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Power Plant Energy Prediction AI Challenge

The aim of this challenge is to design an AI model to predict hourly power plant energy output.

Difficulty

Practice
Challenge
Ends in 356 days
195 Participants
3,481 Views
Organized By Dockship

Welcome to Power Plant Energy Prediction AI Challenge!

The aim of this challenge is to predict the hourly energy output of a cyclic power plant based on given parameters. The dataset consists of 3 csv files:

  1. TRAIN.csv
  2. TEST.csv
  3. sample_submission.csv

TRAIN.csv consists of 5 attributes:

  • AT (Temperature)
  • V (Exhaust Vacuum)
  • AP (Ambient Pressure)
  • RH (Relative Humidity)
  • PE (Net Hourly Electrical Energy Output) (Target Column)

This data should be used to train the model, no additional data is allowed to be used for the training process.

TEST.csv consists of the testing data required for prediction and consists of 4 attributes:

  • AT
  • V
  • AP
  • RH

A "SampleSubmission".csv is also provided for ease of the participants. To know the exact submission format, please check out "Submission Guidelines".

The score is displayed in reverse order of Root Mean Square Error (RMSE). "TRAIN.csv" file contains the data required for training.

The output of the model should be "output.csv" containing the following columns in this exact order for predictions on TEST.csv:

  • Index (Row index of TEST.csv data)
  • Value (Output EP Value)

A "SampleSubmission.csv" is also given for reference which already contains the correct format required for submission.

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How to make a submission?

  1. Click on "My Submission"
  2. On the next page, click on "+ New Submission"
  3. Upload your CSV in the next page and click on "Submit for Review"


Please note:

  1. You must submit your CSV file by uploading the CSV in the "My Submissions" section of this challenge.
  2. Your submission will be auto graded and you will be able to see your results instantly.
  3. If there is any error in the submission, your final score will be marked as 0.

Judgement

  1. Root Mean Squared Error (RMSE) will be used for evaluation

Rules

  1. Candidate topping the challenge will be sent to the next round of interview, where they will be asked a proper expiation on the solution approach they took to solve the challenge.
  2. Submission must not include copyrighted code. If violation is found, submission will be rejected. Plagiarism is not encouraged.
  3. The submission should be in a proper format as described by "Submission Guidelines".
  4. Late submission will not be accepted beyond provided deadline (Indian Standard Time).


Reward

  1. Top three participants will get a place in Hall of Fame page.
How do I apply for this Challenge?
How do I download the dataset?
Can I make multiple submissions?
Where will the results be declared?
Can we apply as a team?
I've other queries, where can I get support?
Challenge Announced
15-Nov-2020, 5:50 am IST
18-Nov-2020, 12:00 pm IST
Challenge Started
Challenge Ends
18-Nov-2022, 6:00 pm IST