Classification of valence changes of trivalent rare earth ions in alkaline earth borates using artificial neural networks
✍ Scribed by Yu-Hua Qi; Lu Xu
- Publisher
- Elsevier Science
- Year
- 1999
- Tongue
- English
- Weight
- 74 KB
- Volume
- 45
- Category
- Article
- ISSN
- 0169-7439
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✦ Synopsis
3q
2q Ž . The investigations of classification on the valence changes from RE to RE RE ' Eu, Sm, Yb, Tm in host com-Ž . pounds of alkaline earth borate were performed using artificial neural networks ANNs . For comparison, the common methods of pattern recognition, such as SIMCA, KNN, Fisher discriminant analysis and stepwise discriminant analysis were adopted. A learning set consisting of 24 host compounds and a test set consisting of 12 host compounds were characterized by eight crystal structure parameters. These parameters were reduced from 8 to 4 by leaps and bounds algorithm. The recognition rates from 87.5 to 95.8% and prediction capabilities from 75.0 to 91.7% were obtained. The results provided by ANN method were better than that achieved by the other four methods.