Location Model Based on Population Distribution of Language

Huang, Yaqun; Ying, Haocong; Chen, Mei‐Ling; Yu, Qinyi; Jiang, Murong; Li, Haiyan

doi:10.1109/iaeac.2018.8577904

Cited by 1 publication

(1 citation statement)

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“…This algorithm was described by the probability transfer matrix and optimized by the particle swarm optimization algorithm to calculate the number of future Language users. Literature [2] builds a population growth model by analyzing population growth and migration rules, so as to observe the development of language communication. Literature [3], based on game theory, holding that a small population size is a key factor for the emergence of language consistency.…”

Section: Introductionmentioning

confidence: 99%

Prediction of Language Users Based on Multi-factor Analysis

Shen¹,

Li²,

Wang³

2019

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Predicting the number of speakers in different languages in the next 50 years will not only have far-reaching significance for human social development, cultural intercommunication, but also have a positive effect on the popularization of common languages and the protection of endangered languages. In order to predict the number of speakers in each language, this paper established a Grey Markov Prediction Model and used the Analytic Hierarchy Process to consider the political and economic strength, population size, language audience, immigration rate and use of electronic communication and social media to correct the results. After 50 years, English, Hindi, and Chinese will become the top three most used languages. The prediction and test results show that the corrected results are more accurate and closer to the actual development of the society, and the accuracy of the results is improved.

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Section: Introductionmentioning

confidence: 99%