Prediction of Thalassemia Based on SAELM Hybrid Algorithm
| Autor: | Yaolian Song, Tuanbiao Zou, Wenlin Xu |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
0209 industrial biotechnology
Computer science Thalassemia 02 engineering and technology medicine.disease Hybrid algorithm Statistical classification 020901 industrial engineering & automation Simulated annealing 0202 electrical engineering electronic engineering information engineering medicine 020201 artificial intelligence & image processing Algorithm Global optimization Extreme learning machine |
| Zdroj: | 2019 3rd International Conference on Data Science and Business Analytics (ICDSBA). |
| DOI: | 10.1109/icdsba48748.2019.00054 |
| Popis: | Thalassemia is a serious hereditary disease, which cannot be cured. It’s valuable to study on thalassemia. The input weights and biases of Extreme Learning Machine (ELM) can be randomly initialized, which sometimes cannot get the better result. So a new algorithm named SAELM based on thalassemia is proposed by using the strong global optimization ability of Simulated Annealing (SA) algorithm, which can find the best weights and biases of ELM algorithm. Simulation results illustrated that the SAELM is better than ELM in the main evaluation indices, so SAELM algorithm can be used as a medical reference index in the screening of thalassemia. |
| Databáze: | OpenAIRE |
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