The charm

今天给大家带来一篇优秀的论文 供大家参考学习，这篇论文讨论了语言。语言，是人类的重要组成部分，更是人类沟通交流的桥梁。借助合适的语言，人们能够恰当地表达自己的思想，可以拉近人与人之间的距离。人类生活中离不开语言，但是绝大多数人对于语言的规律不甚了解。实际上，语言的数量和语言的规模，随着人类历史的推移也在不断的变化，在全球化进程中强势语言迅猛传播，而弱势语言随着语言功能衰减使用人数不断减少，逐渐走向濒危和消亡。话不多说  一起来看看吧 有论文需要帮忙的亲亲可以联系我们的专属客服 Even100100进行咨询喔~ 

Language is an important part of human beings and a bridge of human communication. With the right language, people can express their thoughts properly, which can shorten the distance between people. Language is indispensable in human life, but most people don't know much about the laws of language. In fact, the number of languages and the scale of languages are constantly changing with the passage of human history. In the process of globalization, strong languages spread rapidly, while weak ones gradually become endangered and die out with the declining number of speakers of language functions. How to select the most versatile among the various languages, how to achieve accurate result prediction in the intricate distribution transfer of language, and if the above two questions are answered, the results are encouraging. In this paper, we establish a multi-factor continuous language population model, carry out time series analysis, apply logistic regression algorithm and stochastic gradient descent to achieve the model solution, and give the result analysis.

In order to predict the language distribution and change trend, we established a model to predict the distribution of various language users over time and the number of language users changes within 50 years, and judged whether the languages in the list of top 10 languages were still in the top 10. In addition, the distribution of language is predicted and described in the context of the global population migration.

As shown in the figure, language users of a region can be divided into three states, and the changes of each state are given the state transition parameters. They constitute the basic model, and there is a state transition relationship between them.

In the continuous model, we use the transformation parameter to calculate the change of the number of speakers of each language in a region after a time step, and then predict the change of the number of speakers over time. The definition required for model parameters is given in figure 2.

As for the number of non-official speakers in the region, it can be seen that the conversion comes from people moving in from n-speaking countries and people who do not have a second language in the region.

Considering the different influences of political economy, culture and society in different regions, we introduced the transformation parameter ki and the judgment factor aN. Ki represents the influence of I district government promotion, school use and social pressure on the second language. If language N is the second language promoted by the local government, then aN=1 =1, otherwise 0. Therefore, we get formula B as follows:

Where possible, we use real data to provide appropriate estimates for these parameters. This method of providing parameters for parameters provides a real basis for language changes in the model.

As the implementation of the second language is mainly realized through education, which is positively correlated with education investment and the calculation formula obtained by referring to relevant literature, c is the influencing factor that integrates policy, social pressure and international trade

Since no reliable data can be used to determine C, their values are defined as anthropological data. This ensures that our model is accurate and allows C as part of the solution to provide predictions of language change in the world.

As time goes on, Chinese, English and punjabi occupies the proportion of increase gradually, we think that because of China's big population base, the new birth population is much, so to master the high proportion of Chinese and the language of the developed countries such as Britain, the United States is English, because of high international standing in the developed countries, the language high liquidity, most countries are willing to speak English as a second language. As punjabi is the common language of Africa, africans gradually began to explore the African market over time and began to learn punjabi.

In terms of the proportion of total language use, the proportion of Bengali has been decreasing continuously in the past 50 years, which has been kicked out of the top 10 languages and replaced by German. The reason is analyzed, and we believe that the number of German is higher due to the strong demand of German industrial production, good economic situation and positive attitude of the market.

Overall, European languages have been languishing, possibly because of Europe's low birth rate associated with an aging society.

In our analysis, we considered independent of the government, schools, social pressure influence on language, at the same time testing the birth rate and mortality rates change over time of three conditions: population growth, population constant, population growth, in the short term and the medium to longer term take different demographic change pattern, enables us to determine the factors underlying language change, analyze the practical significance of the language change to better improve our model, at the same time, we got the following qualitative conclusions.

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