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  • Open Access

    ARTICLE

    Low Carbon Economic Dispatch of Integrated Energy System Considering Power Supply Reliability and Integrated Demand Response

    Jian Dong, Haixin Wang, Junyou Yang*, Liu Gao, Kang Wang, Xiran Zhou

    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.1, pp. 319-340, 2022, DOI:10.32604/cmes.2022.020394

    Abstract Integrated energy system optimization scheduling can improve energy efficiency and low carbon economy. This paper studies an electric-gas-heat integrated energy system, including the carbon capture system, energy coupling equipment, and renewable energy. An energy scheduling strategy based on deep reinforcement learning is proposed to minimize operation cost, carbon emission and enhance the power supply reliability. Firstly, the low-carbon mathematical model of combined thermal and power unit, carbon capture system and power to gas unit (CCP) is established. Subsequently, we establish a low carbon multi-objective optimization model considering system operation cost, carbon emissions cost, integrated demand response, wind and photovoltaic curtailment,… More >

  • Open Access

    ARTICLE

    Interval-Valued Neutrosophic Soft Expert Set from Real Space to Complex Space

    Faisal Al-Sharqi1,2, Abd Ghafur Ahmad1,*, Ashraf Al-Quran3

    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.1, pp. 267-293, 2022, DOI:10.32604/cmes.2022.019684

    Abstract A fuzzy system is a novel computing technique that accesses uncertain information by fuzzy representation. In the decision-making process, fuzzy system and soft computing are effective tools that are tolerant to imprecision, uncertainty, and partial truths. Evolutionary fuzzy systems have been developed with the appearance of interval fuzzy, dual fuzzy, hesitant fuzzy, neutrosophic, plithogenic representations, etc. Moreover, by capturing compound features and convey multi-dimensional data, complex numbers are utilized to generalize fuzzy and neutrosophic fuzzy sets. In this paper, a representation of neutrosophic soft expert systems based on the real and complex numbers in the interval form is proposed. The… More >

  • Open Access

    ARTICLE

    A Frost Heaving Prediction Approach for Ground Uplift Simulation Due to Freeze-Sealing Pipe Roof Method

    Shengjun Deng1,2,3, Haolin Chen1, Xiaonan Gong2, Jiajin Zhou2, Xiangdong Hu4, Gang Jiang1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.1, pp. 251-266, 2022, DOI:10.32604/cmes.2022.020388

    Abstract Freeze-sealing pipe roof method is applied in the Gongbei tunnel, which causes the ground surface uplift induced by frost heave. A frost heaving prediction approach based on the coefficient of cold expansion is proposed to simulate the ground deformation of the Gongbei tunnel. The coefficient of cold expansion in the model and the frost heaving rate from the frost heave test under the hydration condition can achieve a good correspondence making the calculation result closer to the actual engineering. The ground surface uplift along the lateral and longitudinal direction are respectively analyzed and compared with the field measured data to… More >

  • Open Access

    ARTICLE

    Foundation Treatment in Urban Underground Engineering Using Big Data Analysis for Smart City Applications

    Fei Liu1,2, Yunkai Zhang1,2, Jian Zhang3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.1, pp. 153-172, 2022, DOI:10.32604/cmes.2022.017967

    Abstract A core element of the sustainable approach to global living quality improvement can now become the intensive and organized usage of underground space. There is a growing interest in underground building and growth worldwide. The reduced consumption of electricity, effective preservation of green land, sustainable wastewater and sewage treatment, efficient reverse degradation of the urban environment, and reliable critical infrastructure management can improve the quality of life. At the same time, technological innovations such as artificial intelligence (AI), cloud computing (CC), the internet of things (IoT), and big data analytics (BDA) play a significant role in improved quality of life.… More >

  • Open Access

    ARTICLE

    Asymptotic Approximations of Apostol-Tangent Polynomials in Terms of Hyperbolic Functions

    Cristina B. Corcino1,2, Wilson D. Castañeda Jr.3, Roberto B. Corcino1,2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.1, pp. 133-151, 2022, DOI:10.32604/cmes.2022.019965

    Abstract The tangent polynomials Tn (z) are generalization of tangent numbers or the Euler zigzag numbers Tn. In particular, Tn (0) = Tn. These polynomials are closely related to Bernoulli, Euler and Genocchi polynomials. One of the extensions and analogues of special polynomials that attract the attention of several mathematicians is the Apostoltype polynomials. One of these Apostol-type polynomials is the Apostol-tangent polynomials Tn(z, λ). When λ = 1, Tn (z, 1) = Tn(z). The use of hyperbolic functions to derive asymptotic approximations of polynomials together with saddle point method was applied to the Bernoulli and Euler polynomials by Lopez and… More >

