恶化逃税的非行政模型:利用NLP档案形成纳税人欣愉的社会控制论应用

V. Kanavas, A. Zisopoulos, Razis Dimitrios
{"title":"恶化逃税的非行政模型:利用NLP档案形成纳税人欣愉的社会控制论应用","authors":"V. Kanavas, A. Zisopoulos, Razis Dimitrios","doi":"10.5296/RAE.V9I4.11904","DOIUrl":null,"url":null,"abstract":"With our Socio-Cybernetic Application we present a minimal approach to reduce tax evasion. Theoretically we use proven theories of Neuro Linguistic Processing, Christian Virtues influence, Cognitive Psychology guidelines, Tax collection and law enforcement principles. Our database are taxpayers, payments Beneficiary, Neuro Linguistic Programming reference points, Virtue points, etc. From the last two we create the Personal Human Space database with 1803 records. Then we analyze every person in the Taxpayers and money Receivers database and according to the theoretical guidance we formulate a specific limited human-space diagram for all 7 million persons and legal entities. As an example, we demonstrate the exact math and Matlab methodology to match a Taxpayer and money beneficiary with scoreboard 65 non-zero diagram points. The working system could be useful for Financial Intelligent Units, Economic Law enforcement agencies and Immigration Authorities.","PeriodicalId":225665,"journal":{"name":"Research in Applied Economics","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Non-Administrative Models to Deteriorate Tax Evasion, a Socio-Cybernetic Application using NLP Archives for Taxpayer Euphoria Formation\",\"authors\":\"V. Kanavas, A. Zisopoulos, Razis Dimitrios\",\"doi\":\"10.5296/RAE.V9I4.11904\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With our Socio-Cybernetic Application we present a minimal approach to reduce tax evasion. Theoretically we use proven theories of Neuro Linguistic Processing, Christian Virtues influence, Cognitive Psychology guidelines, Tax collection and law enforcement principles. Our database are taxpayers, payments Beneficiary, Neuro Linguistic Programming reference points, Virtue points, etc. From the last two we create the Personal Human Space database with 1803 records. Then we analyze every person in the Taxpayers and money Receivers database and according to the theoretical guidance we formulate a specific limited human-space diagram for all 7 million persons and legal entities. As an example, we demonstrate the exact math and Matlab methodology to match a Taxpayer and money beneficiary with scoreboard 65 non-zero diagram points. The working system could be useful for Financial Intelligent Units, Economic Law enforcement agencies and Immigration Authorities.\",\"PeriodicalId\":225665,\"journal\":{\"name\":\"Research in Applied Economics\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-11-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Research in Applied Economics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5296/RAE.V9I4.11904\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Research in Applied Economics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5296/RAE.V9I4.11904","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

通过我们的社会控制论应用,我们提出了一种减少逃税的最小方法。从理论上讲,我们使用神经语言处理,基督教美德的影响,认知心理学指导方针,税收和执法原则的证明理论。我们的数据库有纳税人,付款受益人,神经语言规划参考点,美德点等。根据最后两个,我们创建了包含1803条记录的Personal Human Space数据库。然后,我们分析了纳税人和收款人数据库中的每个人,并根据理论指导,为所有700万个人和法人实体制定了具体的有限人类空间图。作为一个例子,我们演示了精确的数学和Matlab方法来匹配纳税人和货币受益人与记分牌65个非零图表点。该工作系统可为金融情报单位、经济执法机构和移民当局所用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Non-Administrative Models to Deteriorate Tax Evasion, a Socio-Cybernetic Application using NLP Archives for Taxpayer Euphoria Formation
With our Socio-Cybernetic Application we present a minimal approach to reduce tax evasion. Theoretically we use proven theories of Neuro Linguistic Processing, Christian Virtues influence, Cognitive Psychology guidelines, Tax collection and law enforcement principles. Our database are taxpayers, payments Beneficiary, Neuro Linguistic Programming reference points, Virtue points, etc. From the last two we create the Personal Human Space database with 1803 records. Then we analyze every person in the Taxpayers and money Receivers database and according to the theoretical guidance we formulate a specific limited human-space diagram for all 7 million persons and legal entities. As an example, we demonstrate the exact math and Matlab methodology to match a Taxpayer and money beneficiary with scoreboard 65 non-zero diagram points. The working system could be useful for Financial Intelligent Units, Economic Law enforcement agencies and Immigration Authorities.
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
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信