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Cellular Automata Epidemic (CAE) Model for Language Development Prediction

机译:用于语言发展预测的元胞自动机流行病(CAE)模型

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This paper proposes a cellular-automata-epidemic (CAE) model which is a combination of cellular-automata and epidemic model for predicting the language development in 50 years. In this model, three factors are considered: the international trade, global tourism and social communication. The Principal Component Analysis (PCA) is used to calculate scores which rank the effect of languages. The language which learned by people are chose by the roulette algorithm. The result shows that Bengali, Punjabi languages will fall out of top 10 and the language of French and German will get into the top 10. We believe that this work will contribute to the construction of linguistic disciplines and the development of languages.
机译:本文提出了一种将细胞自动机和流行病模型相结合的细胞自动机流行病(CAE)模型,以预测50年的语言发展。在此模型中,考虑了三个因素:国际贸易,全球旅游业和社会传播。主成分分析(PCA)用于计算对语言影响进行排名的分数。人们通过轮盘赌算法选择学习的语言。结果表明,孟加拉语,旁遮普语将排在前10名之列,而法语和德语将排在前10名。我们相信这项工作将有助于语言学科的建设和语言的发展。

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