{
  "id": 113080,
  "title": "🔌TOP 2019 PUBLISHED ARTICLES🔌 ON ENERGY CONSUMTION PREDICTION",
  "url": "/competitions/ashrae-energy-prediction/discussion/113080",
  "author_name": "",
  "post_date": "2019-10-16T21:28:17.313182100Z",
  "votes": 22,
  "comment_count": 11,
  "views": 0,
  "content": "<p><strong>This is a competitive list and you’ll find the experience and techniques shared by the Data Science leaders useful.</strong></p>\n\n<p><img src=\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1673888%2F2844f3c055e62c7473fd5a89655b15a3%2Fapp.png?generation=1571260123897866&amp;alt=media\" alt=\"\">\n1. <a href=\"https://www.sciencedirect.com/science/article/abs/pii/S0306261919304878\">Vector field-based support vector regression for building energy consumption prediction</a></p>\n\n<p><img src=\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1673888%2F9b5ddff9716f8aff242c56b26ee5dd6e%2Fapp1.jpg?generation=1571260276953613&amp;alt=media\" alt=\"\">\n2. <a href=\"https://www.sciencedirect.com/science/article/pii/S0378778818322965\">Data driven parallel prediction of building energy consumption using generative adversarial nets</a></p>\n\n<p><img src=\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1673888%2F1575801b3c9ad687973623ff6484f90d%2Fapp2.png?generation=1571260408091203&amp;alt=media\" alt=\"\">\n3. <a href=\"https://link.springer.com/chapter/10.1007/978-3-030-15035-8_111\">Prediction of Building Energy Consumption Using Enhance Convolutional Neural Network</a></p>\n\n<p><img src=\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1673888%2F4351ce6a32d51a37b3421aa973c3f5ac%2Fapp3.png?generation=1571260523577046&amp;alt=media\" alt=\"\">\n4. <a href=\"https://journals.sagepub.com/doi/abs/10.1177/0144598718822400\">Accuracy analyses and model comparison of machine learning adopted in building energy consumption prediction</a></p>\n\n<p><img src=\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1673888%2F1981681b062860c3e78a59f0f8e390d7%2Fapp4.png?generation=1571260746367441&amp;alt=media\" alt=\"\">\n6. <a href=\"https://www.mdpi.com/1996-1073/12/10/1934\">A Comparative Study of Time Series Forecasting Methods for Short Term Electric Energy Consumption Prediction in Smart Buildings</a></p>\n\n<ol>\n<li><p><a href=\"https://www.mdpi.com/1996-1073/12/4/739\">Electric energy consumption prediction by deep learning with state explainable autoencoder</a></p></li>\n<li><p><a href=\"https://eprints.qut.edu.au/128957/\">Energy consumption prediction using machine learning: A review</a></p></li>\n<li><p><a href=\"https://www.mdpi.com/2227-7080/7/2/30/htm\">A Framework for Prediction of Household Energy Consumption Using Feed Forward Back Propagation Neural Network</a></p></li>\n</ol>\n\n<p><img src=\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1673888%2Fdfbbfc0b95164d2bbcf2c8afe54b269b%2Fapp5.jpg?generation=1571261068930885&amp;alt=media\" alt=\"\">\n10. <a href=\"https://link.springer.com/chapter/10.1007/978-3-030-00220-6_83\">Predicting energy consumption of office buildings: a hybrid machine learning-based approach</a></p>",
  "messages": [
    {
      "id": "650939",
      "postDate": "10/16/2019 21:28:17",
      "content": "<p><strong>This is a competitive list and you’ll find the experience and techniques shared by the Data Science leaders useful.</strong></p>\n\n<p><img src=\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1673888%2F2844f3c055e62c7473fd5a89655b15a3%2Fapp.png?generation=1571260123897866&amp;alt=media\" alt=\"\">\n1. <a href=\"https://www.sciencedirect.com/science/article/abs/pii/S0306261919304878\">Vector field-based support vector regression for building energy consumption prediction</a></p>\n\n<p><img src=\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1673888%2F9b5ddff9716f8aff242c56b26ee5dd6e%2Fapp1.jpg?generation=1571260276953613&amp;alt=media\" alt=\"\">\n2. <a href=\"https://www.sciencedirect.com/science/article/pii/S0378778818322965\">Data driven parallel prediction of building energy consumption using generative adversarial nets</a></p>\n\n<p><img src=\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1673888%2F1575801b3c9ad687973623ff6484f90d%2Fapp2.png?generation=1571260408091203&amp;alt=media\" alt=\"\">\n3. <a href=\"https://link.springer.com/chapter/10.1007/978-3-030-15035-8_111\">Prediction of Building Energy Consumption