An optimum drill bit selection technique using artificial neural networks and genetic algorithms to increase the rate of penetration
Drill bit is the most essential tool in drilling and drill bit selection plays a significant role in drilling process planning. This paper discusses bit selection by employing a method of combining Artificial Neural Network (ANN) and the computation of Genetic Algorithm (GA). In this method, offset...
| Main Authors: | Momeni, M., Hosseini, S.J., Ridha, S., Laruccia, M.B., Liu, X. |
|---|---|
| Format: | Article |
| Institution: | Universiti Teknologi Petronas |
| Record Id / ISBN-0: | utp-eprints.21803 / |
| Published: |
Taylor's University
2018
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| Online Access: |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85041802992&partnerID=40&md5=433c9205b717f02473875d0f19d8d7cf http://eprints.utp.edu.my/21803/ |
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