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32 ta ish

Ish: A Systematic Review of Comparative Analysis of Machine Learning Models for Predicting Heating Demand and Electricity Usage with Weather Data in Buildings: Two Case Studies in Norway

  1. Artificial neural networks in supply chain management, a review

    Mohsen Soori, Behrooz Arezoo, Roza Dastres

    Sharh maqola20233 iqtibos
    ABI

  2. Building energy consumption prediction for residential buildings using deep learning and other machine learning techniques

    Razak Olu-Ajayi, Hafiz Alaka, Ismail Sulaimon +2

    Maqola20213 iqtibos
    ABI

  3. Machine learning approaches for estimating commercial building energy consumption

    Caleb Robinson, Bistra Dilkina, Jeffrey Hubbs +4

    Maqola20172 iqtibos
    ABI

  4. Impact of occupancy rates on the building electricity consumption in commercial buildings

    Yang‐Seon Kim, Jelena Srebric

    Maqola20162 iqtibos
    ABI

  5. Predicting electricity consumption in a building using an optimized back-propagation and Levenberg–Marquardt back-propagation neural network: Case study of a shopping mall in China

    Zhaoyang Ye, Moon Keun Kim

    Maqola20182 iqtibos
    ABI

  6. On hyperparameter optimization of machine learning algorithms: Theory and practice

    Li Yang, Abdallah Shami

    Maqola20202 iqtibos
    ABI

  7. Investigating the Impact of Min-Max Data Normalization on the Regression Performance of K-Nearest Neighbor with Different Similarity Measurements

    Peshawa Jamal Muhammad Ali

    Maqola20222 iqtibos
    ABI

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