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Artificial Neural Network Training using Fireworks Algorithm in Medical Data Mining
| Content Provider | Semantic Scholar |
|---|---|
| Author | Dutta, Ram Kinkar Karmakar, Nabin Kanti Si, Tapas Zhu, Yingchen |
| Copyright Year | 2016 |
| Abstract | This paper proposes a novel application of Fireworks Algorithm in Artificial Neural Network training. Fireworks Algorithm is a recently developed Swarm Intelligence algorithm for function optimization. Fireworks Algorithm mimics the explosion process of fireworks. In this paper, Fireworks Algorithm is applied in training of Multi-Layer Perceptron for classification task in medical data mining. The classification task is carried out on 5 well-known medical data sets from UCI machine learning repository. A comparative study has been made with classical optimization algorithm Levenberg-Marquardt Method and another Swarm Intelligence algorithm Particle Swarm Optimizer. The experimental results show that the proposed method performs better than other algorithms in classification. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.ijcaonline.org/archives/volume137/number1/24236-24236-2016908726?format=pdf |
| Alternate Webpage(s) | https://www.ijcaonline.org/archives/volume137/number1/24236-24236-2016908726?format=pdf |
| Alternate Webpage(s) | http://www.ijcaonline.org/research/volume137/number1/dutta-2016-ijca-908726.pdf |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | Adobe Fireworks Artificial neural network Data mining Fireworks algorithm Levenberg–Marquardt algorithm Machine learning Mathematical optimization Multilayer perceptron Particle swarm optimization Swarm intelligence |
| Content Type | Text |
| Resource Type | Article |
