Name
Title | ||
|---|---|---|
Predicting high-tech equipment fabrication cost with a novel evolutionary SVM inference model |
Abstract | ||
|---|---|---|
Accurately predicting fabricating cost in a timely manner can enhance corporate competitiveness. This study employs the Evolutionary Support Vector Machine Inference Model (ESIM) to predict the cost of manufacturing thin-film transistor liquid-crystal display (TFT-LCD) equipment. The ESIM is a hybrid model integrating a support vector machine (SVM) with a fast messy genetic algorithm (fmGA). The SVM concerns primarily with learning and curve fitting, while the fmGA is focuses on optimization of minimal errors. Recently completed equipment development projects are utilized to assess prediction performance. The ESIM is developed to achieve the fittest C and @c parameters with minimized prediction error when used for cost estimate during conceptual stages. This study describes an actionable knowledge-discovery process using real-world data for high-tech equipment manufacturing industries. Analytical results demonstrate that the ESIM can predict the costs of manufacturing TFT-LCD fabrication equipment with sufficient accuracy. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1016/j.eswa.2011.01.060 | Expert Syst. Appl. |
Keywords | Field | DocType |
svm concern,high-tech equipment manufacturing industry,manufacturing,tft-lcd fabrication equipment,analytical result,prediction performance,tft-lcd,prediction error,support vector machine,high-tech equipment,novel evolutionary svm inference,fabricating cost,evolutionary support,fast messy genetic algorithm,cost estimate,cost estimation,equipment development project,hybrid artificial intelligence,high-tech equipment fabrication cost,manufacturing industry,liquid crystal display,thin film transistor,genetic algorithm,curve fitting,artificial intelligent | Mean squared prediction error,Manufacturing,Curve fitting,Computer science,Inference,Support vector machine,Cost estimate,High tech,Artificial intelligence,Genetic algorithm,Machine learning | Journal |
Volume | Issue | ISSN |
38 | 7 | Expert Systems With Applications |
Citations | PageRank | References |
4 | 0.40 | 20 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jui-Sheng Chou | 1 | 149 | 17.95 |
| Min-Yuan Cheng | 2 | 174 | 19.84 |
| Yu-Wei Wu | 3 | 43 | 5.89 |
| Yian Tai | 4 | 4 | 0.40 |