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  • Open Access

    ARTICLE

    A Predictive Energy Management Strategies for Mining Dump Trucks

    Yixuan Yu, Yulin Wang*, Qingcheng Li, Bowen Jiao

    Energy Engineering, Vol.121, No.3, pp. 769-788, 2024, DOI:10.32604/ee.2023.044042

    Abstract The plug-in hybrid vehicles (PHEV) technology can effectively address the issues of poor dynamics and higher energy consumption commonly found in traditional mining dump trucks. Meanwhile, plug-in hybrid electric trucks can achieve excellent fuel economy through efficient energy management strategies (EMS). Therefore, a series hybrid system is constructed based on a 100-ton mining dump truck in this paper. And inspired by the dynamic programming (DP) algorithm, a predictive equivalent consumption minimization strategy (P-ECMS) based on the DP optimization result is proposed. Based on the optimal control manifold and the SOC reference trajectory obtained by the DP algorithm, the P-ECMS strategy… More >

  • Open Access

    ARTICLE

    Multi-Time Scale Operation and Simulation Strategy of the Park Based on Model Predictive Control

    Jun Zhao*, Chaoying Yang, Ran Li, Jinge Song

    Energy Engineering, Vol.121, No.3, pp. 747-767, 2024, DOI:10.32604/ee.2023.042806

    Abstract Due to the impact of source-load prediction power errors and uncertainties, the actual operation of the park will have a wide range of fluctuations compared with the expected state, resulting in its inability to achieve the expected economy. This paper constructs an operating simulation model of the park power grid operation considering demand response and proposes a multi-time scale operating simulation method that combines day-ahead optimization and model predictive control (MPC). In the day-ahead stage, an operating simulation plan that comprehensively considers the user’s side comfort and operating costs is proposed with a long-term time scale of 15 min. In… More >

  • Open Access

    ARTICLE

    Peak Shaving Strategy of Concentrating Solar Power Generation Based on Multi-Time-Scale and Considering Demand Response

    Lei Fang*, Haiying Dong, Xiaofei Zhen, Shuaibing Li

    Energy Engineering, Vol.121, No.3, pp. 661-679, 2024, DOI:10.32604/ee.2023.029823

    Abstract According to the multi-time-scale characteristics of power generation and demand-side response (DR) resources, as well as the improvement of prediction accuracy along with the approaching operating point, a rolling peak shaving optimization model consisting of three different time scales has been proposed. The proposed peak shaving optimization model considers not only the generation resources of two different response speeds but also the two different DR resources and determines each unit combination, generation power, and demand response strategy on different time scales so as to participate in the peaking of the power system by taking full advantage of the fast response… More >

  • Open Access

    ARTICLE

    A New Flower Pollination Algorithm Strategy for MPPT of Partially Shaded Photovoltaic Arrays

    Muhannad J. Alshareef*

    Intelligent Automation & Soft Computing, Vol.38, No.3, pp. 297-313, 2023, DOI:10.32604/iasc.2023.046722

    Abstract Photovoltaic (PV) systems utilize maximum power point tracking (MPPT) controllers to optimize power output amidst varying environmental conditions. However, the presence of multiple peaks resulting from partial shading poses a challenge to the tracking operation. Under partial shade conditions, the global maximum power point (GMPP) may be missed by most traditional maximum power point tracker. The flower pollination algorithm (FPA) and particle swarm optimization (PSO) are two examples of metaheuristic techniques that can be used to solve the issue of failing to track the GMPP. This paper discusses and resolves all issues associated with using the standard FPA method as… More >

  • Open Access

    ARTICLE

    Coverless Image Steganography System Based on Maze Game Generation

    Al Hussien Seddik Saad1, Mohammed S. Reda2, Gamal M. Behery2, Ahmed A. El-harby2, Mohammed Baz3, Mohamed Abouhawwash4,5,*, Ahmed Ismail Ebada6

    Intelligent Automation & Soft Computing, Vol.38, No.2, pp. 125-138, 2023, DOI:10.32604/iasc.2023.032084

    Abstract The trend of digital information transformation has become a topic of interest. Many data are threatening; thus, protecting such data from attackers is considered an essential process. Recently, a new methodology for data concealing has been suggested by researchers called coverless steganography. Coverless steganography can be accomplished either by building an image database to match its image subblocks with the secret message to obtain the stego image or by generating an image. This paper proposes a coverless image steganography system based on pure image generation using secret message bits with a capacity higher than the other traditional systems. The system… More >

