Výsledky vyhľadávania - Hybrid forecasting algorithm of cooling load

  1. 1

    Forecasting performance comparison of two hybrid machine learning models for cooling load of a large-scale commercial building Autor Xuan, Zhou, Xuehui, Zi, Liequan, Liang, Zubing, Fan, Junwei, Yan, Dongmei, Pan

    ISSN: 2352-7102, 2352-7102
    Vydavateľské údaje: Elsevier Ltd 01.01.2019
    Vydané v Journal of Building Engineering (01.01.2019)
    “…The hourly cooling load forecasting of a commercial building is very hard to be guaranteed with high accuracy…”
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  2. 2

    Hybrid forecasting model of building cooling load based on EMD-LSTM-Markov algorithm Autor Huang, Xiaofei, Han, Yangming, Yan, Junwei, Zhou, Xuan

    ISSN: 0378-7788
    Vydavateľské údaje: Elsevier B.V 15.10.2024
    Vydané v Energy and buildings (15.10.2024)
    “…Precise forecasting of the cooling load (CL) of buildings is crucial for the efficient functioning of central air conditioning systems…”
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  3. 3

    Cooling Load Forecasting Based On Hybrid Machine-Learning Application With Integration Of Meta-heuristic Algorithm Autor Xiaohui Zhang, Lili Pei

    ISSN: 2708-9967
    Vydavateľské údaje: 淡江大學 01.01.2025
    Vydané v 淡江理工學刊 (01.01.2025)
    “… This research presents hybrid machine learning models integrated with advanced optimization techniques tailored for accurately predicting Cooling Load in buildings…”
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  4. 4

    A hybrid forecasting method for cooling load in large public buildings based on improved long short term memory Autor Liu, Zongyi, Yu, Junqi, Feng, Chunyong, Su, Yucong, Dai, Junwei, Chen, Yufei

    ISSN: 2352-7102, 2352-7102
    Vydavateľské údaje: Elsevier Ltd 01.10.2023
    Vydané v Journal of Building Engineering (01.10.2023)
    “… In order to improve the operational efficiency of the air conditioning system, it is crucial to establish an accurate and effective cooling load forecasting model…”
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  5. 5

    A hybrid method of cooling load forecasting for large commercial building based on extreme learning machine Autor Gao, Zhikun, Yu, Junqi, Zhao, Anjun, Hu, Qun, Yang, Siyuan

    ISSN: 0360-5442, 1873-6785
    Vydavateľské údaje: Oxford Elsevier Ltd 01.01.2022
    Vydané v Energy (Oxford) (01.01.2022)
    “…Air conditioning system is extensively used in large commercial buildings. The fast and accurate building cooling load forecasting is the basis for improving…”
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    Hybrid forecasting model of building cooling load based on combined neural network Autor Gao, Zhikun, Yang, Siyuan, Yu, Junqi, Zhao, Anjun

    ISSN: 0360-5442
    Vydavateľské údaje: Elsevier Ltd 15.06.2024
    Vydané v Energy (Oxford) (15.06.2024)
    “…) and long short-term memory neural network (BAS-LSTM) optimized by beetle antennae search algorithm is proposed for building cooling load prediction…”
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  7. 7

    Proposing hybrid prediction approaches with the integration of machine learning models and metaheuristic algorithms to forecast the cooling and heating load of buildings Autor Dasi, He, Ying, Zhang, Ashab, MD Faisal Bin

    ISSN: 0360-5442
    Vydavateľské údaje: Elsevier Ltd 15.03.2024
    Vydané v Energy (Oxford) (15.03.2024)
    “…Accurate prediction of heating and cooling loads in residential buildings is crucial for both researchers and practitioners…”
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  8. 8

    A hybrid prediction model of improved bidirectional long short-term memory network for cooling load based on PCANet and attention mechanism Autor Yan, Xiuying, Ji, Xingxing, Meng, Qinglong, Sun, Hang, Lei, Yu

    ISSN: 0360-5442
    Vydavateľské údaje: Elsevier Ltd 01.04.2024
    Vydané v Energy (Oxford) (01.04.2024)
    “…Accurate and reliable cooling load forecasting is a prerequisite for air-conditioning system control and the basis for building-side energy management…”
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  9. 9

    Intelligent Load Forecasting for Central Air Conditioning Using an Optimized Hybrid Deep Learning Framework Autor He, Wei, Hua, Rui, Xiao, Yulong, Liu, Yuce, Zhou, Chaohui, Li, Chaoshun

    ISSN: 1996-1073, 1996-1073
    Vydavateľské údaje: Basel MDPI AG 01.11.2025
    Vydané v Energies (Basel) (01.11.2025)
    “… To address these issues, this study proposes a novel hybrid forecasting model termed IWOA-BiTCN-BiGRU-SA, which integrates the Improved Whale Optimization Algorithm (IWOA…”
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  10. 10

    Multiple Load Forecasting of Integrated Energy System Based on Sequential-Parallel Hybrid Ensemble Learning Autor You, Wenxia, Guo, Daopeng, Wu, Yonghua, Li, Wenwu

