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  • 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

    Rao Algorithms-Based Structure Optimization for Heterogeneous Wireless Sensor Networks

    Shereen K. Refaay1, Samia A. Ali2, Moumen T. El-Melegy2, Louai A. Maghrabi3, Hamdy H. El-Sayed1,*

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 873-897, 2024, DOI:10.32604/cmc.2023.044982

    Abstract The structural optimization of wireless sensor networks is a critical issue because it impacts energy consumption and hence the network’s lifetime. Many studies have been conducted for homogeneous networks, but few have been performed for heterogeneous wireless sensor networks. This paper utilizes Rao algorithms to optimize the structure of heterogeneous wireless sensor networks according to node locations and their initial energies. The proposed algorithms lack algorithm-specific parameters and metaphorical connotations. The proposed algorithms examine the search space based on the relations of the population with the best, worst, and randomly assigned solutions. The proposed algorithms can be evaluated using any… More >

  • Open Access

    ARTICLE

    Flexible Load Participation in Peaking Shaving and Valley Filling Based on Dynamic Price Incentives

    Lifeng Wang1, Jing Yu2,*, Wenlu Ji1

    Energy Engineering, Vol.121, No.2, pp. 523-540, 2024, DOI:10.32604/ee.2023.041881

    Abstract Considering the widening of the peak-valley difference in the power grid and the difficulty of the existing fixed time-of-use electricity price mechanism in meeting the energy demand of heterogeneous users at various moments or motivating users, the design of a reasonable dynamic pricing mechanism to actively engage users in demand response becomes imperative for power grid companies. For this purpose, a power grid-flexible load bilevel model is constructed based on dynamic pricing, where the leader is the dispatching center and the lower-level flexible load acts as the follower. Initially, an upper-level day-ahead dispatching model for the power grid is established,… More >

  • Open Access

    RETRACTION

    Retraction: Physiological Responses of Pea Plants to Salinity and Gibberellic Acid

    Houneida Attia1,2,*

    Phyton-International Journal of Experimental Botany, Vol.92, No.12, pp. 3371-3371, 2023, DOI:10.32604/phyton.2023.048187

    Abstract This article has no abstract. More >

  • Open Access

    ARTICLE

    Design and Implementation of Quantum Repeaters: Insights on Quantum Entanglement Purification

    Karoki A. Mũgambi*, Geoffrey O. Okeng’o

    Journal of Quantum Computing, Vol.5, pp. 25-40, 2023, DOI:10.32604/jqc.2023.045654

    Abstract Quantum communication is a groundbreaking technology that is driving the future of information transmission and communication technologies to a new paradigm. It relies on quantum entanglement to facilitate the transmission of quantum states between parties. Quantum repeaters are crucial for facilitating long-distance quantum communication. These quantum devices act as intermediaries between adjacent communication channel segments within a fragmented quantum network, allowing for entanglement swapping between the channel segments. This entanglement swapping process establishes entanglement links between the endpoints of adjacent segments, gradually creating a continuous entanglement connection over the entire length of the transmission channel. The established quantum link can… More >

  • Open Access

    ARTICLE

    Evaluating the Derivative Value of Smart Grid Investment under Dual Carbon Target: A Hybrid Multi-Criteria Decision-Making Analysis

    Na Yu1, Changzheng Gao2, Xiuna Wang2, Dongwei Li2,*, Weiyang You2

    Energy Engineering, Vol.120, No.12, pp. 2879-2901, 2023, DOI:10.32604/ee.2023.029426

    Abstract With the goal of “carbon peaking and carbon neutralization”, it is an inevitable trend for investing smart grid to promote the large-scale grid connection of renewable energy. Smart grid investment has a significant driving effect (derivative value), and evaluating this value can help to more accurately grasp the external effects of smart grid investment and support the realization of industrial linkage value with power grid investment as the core. Therefore, by analyzing the characterization of the derivative value of smart grid driven by investment, this paper constructs the evaluation index system of the derivative value of smart grid investment including… More >

