用人工神经网络预测土耳其未来的失业率

Mehmet Karahan, Fatma Çetintaş
{"title":"用人工神经网络预测土耳其未来的失业率","authors":"Mehmet Karahan, Fatma Çetintaş","doi":"10.18070/erciyesiibd.1056618","DOIUrl":null,"url":null,"abstract":"In world economies, in order to achieve high national income level, employment has an important effect. Therefore, it is necessary for unemployment to be highly low. Labor force structure of a country specifies the state of that country, and that unemployment rates are at high levels is an indicator of that there is a deviation in the development and growth rate of country economy. In this context, forecasting unemployment rates in the next periods of Turkey, in order to develop solution suggestions for unemployment problem which is one of the most important problems of today, and make contribution to improving country economy, it was decided to conduct such a study. In this forecasting study conducted, due to the fact that the risk to obtain wrong results with traditional methods is high in the solutions of chaotic contented problems, it was decided to be used ANN (Artificial Neural Network) method, which presents healthy solutions of the chaotic problems including partly erroneous or over deviating data and is one of the contemporary methods, commonly used in the literature. In the study, utilizing the monthly basic economic indicators of Turkey belonging to the period of 2005-2018, forecast of unemployment rate for the next periods was made by ANN method, and the data belonging to totally six basic economic indicators were used in the forecast. As a conclusion of the study, it was identified that the forecast made by the model developed produced the reliable results that are quite close to the reality.","PeriodicalId":53159,"journal":{"name":"Erciyes Universitesi Iktisadi ve Idari Bilimler Fakultesi Dergisi","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"FORECASTING OF TURKEY'S UNEMPLOYMENT RATE FOR FUTURE PERIODS WITH ARTIFICIAL NEURAL NETWORKS\",\"authors\":\"Mehmet Karahan, Fatma Çetintaş\",\"doi\":\"10.18070/erciyesiibd.1056618\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In world economies, in order to achieve high national income level, employment has an important effect. Therefore, it is necessary for unemployment to be highly low. Labor force structure of a country specifies the state of that country, and that unemployment rates are at high levels is an indicator of that there is a deviation in the development and growth rate of country economy. In this context, forecasting unemployment rates in the next periods of Turkey, in order to develop solution suggestions for unemployment problem which is one of the most important problems of today, and make contribution to improving country economy, it was decided to conduct such a study. In this forecasting study conducted, due to the fact that the risk to obtain wrong results with traditional methods is high in the solutions of chaotic contented problems, it was decided to be used ANN (Artificial Neural Network) method, which presents healthy solutions of the chaotic problems including partly erroneous or over deviating data and is one of the contemporary methods, commonly used in the literature. In the study, utilizing the monthly basic economic indicators of Turkey belonging to the period of 2005-2018, forecast of unemployment rate for the next periods was made by ANN method, and the data belonging to totally six basic economic indicators were used in the forecast. As a conclusion of the study, it was identified that the forecast made by the model developed produced the reliable results that are quite close to the reality.\",\"PeriodicalId\":53159,\"journal\":{\"name\":\"Erciyes Universitesi Iktisadi ve Idari Bilimler Fakultesi Dergisi\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-05-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Erciyes Universitesi Iktisadi ve Idari Bilimler Fakultesi Dergisi\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.18070/erciyesiibd.1056618\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Erciyes Universitesi Iktisadi ve Idari Bilimler Fakultesi Dergisi","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18070/erciyesiibd.1056618","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

在世界经济中,为了达到较高的国民收入水平,就业有着重要的作用。因此,有必要使失业率保持在极低水平。一个国家的劳动力结构说明了这个国家的状态,失业率处于高水平是这个国家经济发展和增长速度偏离的一个指标。在这方面,为了预测土耳其今后时期的失业率,为了制定解决失业问题的建议,这是当今最重要的问题之一,并为改善国家经济作出贡献,决定进行这样一项研究。在本次预测研究中,由于传统方法在求解混沌满足问题时得到错误结果的风险较大,因此决定采用ANN (Artificial Neural Network,人工神经网络)方法,该方法对数据部分错误或偏差过大的混沌问题给出健康的解决方案,是当代方法之一,文献中常用。本研究利用土耳其2005-2018年月度基本经济指标,采用人工神经网络方法对今后一个时期的失业率进行预测,预测中使用了共6个基本经济指标的数据。研究结果表明,所建立的模型预测结果较为可靠,与实际情况较为接近。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
FORECASTING OF TURKEY'S UNEMPLOYMENT RATE FOR FUTURE PERIODS WITH ARTIFICIAL NEURAL NETWORKS
In world economies, in order to achieve high national income level, employment has an important effect. Therefore, it is necessary for unemployment to be highly low. Labor force structure of a country specifies the state of that country, and that unemployment rates are at high levels is an indicator of that there is a deviation in the development and growth rate of country economy. In this context, forecasting unemployment rates in the next periods of Turkey, in order to develop solution suggestions for unemployment problem which is one of the most important problems of today, and make contribution to improving country economy, it was decided to conduct such a study. In this forecasting study conducted, due to the fact that the risk to obtain wrong results with traditional methods is high in the solutions of chaotic contented problems, it was decided to be used ANN (Artificial Neural Network) method, which presents healthy solutions of the chaotic problems including partly erroneous or over deviating data and is one of the contemporary methods, commonly used in the literature. In the study, utilizing the monthly basic economic indicators of Turkey belonging to the period of 2005-2018, forecast of unemployment rate for the next periods was made by ANN method, and the data belonging to totally six basic economic indicators were used in the forecast. As a conclusion of the study, it was identified that the forecast made by the model developed produced the reliable results that are quite close to the reality.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
18
审稿时长
16 weeks
期刊最新文献
DOĞRUDAN YABANCI YATIRIMLARIN VE TURİZMİN ENERJİ GÜVENLİĞİNE ETKİSİ: SİNGAPUR ÜZERİNE EKONOMETRİK BİR İNCELEME AKILLI PERAKENDECİLİK: KAVRAMSAL ÇERÇEVE, BİLEŞENLER VE ZORLUKLAR BÜROKRASİ TEORİLERİ’NİN YÖNETİM PSİKOLOJİSİ BAĞLAMINDA TEORİK BİR TAHLİLİ ENTREPRENEURSHIP OPPORTUNITIES: SMART CITY AND DIGITALIZATION THE IMPACT OF MONETARY SHOCKS ON INFLATION IN SELECTED WEST ASIAN COUNTRIES
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1