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  • Open Access

    ARTICLE

    Quantum Fuzzy Regression Model for Uncertain Environment

    Tiansu Chen1,2, Shi bin Zhang1,2, Qirun Wang3, Yan Chang1,2,*

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2759-2773, 2023, DOI:10.32604/cmc.2023.033284

    Abstract In the era of big data, traditional regression models cannot deal with uncertain big data efficiently and accurately. In order to make up for this deficiency, this paper proposes a quantum fuzzy regression model, which uses fuzzy theory to describe the uncertainty in big data sets and uses quantum computing to exponentially improve the efficiency of data set preprocessing and parameter estimation. In this paper, data envelopment analysis (DEA) is used to calculate the degree of importance of each data point. Meanwhile, Harrow, Hassidim and Lloyd (HHL) algorithm and quantum swap circuits are used to improve the efficiency of high-dimensional… More >

  • Open Access

    ARTICLE

    Prediction of Uncertainty Estimation and Confidence Calibration Using Fully Convolutional Neural Network

    Karim Gasmi1,*, Lassaad Ben Ammar2,, Hmoud Elshammari4, Fadwa Yahya2

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2557-2573, 2023, DOI:10.32604/cmc.2023.033270

    Abstract Convolution neural networks (CNNs) have proven to be effective clinical imaging methods. This study highlighted some of the key issues within these systems. It is difficult to train these systems in a limited clinical image databases, and many publications present strategies including such learning algorithm. Furthermore, these patterns are known for making a highly reliable prognosis. In addition, normalization of volume and losses of dice have been used effectively to accelerate and stabilize the training. Furthermore, these systems are improperly regulated, resulting in more confident ratings for correct and incorrect classification, which are inaccurate and difficult to understand. This study… More >

  • Open Access

    ARTICLE

    Backstepping Sliding Mode Control Based on Extended State Observer for Hydraulic Servo System

    Zhenshuai Wan*, Yu Fu, Chong Liu, Longwang Yue

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3565-3581, 2023, DOI:10.32604/iasc.2023.036601

    Abstract Hydraulic servo system plays an important role in industrial fields due to the advantages of high response, small size-to-power ratio and large driving force. However, inherent nonlinear behaviors and modeling uncertainties are the main obstacles for hydraulic servo system to achieve high tracking performance. To deal with these difficulties, this paper presents a backstepping sliding mode controller to improve the dynamic tracking performance and anti-interference ability. For this purpose, the nonlinear dynamic model is firstly established, where the nonlinear behaviors and modeling uncertainties are lumped as one term. Then, the extended state observer is introduced to estimate the lumped disturbance.… More >

  • Open Access

    ARTICLE

    Reliability-Based Topology Optimization of Fail-Safe Structures Using Moving Morphable Bars

    Xuan Wang1,2, Yuankun Shi2, Van-Nam Hoang3, Zeng Meng2,*, Kai Long4,*, Yuesheng Wang1

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 3173-3195, 2023, DOI:10.32604/cmes.2023.025501

    Abstract This paper proposes an effective reliability design optimization method for fail-safe topology optimization (FSTO) considering uncertainty based on the moving morphable bars method to establish the ideal balance between cost and robustness, reliability and structural safety. To this end, a performance measure approach (PMA)-based double-loop optimization algorithm is developed to minimize the relative volume percentage while achieving the reliability criterion. To ensure the compliance value of the worst failure case can better approximate the quantified design requirement, a p-norm constraint approach with correction parameter is introduced. Finally, the significance of accounting for uncertainty in the fail-safe design is illustrated by… More > Graphic Abstract

    Reliability-Based Topology Optimization of Fail-Safe Structures Using Moving Morphable Bars

  • Open Access

    ARTICLE

    Structural Interval Reliability Algorithm Based on Bernstein Polynomials and Evidence Theory

    Xu Zhang1, Jianchao Ni2, Juxi Hu3,*, Weisi Chen4

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 1947-1960, 2023, DOI:10.32604/csse.2023.035118

    Abstract Structural reliability is an important method to measure the safety performance of structures under the influence of uncertain factors. Traditional structural reliability analysis methods often convert the limit state function to the polynomial form to measure whether the structure is invalid. The uncertain parameters mainly exist in the form of intervals. This method requires a lot of calculation and is often difficult to achieve efficiently. In order to solve this problem, this paper proposes an interval variable multivariate polynomial algorithm based on Bernstein polynomials and evidence theory to solve the structural reliability problem with cognitive uncertainty. Based on the non-probabilistic… More >

