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  • Open Access


    Wiener Model Identification Using a Modified Brain Storm Optimization Algorithm

    Tianhong Pan1,*, Ying Song2, Shan Chen2

    Intelligent Automation & Soft Computing, Vol.26, No.5, pp. 934-946, 2020, DOI:10.32604/iasc.2020.010125

    Abstract The Wiener model is widely used in industrial processes. It is composed of a linear dynamic block and a nonlinear static block. Estimating the Wiener model is challenging because of the diversity of static nonlinear functions and the immeasurableness of intermediate signals owing to the series structure of the Wiener model. Existing optimization algorithms cannot satisfy the requirements of accuracy and efficiency of identification and often lose into a local optimum. Herein, a modified Brain Storm Optimization (mBSO) is proposed to estimate the parameters of the Wiener model. Many different combinations of individuals from intra or extra-groups ensure the diversity… More >

  • Open Access


    SEIHCRD Model for COVID-19 Spread Scenarios, Disease Predictions and Estimates the Basic Reproduction Number, Case Fatality Rate, Hospital, and ICU Beds Requirement

    Avaneesh Singh*, Manish Kumar Bajpai

    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.3, pp. 991-1031, 2020, DOI:10.32604/cmes.2020.012503

    Abstract We have proposed a new mathematical method, the SEIHCRD model, which has an excellent potential to predict the incidence of COVID-19 diseases. Our proposed SEIHCRD model is an extension of the SEIR model. Three-compartments have added death, hospitalized, and critical, which improves the basic understanding of disease spread and results. We have studied COVID-19 cases of six countries, where the impact of this disease in the highest are Brazil, India, Italy, Spain, the United Kingdom, and the United States. After estimating model parameters based on available clinical data, the model will propagate and forecast dynamic evolution. The model calculates the… More >

  • Open Access


    Resampling Factor Estimation via Dual-Stream Convolutional Neural Network

    Shangjun Luo1, Junwei Luo1, Wei Lu1,*, Yanmei Fang1, Jinhua Zeng2, Shaopei Shi2, Yue Zhang3,4

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 647-657, 2021, DOI:10.32604/cmc.2020.012869

    Abstract The estimation of image resampling factors is an important problem in image forensics. Among all the resampling factor estimation methods, spectrumbased methods are one of the most widely used methods and have attracted a lot of research interest. However, because of inherent ambiguity, spectrum-based methods fail to discriminate upscale and downscale operations without any prior information. In general, the application of resampling leaves detectable traces in both spatial domain and frequency domain of a resampled image. Firstly, the resampling process will introduce correlations between neighboring pixels. In this case, a set of periodic pixels that are correlated to their neighbors… More >

  • Open Access


    Improved Teaching Learning Based Optimization and Its Application in Parameter Estimation of Solar Cell Models

    Qinqin Fan1,*, Yilian Zhang2, Zhihuan Wang1

    Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 1-12, 2020, DOI:10.31209/2018.100000042

    Abstract Weak global exploration capability is one of the primary drawbacks in teaching learning based optimization (TLBO). To enhance the search capability of TLBO, an improved TLBO (ITLBO) is introduced in this study. In ITLBO, a uniform random number is replaced by a normal random number, and a weighted average position of the current population is chosen as the other teacher. The performance of ITLBO is compared with that of five meta-heuristic algorithms on a well-known test suite. Results demonstrate that the average performance of ITLBO is superior to that of the compared algorithms. Finally, ITLBO is employed to estimate parameters… More >

  • Open Access


    The SLAM Algorithm for Multiple Robots Based on Parameter Estimation

    MengYuan Chen1,2

    Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 593-602, 2018, DOI:10.31209/2018.100000026

    Abstract With the increasing number of feature points of a map, the dimension of systematic observation is added gradually, which leads to the deviation of the volume points from the desired trajectory and significant errors on the state estimation. An Iterative Squared-Root Cubature Kalman Filter (ISR-CKF) algorithm proposed is aimed at improving the SR-CKF algorithm on the simultaneous localization and mapping (SLAM). By introducing the method of iterative updating, the sample points are re-determined by the estimated value and the square root factor, which keeps the distortion small in the highly nonlinear environment and improves the precision further. A robust tracking… More >

