@inproceedings{cfa9f880c71641edb7d47550b4f31e80,
title = "Training a dendritic neural model with genetic algorithm for classification problems",
abstract = "Recently, more neuroscience researches focus on the role of dendritic structure during the neural computation. Inspired by the specified topologies of numerous dendritic trees, we proposed a single neural model with a particular dendritic structure. The dendrites are composed of several branches, and these branches correspond to three distributions in coordinate, which are used to classify the training data as required. Genetic algorithm is used as the training algorithm. Experimental results based on two benchmark classification problems verify the effectiveness of the proposed method, and the distributions of trained dendritic structures are also presented.",
keywords = "Classification, Dendritic neuron model, Genetic algorithm, Neural network",
author = "Junkai Ji and Zhenyu Song and Yajiao Tang and Tao Jiang and Shangce Gao",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 4th IEEE International Conference on Progress in Informatics and Computing, PIC 2016 ; Conference date: 23-12-2016 Through 25-12-2016",
year = "2017",
month = jun,
day = "15",
doi = "10.1109/PIC.2016.7949465",
language = "英語",
series = "PIC 2016 - Proceedings of the 2016 IEEE International Conference on Progress in Informatics and Computing",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "47--50",
editor = "Yinglin Wang and Yaoru Sun",
booktitle = "PIC 2016 - Proceedings of the 2016 IEEE International Conference on Progress in Informatics and Computing",
}