The nature of statistical learning theory
The nature of statistical learning theory
Principle of information diffusion
Fuzzy Sets and Systems
Computers and Operations Research
Risk assessment for highway projects using jackknife technique
Expert Systems with Applications: An International Journal
A new approach to prediction of radiotherapy of bladder cancer cells in small dataset analysis
Expert Systems with Applications: An International Journal
Range estimation of construction costs using neural networks with bootstrap prediction intervals
Expert Systems with Applications: An International Journal
Journal of Intelligent Manufacturing
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - FUZZYSS'2011: 2nd International Fuzzy Systems Symposium
Hi-index | 12.06 |
If the production process, production equipment, or material changes, it becomes necessary to execute pilot runs before mass production in manufacturing systems. Using the limited data obtained from pilot runs to shorten the lead time to predict future production is this worthy of study. Although, artificial neural networks are widely utilized to extract management knowledge from acquired data, sufficient training data is the fundamental assumption. Unfortunately, this is often not achievable for pilot runs because there are few data obtained during trial stages and theoretically this means that the knowledge obtained is fragile. The purpose of this research is to utilize bootstrap to generate virtual samples to fill the information gaps of sparse data. The results of this research indicate that the prediction error rate can be significantly decreased by applying the proposed method to a very small data set.