    ISSN: 1996-1073, 1996-1073
    Vydavateľské údaje: Basel MDPI AG 01.04.2023
    Vydané v Energies (Basel) (01.04.2023)
    “… In order to simultaneously reduce the prediction bias and variance, a hybrid ensemble learning method for load forecasting of an integrated energy system combining sequential ensemble learning…”
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  11. 11

    Deep belief network based ensemble approach for cooling load forecasting of air-conditioning system Autor Fu, Guoyin

    ISSN: 0360-5442, 1873-6785
    Vydavateľské údaje: Oxford Elsevier Ltd 01.04.2018
    Vydané v Energy (Oxford) (01.04.2018)
    “… Therefore, a novel deep learning based hybrid approach is originally proposed in this paper for deterministic cooling load forecasting with high accuracy…”
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    Hybrid prediction model for cold load in large public buildings based on mean residual feedback and improved SVR Autor Liu, Haiyan, Yu, Junqi, Dai, Junwei, Zhao, Anjun, Wang, Meng, Zhou, Meng

    ISSN: 0378-7788
    Vydavateľské údaje: Elsevier B.V 01.09.2023
    Vydané v Energy and buildings (01.09.2023)
    “…•TGRF is proposed for mean residual feedback to improve the model accuracy.•SSA is improved using three strategies to enhance the algorithm performance…”
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  14. 14

    Multi-Energy Load Prediction Method for Integrated Energy System Based on Fennec Fox Optimization Algorithm and Hybrid Kernel Extreme Learning Machine Autor Shen, Yang, Li, Deyi, Wang, Wenbo

    ISSN: 1099-4300, 1099-4300
    Vydavateľské údaje: Switzerland MDPI AG 17.08.2024
    Vydané v Entropy (Basel, Switzerland) (17.08.2024)
    “… the difficulty of forecasting. Therefore, this article puts forward a multi-energy load prediction approach of the IES, which combines the fennec fox optimization algorithm (FFA…”
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  15. 15

    Research on cooling load estimation through optimal hybrid models based on Naive Bayes Autor Xu, Ying

    ISSN: 1110-1903, 2536-9512
    Vydavateľské údaje: Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2024
    “… Traditional methods simplify real-world complexities, highlighting artificial intelligence’s role in precise cooling load forecasting for energy-efficient building management…”
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    Research on ultra-short-term load forecasting method of oil and gas field integrated energy system based on hybrid neural network Autor Zhang, Zhao, Dong, Dezhi, Lv, Lili, Peng, Liyuan, Li, Bing, Peng, Miao, Cheng, Tingting

    ISSN: 0948-7921, 1432-0487
    Vydavateľské údaje: Berlin/Heidelberg Springer Berlin Heidelberg 01.10.2025
    Vydané v Electrical engineering (01.10.2025)
    “…Aiming at the source-network-load coordination requirements of distributed new energy and cooling, heating and electricity loads in oil and gas fields, this paper proposes an ultra-short-term load…”
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    Forecasting heating and cooling loads of buildings: a comparative performance analysis Autor Roy, Sanjiban Sekhar, Samui, Pijush, Nagtode, Ishan, Jain, Hemant, Shivaramakrishnan, Vishal, Mohammadi-ivatloo, Behnam

    ISSN: 1868-5137, 1868-5145
    Vydavateľské údaje: Berlin/Heidelberg Springer Berlin Heidelberg 01.03.2020
    “…Heating load and cooling load forecasting are crucial for estimating energy consumption and improvement of energy performance during the design phase of buildings…”
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  18. 18

    Meta-learning strategy based on user preferences and a machine recommendation system for real-time cooling load and COP forecasting Autor Li, Wenqiang, Gong, Guangcai, Fan, Houhua, Peng, Pei, Chun, Liang

    ISSN: 0306-2619, 1872-9118
    Vydavateľské údaje: Elsevier Ltd 15.07.2020
    Vydané v Applied energy (15.07.2020)
    “… (subjective and objective) user preferences.•Multi-objective decision making algorithms (MODMA) are used in option optimization…”
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    Dynamic forecast of cooling load and energy saving potential based on Ensemble Kalman Filter for an institutional high-rise building with hybrid ventilation Autor Hou, Danlin, Lin, Cheng-Chun, Katal, Ali, Wang, Liangzhu (Leon)

    ISSN: 1996-3599, 1996-8744
    Vydavateľské údaje: Beijing Tsinghua University Press 01.12.2020
    Vydané v Building simulation (01.12.2020)
    “…Combining natural and mechanical ventilation, hybrid ventilation is an effective approach to reduce cooling energy consumption…”
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    Forecasting cooling load and water demand of a semi-closed greenhouse using a hybrid modelling approach Autor Mahmood, Farhat, Govindan, Rajesh, Yang, David, Bermak, Amine, Al-Ansari, Tareq

    ISSN: 0143-0750, 2162-8246
    Vydavateľské údaje: Taylor & Francis 31.12.2022
    “…Forecasting the greenhouse cooling and water demand is critical for improving the performance, reducing energy consumption, and operating costs throughout the year…”
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