Model/Technique Registration (*=required):
Information about your group/project:
    Name(s) and e-mail (s) (please list primary contact first)*: Kangjin Lee (leekj87@gmail.com), Jongyeob Park (pjystar@gmail.com), Yong-Jae Moon (moonyj@khu.ac.kr)
    Associated Institution/Project name/Group name*: Kyung Hee University (KHU), Korea Astronomy and Space Science Institute (KASI), Korea Meteorological Administration (KMA)
    Website url(s): http://spaceweather.khu.ac.kr/products/flareforecast

Information about your method:
    Forecasting method name*: Automatic McIntosh-based Occurrence probability of Solar activity (AMOS)
    Shorthand unique identifier for your method (methodname_version, e.g. ASSA_1, ASAP_201201): AMOS_v1
    Short description*: This model provides daily occurrence probabilities of each C, M, and X-class flares for each NOAA active region and full disk using McIntosh sunspot group classes and its area change.
    References: Lee, K., Moon, Y.-J., Lee, J.-Y., Lee, K.-S., and Na, H., Solar Flare Occurrence Rate and Probability in Terms of the Sunspot Classification Supplemented with Sunspot Area and Its Changes, Sol. Phys., 281, 639, 2012.

Further Model Details:
    (1)* Please specify if the forecast is human generated, human generated but model-based, model-based, or other. 
Model-based

    (2)* Does your flare prediction method forecast “M1.0-9.9” or “M and above”? Would it be difficult for you to adapt your method from one to another? Which forecast binning method do you prefer?
M and above

    (3)* How do you specify active regions in your model? Do you relate their location to other schemes such as NOAA or Catania? If so, what is your criterea to relate them?
This model considers the solar region summary (SRS) data from the NOAA SWPC.

    (4)* Uncertainties given as an upper and lower bound is an optional field. Does your model provide uncertainties for the forecasted probability? 
If yes, what percentiles do you use to determine your upper and lower bound? If you are using the XML format, multiple percentiles of the probability density distribution can be specified.
Uncertainties are not given in this model.

    (5)* For each forecast, what prediction window(s) does your method use? E.g. Does your method predict for the next 24 hours, 48, and 72 hours or the next 24 hours, 24-48 hours, 48-72 hours? (This information is useful for displaying only comparable methods together).
Next 24 hours.

    (6)* For how many degrees from disk center is your full disk forecast valid for? E.g. 60 degrees; or 90 degrees (valid for entire disk).
Entire disk.

    (7)* Calibration levels are optional fields. Do you have calibration for the probabilities from your model? E.g. is a 40% forecast a “high” probability for your method? 
If yes, please provide the probability ranges for what is considered a “low”, “medium”, or “high” level. This can be provided in a separate file, or as part of the main template, labeled “X_Level”, “M_Level”, and “C_Level” fields which can take the values 1, 2, or 3. These levels represent probability calibration for a model for each flare class. With 1 meaning “low” probability, 2 is “medium” probability, and 3 is “high” probability.
None.