper, we have learned distributions mixture model to the pixel of an iris image as training data. We introduce the proposed algorithm by adapting the Expectation-Maximization (EM) algorithm. To further improve the accuracy for iris segmentation, we consider the EM algorithm in Markovian and non Markovian cases. Simulated data proves the accuracy of our algorithm. The proposed method is tested on a subset of the CASIA database by Chinese Academy of Sciences Institute of Automation-IrisTwins. The obtained results have shown a significant improvement of our… More >

Leilei Geng¹, Chaoran Cui¹, Qiang Guo¹, Sijie Niu², Guoqing Zhang³, Peng Fu^{4, *}

CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 913-928, 2020, DOI:10.32604/cmc.2020.09975

Abstract The multispectral remote sensing image (MS-RSI) is degraded existing multispectral camera due to various hardware limitations. In this paper, we propose a novel core tensor dictionary learning approach with the robust modified Gaussian mixture model for MS-RSI restoration. First, the multispectral patch is modeled by three-order tensor and high-order singular value decomposition is applied to the tensor. Then the task of MS-RSI restoration is formulated as a minimum sparse core tensor estimation problem. To improve the accuracy of core tensor coding, the core tensor estimation based on the robust modified Gaussian mixture model is introduced into the proposed model by… More >

Jinxing Niu^{1, *}, Yajie Jiang¹, Yayun Fu¹, Tao Zhang¹, Nicola Masini²

CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 807-816, 2020, DOI:10.32604/cmc.2020.011044

Abstract Video surveillance system is used in various fields such as transportation and social life. The bad weather can lead to the degradation of the video surveillance image quality. In rainy environment, the raindrops and the background are mixed, which lead to make the image degradation, so the removal of the raindrops has great significance for image restoration. In this article, after analyzing the inter-frame difference method in detecting and removing raindrops, a background difference method is proposed based on Gaussian model. In this method, the raindrop is regarded as a moving object relative to the background. The principle and procedure… More >

Tao Shang^{1, *}, Ran Liu¹, Jianwei Liu¹, Yafei Hou²

CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1629-1645, 2020, DOI:10.32604/cmc.2020.09820

Abstract Establishing entanglement is an essential task of quantum communication technology. Beyond entanglement, quantum discord, as a measure of quantum correlation, is a necessary prerequisite to the success of entanglement distribution. To realize efficient quantum communication based on quantum discord, in this paper, we consider the practical advantages of continuous variables and propose a feasible continuous-variable quantum network coding scheme based on quantum discord. By means of entanglement distribution by separable states, it can achieve quantum entanglement distribution from sources to targets in a butterfly network. Compared with the representative discrete-variable quantum network coding schemes, the proposed continuous-variable quantum network coding… More >

Gang Xu^{1, *}, Ran Ling¹, Lishan Deng¹, Qing Wu¹, Weiyin Ma²

CMC-Computers, Materials & Continua, Vol.62, No.1, pp. 309-319, 2020, DOI:10.32604/cmc.2020.06509

Abstract In this paper, we propose a novel image interpolation method by using Gaussian-Sinc automatic interpolators with partition of unity property. A comprehensive comparison is made with classical image interpolation methods, such as the bicubic interpolation, Lanczos interpolation, cubic Schaum interpolation, cubic B-spline interpolation and cubic Moms interpolation. The experimental results show the effectiveness of the improved image interpolation method via some image quality metrics such as PSNR and SSIM. More >