  • Open Access


    The Identification of the Wind Parameters Based on the Interactive Multi-Models

    Lihua Zhu1, Zhiqiang Wu1, Lei Wang2, Yu Wang1, *

    CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 405-418, 2020, DOI:10.32604/cmc.2020.010124

    Abstract The wind as a natural phenomenon would cause the derivation of the pesticide drops during the operation of agricultural unmanned aerial vehicles (UAV). In particular, the changeable wind makes it difficult for the precision agriculture. For accurate spraying of pesticide, it is necessary to estimate the real-time wind parameters to provide the correction reference for the UAV path. Most estimation algorithms are model based, and as such, serious errors can arise when the models fail to properly fit the physical wind motions. To address this problem, a robust estimation model is proposed in this paper. Considering the diversity of the… More >

  • Open Access


    Mixed Noise Parameter Estimation Based on Variance Stable Transform

    Ling Ding1, 2, Huyin Zhang1, *, Jinsheng Xiao3, Junfeng Lei3, Fang Xu3, Shejie Lu2

    CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.2, pp. 675-690, 2020, DOI:10.32604/cmes.2020.07987

    Abstract The ultimate goal of image denoising from video is to improve the given image, which can reduce noise interference to ensure image quality. Through denoising technology, image quality can have effectively optimized, signal-to-noise ratio can have increased, and the original mage information can have better reflected. As an important preprocessing method, people have made extensive research on image denoising algorithm. Video denoising needs to take into account the various level of noise. Therefore, the estimation of noise parameters is particularly important. This paper presents a noise estimation method based on variance stability transformation, which estimates the parameters of variance stability… More >

  • Open Access


    Two-Dimensional Interpolation Criterion Using DFT Coefficients

    Yuan Chen1, Liangtao Duan1, Weize Sun2, *, Jingxin Xu3

    CMC-Computers, Materials & Continua, Vol.62, No.2, pp. 849-859, 2020, DOI:10.32604/cmc.2020.07115

    Abstract In this paper, we address the frequency estimator for 2-dimensional (2-D) complex sinusoids in the presence of white Gaussian noise. With the use of the sinc function model of the discrete Fourier transform (DFT) coefficients on the input data, a fast and accurate frequency estimator is devised, where only the DFT coefficient with the highest magnitude and its four neighbors are required. Variance analysis is also included to investigate the accuracy of the proposed algorithm. Simulation results are conducted to demonstrate the superiority of the developed scheme, in terms of the estimation performance and computational complexity. More >

  • Open Access


    Observability Analysis in Parameters Estimation of an Uncooperative Space Target

    Xianghao Hou1, *, Gang Qiao1

    CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.1, pp. 175-205, 2020, DOI:10.32604/cmes.2020.08452

    Abstract To study the parameter estimating effects of a free-floating tumbling space target, the extended Kalman filter (EKF) scheme is utilized with different high-nonlinear translational and rotational coupled kinematic & dynamic models on the LIDAR measurements. Applying the aforementioned models and measurements results in the situation where one single state can be estimated differently with varying accuracies since the EKFs based on different models have different observabilities. In the proposed EKFs, the traditional quaternions based kinematics and dynamics and the dual vector quaternions (DVQ) based kinematics and dynamics are used for the modeling of the relative motions between a chaser satellite… More >

  • Open Access


    A Control Algorithm for the Optimization of Batch Reactor-Based Processes

    Yanling Bai1,*, Feng Liu2

    FDMP-Fluid Dynamics & Materials Processing, Vol.15, No.4, pp. 307-319, 2019, DOI:10.32604/fdmp.2019.07833

    Abstract Levenberg-Marquardt (LM) algorithm is applied for the optimization of the heat transfer of a batch reactor. The validity of the approach is verified through comparison with experimental results. It is found that the mathematical model can properly describe the heat transfer relationships characterizing the considered system, with the error being kept within ±2°C. Indeed, the difference between the actual measured values and the model calculated value curve is within ±1.5°C, which is in agreement with the model assumptions and demonstrates the reliability and effectiveness of the algorithm applied to the batch reactor heat transfer model. Therefore, the present work provides… More >

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