Using Enhance Convolutional Neural Network</a></p>\n\n<p><img src=\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1673888%2F4351ce6a32d51a37b3421aa973c3f5ac%2Fapp3.png?generation=1571260523577046&amp;alt=media\" alt=\"\">\n4. <a href=\"https://journals.sagepub.com/doi/abs/10.1177/0144598718822400\">Accuracy analyses and model comparison of machine learning adopted in building energy consumption prediction</a></p>\n\n<p><img src=\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1673888%2F1981681b062860c3e78a59f0f8e390d7%2Fapp4.png?generation=1571260746367441&amp;alt=media\" alt=\"\">\n6. <a href=\"https://www.mdpi.com/1996-1073/12/10/1934\">A Comparative Study of Time Series Forecasting Methods for Short Term Electric Energy Consumption Prediction in Smart Buildings</a></p>\n\n<ol>\n<li><p><a href=\"https://www.mdpi.com/1996-1073/12/4/739\">Electric energy consumption prediction by deep learning with state explainable autoencoder</a></p></li>\n<li><p><a href=\"https://eprints.qut.edu.au/128957/\">Energy consumption prediction using machine learning: A review</a></p></li>\n<li><p><a href=\"https://www.mdpi.com/2227-7080/7/2/30/htm\">A Framework for Prediction of Household Energy Consumption Using Feed Forward Back Propagation Neural Network</a></p></li>\n</ol>\n\n<p><img src=\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1673888%2Fdfbbfc0b95164d2bbcf2c8afe54b269b%2Fapp5.jpg?generation=1571261068930885&amp;alt=media\" alt=\"\">\n10. <a href=\"https://link.springer.com/chapter/10.1007/978-3-030-00220-6_83\">Predicting energy consumption of office buildings: a hybrid machine learning-based approach</a></p>",
      "rawMarkdown": "**This is a competitive list and you’ll find the experience and techniques shared by the Data Science leaders useful.**\n\n![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1673888%2F2844f3c055e62c7473fd5a89655b15a3%2Fapp.png?generation=1571260123897866&amp;alt=media)\n1. [Vector field-based support vector regression for building energy consumption prediction](https://www.sciencedirect.com/science/article/abs/pii/S0306261919304878)\n\n![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1673888%2F9b5ddff9716f8aff242c56b26ee5dd6e%2Fapp1.jpg?generation=1571260276953613&amp;alt=media)\n2. [Data driven parallel prediction of building energy consumption using generative adversarial nets](https://www.sciencedirect.com/science/article/pii/S0378778818322965)\n\n![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1673888%2F1575801b3c9ad687973623ff6484f90d%2Fapp2.png?generation=1571260408091203&amp;alt=media)\n3. [Prediction of Building Energy Consumption Using Enhance Convolutional Neural Network](https://link.springer.com/chapter/10.1007/978-3-030-15035-8_111)\n\n![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1673888%2F4351ce6a32d51a37b3421aa973c3f5ac%2Fapp3.png?generation=1571260523577046&amp;alt=media)\n4. [Accuracy analyses and model comparison of machine learning adopted in building energy consumption prediction](https://journals.sagepub.com/doi/abs/10.1177/0144598718822400)\n\n\n![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1673888%2F1981681b062860c3e78a59f0f8e390d7%2Fapp4.png?generation=1571260746367441&amp;alt=media)\n6. [A Comparative Study of Time Series Forecasting Methods for Short Term Electric Energy Consumption Prediction in Smart Buildings](https://www.mdpi.com/1996-1073/12/10/1934)\n\n7. [Electric energy consumption prediction by deep learning with state explainable autoencoder](https://www.mdpi.com/1996-1073/12/4/739)\n\n8. [Energy consumption prediction using machine learning: A review](https://eprints.qut.edu.au/128957/)\n\n\n9. [A Framework for Prediction of Household Energy Consumption Using Feed Forward Back Propagation Neural Network](https://www.mdpi.com/2227-7080/7/2/30/htm)\n\n![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1673888%2Fdfbbfc0b95164d2bbcf2c8afe54b269b%2Fapp5.jpg?generation=1571261068930885&amp;alt=media)\n10. [Predicting energy consumption of office buildings: a hybrid machine learning-based approach](https://link.springer.com/chapter/10.1007/978-3-030-00220-6_83)",
      "votes": null
    },
    {
      "id": "651033",
      "postDate": "10/17/2019 01:20:13",
      "content": "<p>Great ! thanks for sharing  <a href=\"/hamditarek\">@hamditarek</a>  ! </p>",
      "rawMarkdown": "Great ! thanks for sharing  @hamditarek  !",
