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    Day-Ahead and Intraday Economic Optimization Models of the Stackelberg Game Considering Source-Load Uncertainty by Ning Li, Weibo Liu, Xiaodong Wan, Xiu Ren, Haining Yu

    Published 2025-01-01
    “…In order to enhance the demand response rate on the demand side and the wind power accommodation rate on the supply side, as well as to curtail the operational cost effectively, this paper formulates a day-ahead and intraday economic dispatch model predicated on Stackelberg game theory. …”
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  4. 84

    Prediction of Conductive Anomalies Ahead of the Tunnel by the 3D-Resitivity Forward Modeling in the Whole Space by Daiming Hu, Bülent Tezkan, Mingxin Yue, Xiaodong Yang, Xiaoping Wu, Guanqun Zhou

    Published 2021-01-01
    “…By simulating a large number of models with different tunnel sizes, we propose an equation, which considers the tunnel effect and can predict the water-bearing structures ahead of the tunnel face. The Monte Carlo method is used to evaluate the quality of the predicted model by simulating and comparing 10,000 random models. …”
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    Evaluating the mental and emotional effects of Sahand Bonab thermal power plant greenhouse on rural communities, Case study: Rurlas in Bonab by Mohamad Zaheri, Ali Majnouni-Toutakhane

    Published 2019-06-01
    “…Accordingly, the present study was conducted to measure the pollutants released by Sahand Bonab thermal power plant and to investigate the effects of this pollution on the psychological and psychological pressure of rural residents. …”
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    Warped matrix-variate Gaussian processes with structured kernels for multi-step-ahead driving behaviour prediction by Seiya Takano, Tomohiko Jimbo

    Published 2025-12-01
    “…To achieve high accuracy through recursive multi-step-ahead prediction using GP, large computational resources are required. …”
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  10. 90

    Probabilistic forecasting of multiple plant day-ahead renewable power generation sequences with data privacy preserving by Hong Liu, Zijun Zhang

    Published 2025-01-01
    “…This paper studies the renewable power forecasting task with a more advanced formulation, the probabilistic forecasts of day-ahead power generation sequences of multiple renewable power plants without breaching the privacy of data in each plant. …”
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  11. 91

    Probabilistic Prediction of Dst Storms One‐Day‐Ahead Using Full‐Disk SoHO Images by A. Hu, C. Shneider, A. Tiwari, E. Camporeale

    Published 2022-08-01
    “…The proposed model can predict the probability that Dst < −100 nT 24 hr ahead with a True Skill Statistic (TSS) of 0.62 and Matthews Correlation Coefficient (MCC) of 0.37. …”
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  12. 92

    Day-Ahead Operational Strategy for Virtual Power Plant Considering Green Certificate Classification in Coupled Market by TIAN Yuliang, QIN Zhijun, HUANG Zhen

    Published 2025-01-01
    “…This study proposes an approach to implement both green certificate trading and carbon emissions offsetting in the development of day-ahead operational strategy of the VPP. First,the electricity associated with tradable and nontradable green certificates of the VPP is quantified based on the "use what is generated,and the excess on the grid" mode of renewable energy generation in the VPP. …”
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    Independent aggregation in the nordic day-ahead market: What is the welfare impact of socializing supplier compensation payments? by Kārlis Baltputnis, Tim Schittekatte, Zane Broka

    Published 2025-01-01
    “…Based on a case study utilizing data for the full year of 2018, it is found that subsidizing the participation of IAs in the day-ahead market leads to negative overall welfare impacts due to over-incentivization of demand reduction. …”
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    Development of improved deep learning models for multi-step ahead forecasting of daily river water temperature by Mehdi Gheisari, Jana Shafi, Saeed Kosari, Samaneh Amanabadi, Saeid Mehdizadeh, Christian Fernandez Campusano, Hemn Barzan Abdalla

    Published 2025-12-01
    “…The superior river WT forecasts at both stations during the testing stage were concluded for one day ahead at EEMD-GRU model (USGS 14211010: RMSE = 0.1929 ℃, MAE = 0.1489 ℃, R2 = 0.9988, U95% = 0.3745, MAPE = 1.3608%; USGS 14211720: RMSE = 0.1918 ℃, MAE = 0.1558 ℃, R2 = 0.9990, U95% = 0.3690, MAPE = 1.1790%).…”
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    Caulfield, M. ve Wineburg, S. (2023). Doğrulandı: Doğru Düşünme, Daha Az Kandırılma ve İnternette Neye İnanacağınıza Dair Daha İyi Kararlar Verme Yolları. by Özden Demircioğlu Faydalıgül

    Published 2024-12-01
    “…Yazarlar, bilgi okuryazarlığının önemini vurgularken, insanların internette hangi bilgilere güveneceklerini daha doğru şekilde belirlemelerine yardımcı olmak amacıyla dijital okuryazarlık becerilerini geliştirmek için detaylı adımlar sunmaktadır. …”
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