You cannot sign up to Kaggle from multiple accounts and therefore you cannot submit from multiple accounts.
\r\n\r\n Privately sharing code or data outside of teams is not permitted.\r\n It's okay to share code if made available to all participants on the forums.\r\n
\r\nKaggle and the competition host have the right to publicly disseminate any entries or models.
\r\n\r\n Winning solutions need to be made available under\r\n a popular OSI-approved license\r\n in order to be eligible for recognition and prize money.\r\n
\r\n\r\n Prizes will be awarded after the winners have posted their solutions to the competition forum.\r\n Winners must post or link to their solutions within seven (7) days of being notified of their winning status.\r\n
\r\n\r\n Team mergers are allowed and can be performed by the team leader. In order to merge, the combined team must have a total submission count less than or equal to the maximum allowed as of the merge date. The maximum allowed is the number of submissions per day multiplied by the number of days the competition has been running.
\r\n
There is no maximum team size.
\r\nYou may submit a maximum of 2 entries per day.
\r\nYou may select up to 1 final submissions for judging.
\r\nStart Date: 9/6/2012 1:24 AM UTC
\r\nMerger Deadline: None
\r\nEntry Deadline: None
\r\nEnd Date: 10/31/2012 12:00 AM UTC
\r\n\t\r\nParticipants should submit their algorithms, models, complete code and a detailed report via email to the General Chair of GEFCom2012\r\n(Dr. Tao Hong, hongtao01@gmail.com) by 11/1/2012.
\r\nSelected entries will be invited to the IEEE PES General Meeting 2013 in Vancouver, Canada to present their methodologies and results. The final winners will be determined by the GEFCom Award Committee after the presentations based on forecasting accuracy,\r\n clarity of documentation, rigors of the approach, interpretability of the models and practicality to the industry.
\r\nModels should be generated using software that is free and open source or is in the following list of exceptions: MATLAB, SAS, MS Excel. The participants who are using other software packages should send a free evaluation copy of the software to GEFCom Award\r\n Committee to reproduce and evaluate the proposed models.
", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "data-description", "content": ""train.csv" contains the training data:
\r\n- the first column ("date") is a timestamp giving date and time of the hourly wind power measurements in following columns. For instance "2009070812" is for the 8th of July 2009 at 12:00;
\r\n- the following 7 columns ("wp1" to "wp7") gather the normalized wind power measurements for the 7 wind farms. They are normalized so as to take values between 0 and 1 in order for the wind farms not to be recognizable.
\r\nIn parallel, files with explanatory variables (wind forecasts) are also provided for those who may want to use them. For example, the file "windforecasts_wf1" contains the wind forecasts for the wind farm 1. In these files:
\r\n- the first column ("date") is a timestamp giving date and time at which the forecasts are issued. For instance "2009070812" is for the 8th of July 2009 at 12:00;
\r\n- the second column ("hors") is for the lead time of the forecast. For instance if "date" = 2009070812 and "hors" = 1, the forecast is for the 8th of July 2009 at 13:00
\r\n- the following 4 columns ("u", "v", "ws" and "wd") are the forecasts themselves, the first two being the zonal and meridional wind components, while the following two are corresponding wind speed and direction.
\r\nFinally, the file "benchmark.csv" provide example forecast results from the persistence forecast method ("what you see is what you get"). This file also gives a template for submission of results that should be strictly followed.
\r\nPlease notice that the first column of "benchmark.csv" is called "id" and contains unique identifier for each row. The other 8 columns are the same as "train.csv".\r\nWhen submitting the results, please make sure that your file includes totally 9 columns in the same format as "benchmark.csv".
", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "Description", "content": "This is the Wind Forecasting track of Global Energy Forecasting Competition 2012 (GEFCom2012).This competition will bring together state-of-the-art techniques for energy forecasting, serve as the bridge to connect academic\r\n research and industry practice, promote analytics in power engineering education, and prepare the industry to overcome forecasting challenges in the smart grid world.
\r\nThe total prize pool for the wind forecasting track is \r\n$7,500. GEFCom is not a paper contest. Instead, this is a competition that requires participants to develop models and submit forecasts based on a given data set. Accuracy of the forecasts will be one of the evaluation criteria. In addition to accuracy,\r\n the participants are also required to submit a report describing the methodology, findings and models. Selected entries will be invited to IEEE PES General Meeting 2013 in Vancouver, Canada to present their methodologies and results. The team that finishes\r\n at the top of the leaderboard will win a cash prize. However overall winners of the competition will be determined by the GEFCom Award Committee after the presentations based on forecasting accuracy, clarity of documentation, rigors of the approach, interpretability\r\n of the models and practicality to the industry. A few winning entries will be invited to submit the report in scientific paper format to prestigious scholarly journals, such as International Journal of Forecasting and IEEE Transactions on Smart Grid.
\r\nThe topic for the wind forecasting track is focused on mimicking the operation 48-hour ahead prediction of hourly power generation at 7 wind farms, based on historical measurements and additional wind forecast information (48-hour ahead predictions of wind\r\n speed and direction at the sites). The data is available for period ranging from the 1st hour of 2009/7/1 to the 12th hour of 2012/6/28.
\r\nThe period between 2009/7/1 and 2010/12/31 is a model identification and training period, while the remainder of the dataset, that is, from 2011/1/1 to 2012/6/28, is there for the evaluation. The training period is there to be used for designing and estimating\r\n models permiting to predicting wind power generation at lead times from 1 to 48 hours ahead, based on past power observations and/or available meteorological wind forecasts for that period. Over the evaluation part, it is aimed at mimicking real operational\r\n conditions. For that, a number of 48-hour periods with missing power observations where defined. All these power observations are to be predicted. These periods are defined as following. The first period with missing observations is that from 2011/1/1 at 01:00\r\n until 2011/1/3 at 00:00. The second period with missing observations is that from 2011/1/4 at 13:00 until 2011/1/6 at 12:00. Note that to be consistent, only the meteorological forecasts for that period that would actually be available in practice are given.\r\n These two periods then repeats every 7 days until the end of the dataset. Inbetween periods with missing data, power observations are available for updating the models.
\r\n", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "Prizes", "content": "
The competition is financially sponsored by IEEE Power & Energy Society. Prizes will be awarded according to the Leaderboard and an Award Committee.
\r\nLeaderboard Prize for First Place: $500
\r\nAward Committee of the GEFCom2012 Prizes:
\r\nThe forecasting accuracy will be evaluated with a Root Mean Square Error (RMSE) criterion. The RMSE is calculated as the square root of the average of square forecast errors. All forecasts will be equally weighted in the score calculation.
", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false } ] }