      "votes": null
    },
    {
      "id": "651037",
      "postDate": "10/17/2019 01:27:27",
      "content": "<p>You are welcome <a href=\"/caesarlupum\">@caesarlupum</a> and good luck</p>",
      "rawMarkdown": "You are welcome @caesarlupum and good luck",
      "votes": null
    },
    {
      "id": "651137",
      "postDate": "10/17/2019 04:54:09",
      "content": "<p>Very Informative &amp; Helpful\nThanks <a href=\"/hamditarek\">@hamditarek</a> </p>",
      "rawMarkdown": "Very Informative &amp; Helpful\nThanks @hamditarek",
      "votes": null
    },
    {
      "id": "651248",
      "postDate": "10/17/2019 08:20:51",
      "content": "<p>You are welcome <a href=\"/veeralakrishna\">@veeralakrishna</a> </p>",
      "rawMarkdown": "You are welcome @veeralakrishna",
      "votes": null
    },
    {
      "id": "651524",
      "postDate": "10/17/2019 14:56:21",
      "content": "<p>Very informative. Thanks for sharing buddy!</p>",
      "rawMarkdown": "Very informative. Thanks for sharing buddy!",
      "votes": null
    },
    {
      "id": "651542",
      "postDate": "10/17/2019 15:28:56",
      "content": "<p>You are welcome <a href=\"/themonologue\">@themonologue</a>  and good luck</p>",
      "rawMarkdown": "You are welcome @themonologue  and good luck",
      "votes": null
    },
    {
      "id": "652432",
      "postDate": "10/18/2019 20:53:31",
      "content": "<p>Oh wow – good catch! Very much appreciated! 👍 </p>",
      "rawMarkdown": "Oh wow – good catch! Very much appreciated! 👍",
      "votes": null
    },
    {
      "id": "652442",
      "postDate": "10/18/2019 21:08:29",
      "content": "<p>You are welcome <a href=\"/chmaxx\">@chmaxx</a> and good luck</p>",
      "rawMarkdown": "You are welcome @chmaxx and good luck",
      "votes": null
    },
    {
      "id": "661851",
      "postDate": "10/30/2019 19:12:12",
      "content": "<p>Great collection. Thank you for sharing!👌 </p>",
      "rawMarkdown": "Great collection. Thank you for sharing!👌",
      "votes": null
    },
    {
      "id": "661858",
      "postDate": "10/30/2019 19:31:54",
      "content": "<p>Thanks <a href=\"/hamditarek\">@hamditarek</a> ! Good luck ! </p>",
      "rawMarkdown": "Thanks @hamditarek ! Good luck !",
      "votes": null
    },
    {
      "id": "665324",
      "postDate": "11/04/2019 21:55:58",
      "content": "<p>you are welcome</p>",
      "rawMarkdown": "you are welcome",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 651033,
      "author_name": "caesarlupum",
      "author_url": "",
      "post_date": "10/17/2019 01:20:13",
      "content": "<p>Great ! thanks for sharing  <a href=\"/hamditarek\">@hamditarek</a>  ! </p>",
      "votes": null,
      "replies": [
        {
          "id": 651037,
          "author_name": "hamditarek",
          "author_url": "",
          "post_date": "10/17/2019 01:27:27",
          "content": "<p>You are welcome <a href=\"/caesarlupum\">@caesarlupum</a> and good luck</p>",
          "votes": null,
          "replies": []
        },
        {
          "id": 661858,
          "author_name": "caesarlupum",
          "author_url": "",
          "post_date": "10/30/2019 19:31:54",
          "content": "<p>Thanks <a href=\"/hamditarek\">@hamditarek</a> ! Good luck ! </p>",
          "votes": null,
          "replies": []
        }
      ]
    },
    {
      "id": 651137,
      "author_name": "veeralakrishna",
      "author_url": "",
      "post_date": "10/17/2019 04:54:09",
      "content": "<p>Very Informative &amp; Helpful\nThanks <a href=\"/hamditarek\">@hamditarek</a> </p>",
      "votes": null,
      "replies": [
        {
          "id": 651248,
          "author_name": "hamditarek",
          "author_url": "",
          "post_date": "10/17/2019 08:20:51",
          "content": "<p>You are welcome <a href=\"/veeralakrishna\">@veeralakrishna</a> </p>",
          "votes": null,
          "replies": []
        }
      ]
    },
    {
      "id": 651524,
      "author_name": "themonologue",
      "author_url": "",
      "post_date": "10/17/2019 14:56:21",
      "content": "<p>Very informative. Thanks for sharing buddy!</p>",
      "votes": null,
      "replies": [
        {
          "id": 651542,
          "author_name": "hamditarek",
          "author_url": "",
          "post_date": "10/17/2019 15:28:56",