  • Open Access

    ARTICLE

    The Relationship between Father-Love Absence and Non-Suicidal Self-Injury: Based on Nock’s Integrated Theoretical Model of NSSI

    Yuhan Zhou1,2,#, Xiaojun Li3,#, Yanhui Xiang1,2,4,*

    International Journal of Mental Health Promotion, Vol.26, No.1, pp. 31-38, 2024, DOI:10.32604/ijmhp.2023.043167

    Abstract Fathers play an important role in children’s development throughout their lives, and Father-Love Absence (FLA) leads to more behavioral problems, including Non-Suicidal Self-Injury (NSSI). However, there has been no research on the relationship between FLA and NSSI and its influencing mechanism. This study is based on Nock’s integrated theoretical model of NSSI, aiming to explore the influence of FLA on NSSI and further investigate the mechanism of Subjective Vitality (SV) and Forgiveness (FORG). This study recruited 1795 adolescents in central China to complete four scales, including Father-Love Absence Scale (FLAS), The Subjective Vitality Scale (SVS), The Tendency to Forgive Scale… More >

  • Open Access

    ARTICLE

    An Industrial Intrusion Detection Method Based on Hybrid Convolutional Neural Networks with Improved TCN

    Zhihua Liu, Shengquan Liu*, Jian Zhang

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 411-433, 2024, DOI:10.32604/cmc.2023.046237

    Abstract Network intrusion detection systems (NIDS) based on deep learning have continued to make significant advances. However, the following challenges remain: on the one hand, simply applying only Temporal Convolutional Networks (TCNs) can lead to models that ignore the impact of network traffic features at different scales on the detection performance. On the other hand, some intrusion detection methods consider multi-scale information of traffic data, but considering only forward network traffic information can lead to deficiencies in capturing multi-scale temporal features. To address both of these issues, we propose a hybrid Convolutional Neural Network that supports a multi-output strategy (BONUS) for… More >

  • Open Access

    ARTICLE

    Enhanced Steganalysis for Color Images Using Curvelet Features and Support Vector Machine

    Arslan Akram1,2, Imran Khan1, Javed Rashid2,3, Mubbashar Saddique4,*, Muhammad Idrees4, Yazeed Yasin Ghadi5, Abdulmohsen Algarni6

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1311-1328, 2024, DOI:10.32604/cmc.2023.040512

    Abstract Algorithms for steganography are methods of hiding data transfers in media files. Several machine learning architectures have been presented recently to improve stego image identification performance by using spatial information, and these methods have made it feasible to handle a wide range of problems associated with image analysis. Images with little information or low payload are used by information embedding methods, but the goal of all contemporary research is to employ high-payload images for classification. To address the need for both low- and high-payload images, this work provides a machine-learning approach to steganography image classification that uses Curvelet transformation to… More >

  • Open Access

    ARTICLE

    Research on Anti-Fluctuation Control of Winding Tension System Based on Feedforward Compensation

    Yujie Duan1, Jianguo Liang1,*, Jianglin Liu1, Haifeng Gao1, Yinhui Li2, Jinzhu Zhang1, Xinyu Wen3

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1239-1261, 2024, DOI:10.32604/cmes.2023.044400

    Abstract In the fiber winding process, strong disturbance, uncertainty, strong coupling, and fiber friction complicate the winding constant tension control. In order to effectively reduce the influence of these problems on the tension output, this paper proposed a tension fluctuation rejection strategy based on feedforward compensation. In addition to the bias harmonic curve of the unknown state, the tension fluctuation also contains the influence of bounded noise. A tension fluctuation observer (TFO) is designed to cancel the uncertain periodic signal, in which the frequency generator is used to estimate the critical parameter information. Then, the fluctuation signal is reconstructed by a… More >

  • Open Access

    ARTICLE

    Highly Accurate Golden Section Search Algorithms and Fictitious Time Integration Method for Solving Nonlinear Eigenvalue Problems

    Chein-Shan Liu1, Jian-Hung Shen2, Chung-Lun Kuo1, Yung-Wei Chen2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1317-1335, 2024, DOI:10.32604/cmes.2023.030618

    Abstract This study sets up two new merit functions, which are minimized for the detection of real eigenvalue and complex eigenvalue to address nonlinear eigenvalue problems. For each eigen-parameter the vector variable is solved from a nonhomogeneous linear system obtained by reducing the number of eigen-equation one less, where one of the nonzero components of the eigenvector is normalized to the unit and moves the column containing that component to the right-hand side as a nonzero input vector. 1D and 2D golden section search algorithms are employed to minimize the merit functions to locate real and complex eigenvalues. Simultaneously, the real… More >

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