  • Open Access

    ARTICLE

    Assessment of Dependent Performance Shaping Factors in SPAR-H Based on Pearson Correlation Coefficient

    Xiaoyan Su1,*, Shuwen Shang1, Zhihui Xu2, Hong Qian1, Xiaolei Pan1

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1813-1826, 2024, DOI:10.32604/cmes.2023.030957

    Abstract With the improvement of equipment reliability, human factors have become the most uncertain part in the system. The standardized Plant Analysis of Risk-Human Reliability Analysis (SPAR-H) method is a reliable method in the field of human reliability analysis (HRA) to evaluate human reliability and assess risk in large complex systems. However, the classical SPAR-H method does not consider the dependencies among performance shaping factors (PSFs), which may cause overestimation or underestimation of the risk of the actual situation. To address this issue, this paper proposes a new method to deal with the dependencies among PSFs in SPAR-H based on the… More > Graphic Abstract

    Assessment of Dependent Performance Shaping Factors in SPAR-H Based on Pearson Correlation Coefficient

  • Open Access

    ARTICLE

    Using Speaker-Specific Emotion Representations in Wav2vec 2.0-Based Modules for Speech Emotion Recognition

    Somin Park1, Mpabulungi Mark1, Bogyung Park2, Hyunki Hong1,*

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 1009-1030, 2023, DOI:10.32604/cmc.2023.041332

    Abstract Speech emotion recognition is essential for frictionless human-machine interaction, where machines respond to human instructions with context-aware actions. The properties of individuals’ voices vary with culture, language, gender, and personality. These variations in speaker-specific properties may hamper the performance of standard representations in downstream tasks such as speech emotion recognition (SER). This study demonstrates the significance of speaker-specific speech characteristics and how considering them can be leveraged to improve the performance of SER models. In the proposed approach, two wav2vec-based modules (a speaker-identification network and an emotion classification network) are trained with the Arcface loss. The speaker-identification network has a… More >

  • Open Access

    ARTICLE

    Credit Card Fraud Detection on Original European Credit Card Holder Dataset Using Ensemble Machine Learning Technique

    Yih Bing Chu*, Zhi Min Lim, Bryan Keane, Ping Hao Kong, Ahmed Rafat Elkilany, Osama Hisham Abusetta

    Journal of Cyber Security, Vol.5, pp. 33-46, 2023, DOI:10.32604/jcs.2023.045422

    Abstract The proliferation of digital payment methods facilitated by various online platforms and applications has led to a surge in financial fraud, particularly in credit card transactions. Advanced technologies such as machine learning have been widely employed to enhance the early detection and prevention of losses arising from potentially fraudulent activities. However, a prevalent approach in existing literature involves the use of extensive data sampling and feature selection algorithms as a precursor to subsequent investigations. While sampling techniques can significantly reduce computational time, the resulting dataset relies on generated data and the accuracy of the pre-processing machine learning models employed. Such… More >

  • Open Access

    ARTICLE

    Multi-Objective Image Optimization of Product Appearance Based on Improved NSGA-Ⅱ

    Yinxue Ao1, Jian Lv1,*, Qingsheng Xie1, Zhengming Zhang2

    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3049-3074, 2023, DOI:10.32604/cmc.2023.040088

    Abstract A second-generation fast Non-dominated Sorting Genetic Algorithm product shape multi-objective imagery optimization model based on degradation (DNSGA-II) strategy is proposed to make the product appearance optimization scheme meet the complex emotional needs of users for the product. First, the semantic differential method and K-Means cluster analysis are applied to extract the multi-objective imagery of users; then, the product multidimensional scale analysis is applied to classify the research objects, and again the reference samples are screened by the semantic differential method, and the samples are parametrized in two dimensions by using elliptic Fourier analysis; finally, the fuzzy dynamic evaluation function is… More >

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