  • Open Access

    ARTICLE

    Image Encryption Algorithm Based on New Fractional Beta Chaotic Maps

    Rabha W. Ibrahim1,*, Hayder Natiq2, Ahmed Alkhayyat3, Alaa Kadhim Farhan4, Nadia M. G. Al-Saidi5, Dumitru Baleanu6,7,8

    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.1, pp. 119-131, 2022, DOI:10.32604/cmes.2022.018343

    Abstract In this study, a new algorithm of fractional beta chaotic maps is proposed to generate chaotic sequences for image encryption. The proposed technique generates multi random sequences by shuffling the image pixel position. This technique is used to blur the pixels connecting the input and encrypted images and to increase the attack resistance. The proposed algorithm makes the encryption process sophisticated by using fractional chaotic maps, which hold the properties of pseudo-randomness. The fractional beta sequences are utilized to alter the image pixels to decryption attacks. The experimental results proved that the proposed image encryption algorithm successfully encrypted and decrypted… More >

  • Open Access

    ARTICLE

    An Optimized Convolutional Neural Network with Combination Blocks for Chinese Sign Language Identification

    Yalan Gao, Yanqiong Zhang, Xianwei Jiang*

    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.1, pp. 95-117, 2022, DOI:10.32604/cmes.2022.019970

    Abstract (Aim) Chinese sign language is an essential tool for hearing-impaired to live, learn and communicate in deaf communities. Moreover, Chinese sign language plays a significant role in speech therapy and rehabilitation. Chinese sign language identification can provide convenience for those hearing impaired people and eliminate the communication barrier between the deaf community and the rest of society. Similar to the research of many biomedical image processing (such as automatic chest radiograph processing, diagnosis of chest radiological images, etc.), with the rapid development of artificial intelligence, especially deep learning technologies and algorithms, sign language image recognition ushered in the spring. This… More >

  • Open Access

    ARTICLE

    Edge Detection of COVID-19 CT Image Based on GF_SSR, Improved Multiscale Morphology, and Adaptive Threshold

    Shouming Hou1, Chaolan Jia1, Kai Li1, Liya Fan2, Jincheng Guo3,*, Mackenzie Brown4,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.1, pp. 81-94, 2022, DOI:10.32604/cmes.2022.019006

    Abstract Edge detection is an effective method for image segmentation and feature extraction. Therefore, extracting weak edges with the inhomogeneous gray of Corona Virus Disease 2019 (COVID-19) CT images is extremely important. Multiscale morphology has been widely used in the edge detection of medical images due to its excellent boundary detection accuracy. In this paper, we propose a weak edge detection method based on Gaussian filtering and singlescale Retinex (GF_SSR), and improved multiscale morphology and adaptive threshold binarization (IMSM_ATB). As all the CT images have noise, we propose to remove image noise by Gaussian filtering. The edge of CT images is… More >

  • Open Access

    ARTICLE

    A Fast Element-Free Galerkin Method for 3D Elasticity Problems

    Zhijuan Meng1, Yanan Fang1, Yumin Cheng2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.1, pp. 55-79, 2022, DOI:10.32604/cmes.2022.019828

    Abstract In this paper, a fast element-free Galerkin (FEFG) method for three-dimensional (3D) elasticity problems is established. The FEFG method is a combination of the improved element-free Galerkin (IEFG) method and the dimension splitting method (DSM). By using the DSM, a 3D problem is converted to a series of 2D ones, and the IEFG method with a weighted orthogonal function as the basis function and the cubic spline function as the weight function is applied to simulate these 2D problems. The essential boundary conditions are treated by the penalty method. The splitting direction uses the finite difference method (FDM), which can… More >

  • Open Access

    ARTICLE

    Discrete Element Simulations of Ice Load and Mooring Force on Moored Structure in Level Ice

    Hongri Zhu, Shunying Ji*

    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.1, pp. 5-21, 2022, DOI:10.32604/cmes.2022.019991

    Abstract Moored structures are suitable for operations in ice-covered regions owing to their security and efficiency. This paper aims to present a new method for simulating the ice load and mooring force on the moored structure during ice-structure interaction with a spherical Discrete Element Method (DEM). In this method, the level ice and mooring lines consist of bonded sphere elements arranged in different patterns. The level ice model has been widely validated in simulation of the ice load of fixed structures. In the mooring line simulation, a string of spherical elements was jointed with the parallel bond model to simulate the… More >

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