          "content": "<p>You are welcome <a href=\"/themonologue\">@themonologue</a>  and good luck</p>",
          "votes": null,
          "replies": []
        }
      ]
    },
    {
      "id": 652432,
      "author_name": "chmaxx",
      "author_url": "",
      "post_date": "10/18/2019 20:53:31",
      "content": "<p>Oh wow – good catch! Very much appreciated! 👍 </p>",
      "votes": null,
      "replies": [
        {
          "id": 652442,
          "author_name": "hamditarek",
          "author_url": "",
          "post_date": "10/18/2019 21:08:29",
          "content": "<p>You are welcome <a href=\"/chmaxx\">@chmaxx</a> and good luck</p>",
          "votes": null,
          "replies": []
        }
      ]
    },
    {
      "id": 661851,
      "author_name": "zinovadr",
      "author_url": "",
      "post_date": "10/30/2019 19:12:12",
      "content": "<p>Great collection. Thank you for sharing!👌 </p>",
      "votes": null,
      "replies": [
        {
          "id": 665324,
          "author_name": "hamditarek",
          "author_url": "",
          "post_date": "11/04/2019 21:55:58",
          "content": "<p>you are welcome</p>",
          "votes": null,
          "replies": []
        }
      ]
    }
  ],
  "raw_markdown_by_id": {
    "650939": "**This is a competitive list and you’ll find the experience and techniques shared by the Data Science leaders useful.**\n\n![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1673888%2F2844f3c055e62c7473fd5a89655b15a3%2Fapp.png?generation=1571260123897866&amp;alt=media)\n1. [Vector field-based support vector regression for building energy consumption prediction](https://www.sciencedirect.com/science/article/abs/pii/S0306261919304878)\n\n![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1673888%2F9b5ddff9716f8aff242c56b26ee5dd6e%2Fapp1.jpg?generation=1571260276953613&amp;alt=media)\n2. [Data driven parallel prediction of building energy consumption using generative adversarial nets](https://www.sciencedirect.com/science/article/pii/S0378778818322965)\n\n![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1673888%2F1575801b3c9ad687973623ff6484f90d%2Fapp2.png?generation=1571260408091203&amp;alt=media)\n3. [Prediction of Building Energy Consumption Using Enhance Convolutional Neural Network](https://link.springer.com/chapter/10.1007/978-3-030-15035-8_111)\n\n![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1673888%2F4351ce6a32d51a37b3421aa973c3f5ac%2Fapp3.png?generation=1571260523577046&amp;alt=media)\n4. [Accuracy analyses and model comparison of machine learning adopted in building energy consumption prediction](https://journals.sagepub.com/doi/abs/10.1177/0144598718822400)\n\n\n![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1673888%2F1981681b062860c3e78a59f0f8e390d7%2Fapp4.png?generation=1571260746367441&amp;alt=media)\n6. [A Comparative Study of Time Series Forecasting Methods for Short Term Electric Energy Consumption Prediction in Smart Buildings](https://www.mdpi.com/1996-1073/12/10/1934)\n\n7. [Electric energy consumption prediction by deep learning with state explainable autoencoder](https://www.mdpi.com/1996-1073/12/4/739)\n\n8. [Energy consumption prediction using machine learning: A review](https://eprints.qut.edu.au/128957/)\n\n\n9. [A Framework for Prediction of Household Energy Consumption Using Feed Forward Back Propagation Neural Network](https://www.mdpi.com/2227-7080/7/2/30/htm)\n\n![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1673888%2Fdfbbfc0b95164d2bbcf2c8afe54b269b%2Fapp5.jpg?generation=1571261068930885&amp;alt=media)\n10. [Predicting energy consumption of office buildings: a hybrid machine learning-based approach](https://link.springer.com/chapter/10.1007/978-3-030-00220-6_83)",
    "651033": "Great ! thanks for sharing  @hamditarek  !",
    "651037": "You are welcome @caesarlupum and good luck",
    "651137": "Very Informative &amp; Helpful\nThanks @hamditarek",
    "651248": "You are welcome @veeralakrishna",
    "651524": "Very informative. Thanks for sharing buddy!",
    "651542": "You are welcome @themonologue  and good luck",
    "652432": "Oh wow – good catch! Very much appreciated! 👍",
    "652442": "You are welcome @chmaxx and good luck",
    "661851": "Great collection. Thank you for sharing!👌",
    "661858": "Thanks @hamditarek ! Good luck !",
    "665324": "you are welcome"
  },
  "source": "meta"
}