Dataset Ⅰ:To obtain the prices of parts from the manufacturing characteristics and other manufacturing processes, feature quantity expression is innovatively applied. By identifying manufacturing features and calculating the feature quantities, the feature quantities are described in the form of assignments as data. To obtain the prices of parts intelligently, the most widely used and mature deep-learning method is adopted to realize the accurate quotation of parts.

Dataset Files

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[1] Fangwei Ning, "Mechanical Parts data cost data and shape cluster ", IEEE Dataport, 2019. [Online]. Available: http://dx.doi.org/10.21227/1tq7-y065. Accessed: Feb. 07, 2025.
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doi = {10.21227/1tq7-y065},
url = {http://dx.doi.org/10.21227/1tq7-y065},
author = {Fangwei Ning },
publisher = {IEEE Dataport},
title = {Mechanical Parts data cost data and shape cluster },
year = {2019} }
TY - DATA
T1 - Mechanical Parts data cost data and shape cluster
AU - Fangwei Ning
PY - 2019
PB - IEEE Dataport
UR - 10.21227/1tq7-y065
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Fangwei Ning. (2019). Mechanical Parts data cost data and shape cluster . IEEE Dataport. http://dx.doi.org/10.21227/1tq7-y065
Fangwei Ning, 2019. Mechanical Parts data cost data and shape cluster . Available at: http://dx.doi.org/10.21227/1tq7-y065.
Fangwei Ning. (2019). "Mechanical Parts data cost data and shape cluster ." Web.
1. Fangwei Ning. Mechanical Parts data cost data and shape cluster [Internet]. IEEE Dataport; 2019. Available from : http://dx.doi.org/10.21227/1tq7-y065
Fangwei Ning. "Mechanical Parts data cost data and shape cluster ." doi: 10.21227/1tq7-y065