  • Open Access

    ARTICLE

    Optimizing Service Stipulation Uncertainty with Deep Reinforcement Learning for Internet Vehicle Systems

    Zulqar Nain1, B. Shahana2, Shehzad Ashraf Chaudhry3, P. Viswanathan4, M.S. Mekala1, Sung Won Kim1,*

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5705-5721, 2023, DOI:10.32604/cmc.2023.033194

    Abstract Fog computing brings computational services near the network edge to meet the latency constraints of cyber-physical System (CPS) applications. Edge devices enable limited computational capacity and energy availability that hamper end user performance. We designed a novel performance measurement index to gauge a device’s resource capacity. This examination addresses the offloading mechanism issues, where the end user (EU) offloads a part of its workload to a nearby edge server (ES). Sometimes, the ES further offloads the workload to another ES or cloud server to achieve reliable performance because of limited resources (such as storage and computation). The manuscript aims to… More >

  • Open Access

    ARTICLE

    Non-Negative Adaptive Mechanism-Based Sliding Mode Control for Parallel Manipulators with Uncertainties

    Van-Truong Nguyen*

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2771-2787, 2023, DOI:10.32604/cmc.2023.033460

    Abstract In this paper, a non-negative adaptive mechanism based on an adaptive nonsingular fast terminal sliding mode control strategy is proposed to have finite time and high-speed trajectory tracking for parallel manipulators with the existence of unknown bounded complex uncertainties and external disturbances. The proposed approach is a hybrid scheme of the online non-negative adaptive mechanism, tracking differentiator, and nonsingular fast terminal sliding mode control (NFTSMC). Based on the online non-negative adaptive mechanism, the proposed control can remove the assumption that the uncertainties and disturbances must be bounded for the NFTSMC controllers. The proposed controller has several advantages such as simple… More >

  • Open Access

    ARTICLE

    Energy Management of Networked Smart Railway Stations Considering Regenerative Braking, Energy Storage System, and Photovoltaic Units

    Saeed Akbari1, Seyed Saeed Fazel1,*, Hamed Hashemi-Dezaki2,3

    Energy Engineering, Vol.120, No.1, pp. 69-86, 2023, DOI:10.32604/ee.2022.024121

    Abstract The networking of microgrids has received significant attention in the form of a smart grid. In this paper, a set of smart railway stations, which is assumed as microgrids, is connected together. It has been tried to manage the energy exchanged between the networked microgrids to reduce received energy from the utility grid. Also, the operational costs of stations under various conditions decrease by applying the proposed method. The smart railway stations are studied in the presence of photovoltaic (PV) units, energy storage systems (ESSs), and regenerative braking strategies. Studying regenerative braking is one of the essential contributions. Moreover, the… More > Graphic Abstract

    Energy Management of Networked Smart Railway Stations Considering Regenerative Braking, Energy Storage System, and Photovoltaic Units

  • Open Access

    ARTICLE

    A New Framework for Employing Responsive End-Users Using FAHP and PSO Algorithm

    Reza Etemad1, Mohammad Sadegh Ghazizadeh1, Mehrdad Ahmadi Kamarposhti2,*, Ilhami Colak3, Kei Eguchi4

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 951-964, 2023, DOI:10.32604/cmc.2023.032631

    Abstract The capacitor bank and synchronous condenser have been the only available sources of reactive power. Nowadays, most of the appliances use a power electronic interface for their connection. Applying a power electronic interface adds many features to these appliances. One of the promising features is their capability to interact with Volt-VAR programs. In this paper was investigated the reactive power interaction of the end-user appliances. For this purpose, the distribution network buses are ranked based on their effectiveness, followed by studying their interaction in the Volt-VAR program. To be able to consider the uncertainties, Probability Density Function (PDF) curve was… More >

  • Open Access

    ARTICLE

    An Uncertainty Analysis and Reliability-Based Multidisciplinary Design Optimization Method Using Fourth-Moment Saddlepoint Approximation

    Yongqiang Guo1,2,*, Zhiyuan Lv3

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.3, pp. 1855-1870, 2023, DOI:10.32604/cmes.2022.022211

    Abstract In uncertainty analysis and reliability-based multidisciplinary design and optimization (RBMDO) of engineering structures, the saddlepoint approximation (SA) method can be utilized to enhance the accuracy and efficiency of reliability evaluation. However, the random variables involved in SA should be easy to handle. Additionally, the corresponding saddlepoint equation should not be complicated. Both of them limit the application of SA for engineering problems. The moment method can construct an approximate cumulative distribution function of the performance function based on the first few statistical moments. However, the traditional moment matching method is not very accurate generally. In order to take advantage of… More >

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