Abstract:
:Baseball players swung very light and very heavy bats through our instrument and the speed of the bat was recorded. These data were used to make mathematical models for each person. Then these models were coupled with equations of physics for bat-ball collisions to compute the Ideal Bat Weight for each individual. However, these calculations required the use of a sophisticated instrument that is not conveniently available to most people. So, we tried to find items in our database that correlated with Ideal Bat Weight. However, because many cells in the database were empty, we could not use traditional statistical techniques or even neural networks. Therefore, three new methods were used to estimate the missing data: (i) a neural network was trained using subjects that had no empty cells, then that neural network was used to predict the missing data, (ii) the data patching facility of a commercial software package was used, and (iii) the empty cells were filled with random numbers. Then, using these fully populated databases, several simple models were derived for recommending bat weights.
journal_name
Ann Biomed Engjournal_title
Annals of biomedical engineeringauthors
Bahill AT,Freitas MMdoi
10.1007/BF02584443subject
Has Abstractpub_date
1995-07-01 00:00:00pages
436-44issue
4eissn
0090-6964issn
1573-9686journal_volume
23pub_type
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journal_title:Annals of biomedical engineering
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journal_title:Annals of biomedical engineering
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journal_title:Annals of biomedical engineering
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journal_title:Annals of biomedical engineering
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journal_title:Annals of biomedical engineering
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doi:10.1114/1.1349698
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journal_title:Annals of biomedical engineering
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