participants
ITRI established the first big data R&D center, the Computational Intelligence Technology Center (CITC) in 2013, to bridge the big data technology across industries in Taiwan.By developing the intelligent analytics technologies, it can boost Artificial Intelligence and big data core capabilities for local IT software companies.Besides, CITC also applies intelligent analytics to help the related industries to enhance their productivity and create new business opportunities. The cross-disciplinary approach enables CITC’s core technology capabilities to provide intelligent analytics and machine learning algorithms that industries need. CITC develops an open source Artificial Intelligence and big data platform to create solutions that facilitate the innovative application for service design and business model for industries.
This is a topic from the “Taiwan COVID-19 confirmed cases forecast” project which will last for a week. The target is to give a prediction of the newly confirmed COVID-19 cases of each day during 13/05/20 to 19/05/20 (DD/MM/YY). During the competition, the historical data from 22/04/20 to 28/04/20 will be adopted for verifying and score calculating. This score is only for competitor’s reference, the final score will be based on the Private Leaderboard.
For more information, please refer to the website: https://aidea-web.tw/covid-19
Awards were provided by Chunghwa Telecom
Note:
1.Hicloud points can redeem service charge. After the discount, the price will be charged at 30% off based on the list price automatically.
2.Chunghwa Telecom deserves the right to make changes to the terms and conditions herein.
The example of calculating points can be referred to https://aidea-web.tw/computing
The activity period would be mainly based on Taiwan Standard Time (UTC+8), and the schedule is as follows,
| Time(DD/MM/YY) | Events |
|---|---|
| 29/04/20 | Registration begins |
| 12/05/20 | Upload deadline |
| 20/05/20 | Winners announcement |
Evaluations are conducted by calculating the Weighted Root Mean Squared Error (Weighted RMSE）. The formula is as follows: $$Weighted \; RMSE = \sqrt{\sum_{i=1}^{n} w_i(y_i - \hat{y}_i) ^ 2}$$
$$w_i \;(weight): the \; values \; are between \; 0-1, and \; the \; sum \; is \; 1$$
$$w_1 \;is \; the \; weight \; of \; day \; one,\; w_2 \; is \; the \; weight \;of \; day \;two,...and \; so \; on. \;w_1: 0.11，w_2: 0.11，w_3: 0.14，w_4: 0.14，w_5: 0.16，w_6: 0.16，w_7: 0.18$$
