Electronic Forecasting of Women's Jumping Events using Neural Networks

• Main Authors: Fares Ahmed, Aida Muhammad, Hala Fathi
• Format: Article
• Language: Arabic
• Published: Mosul University 2013-03-01
• Series: Al-Rafidain Journal of Computer Sciences and Mathematics
• Subjects: forecasting; neural network; expert system; jumping competitions
• Online Access: https://csmj.mosuljournals.com/article_163461_68f11396261239e5d8589ede8398ce96.pdf

The aim of this research is to use neural network in future forecasting field to show the of jumping competitions in international Olympics for (2016-2024). Expert system named (AAA) is designed by using neural network in  future forecasting field for period chain of data from 1984 to 2012,which represents 8 years period.  The data represent the first three winners in running competition for (100 m., 200 m., 400 m., 100 m. Hurdles, 400 m. Hurdles, 4×100 Relay, 4×400 Relay), The prepared programs for this research has been done C++.  Then it forecast three future levels represented in (2016, 2020, 2024),where the Olympic Cycle take place each 4 years. Throughout the results it found that forecasting values are the best by using neural networks then other traditional methods used before. This  paper is depended  on the results of athletes who take Olympic medals in women jumping events (long, triple, high and pole-vault) in 8  Olympic cycles, since Tokyo cycle (1984) till the last Olympic cycle in (2012) . The cycle on (1984) was used as the  beginning of  study as it considered as the first Olympic cycle.