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Model-based system tool for Thai Tax Revenue Forecasting (MBS-TTRF)

机译:基于模型的泰国税收预测系统工具(MBS-TTRF)

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Model-Based System Tool for Thai Tax Revenue Forecasting (MBS-TTRF) is a model-based management system used to provide the flexibility and increase efficiency of Thai Tax Revenue Forecasting in the Revenue Department (RD). MBSTTRF contains five essential model-categories for Tax Revenue Forecasting, i.e., ETTRF Models, NITTRF Models, STTRF Models, TTRF A Models, and TTRFAC Models. The system supports the data analytical functions: Sensitivity, What-if and Goal-seeking analysis, useful for analyzing results before making a decision. Furthermore, this system also improves the accuracy of Thai Tax Revenue Forecasting by adding regression approach to NITTRF. The experimental results showed that NITTRF generated better results than the existing model-ETTRF. The results also showed that MBS-TTRF is suitable to assist a user/decision maker as an alternative model to forecast tax revenue and reduces time for Thai Tax Revenue Forecasting operation that depends mainly on human expertise.
机译:泰国税收收入预测的基于模型的系统工具(MBS-TTRF)是基于模型的管理系统,用于在收入部(RD)中提供灵活性和提高泰国税收收入预测的效率。 MBSTTRF包含用于税收预测的五个基本模型类别,即ETTRF模型,NITTRF模型,STTRF模型,TTRF A模型和TTRFAC模型。该系统支持数据分析功能:敏感性,假设分析和目标寻找分析,可用于在做出决定之前分析结果。此外,该系统还通过向NITTRF添加回归方法来提高泰国税收预测的准确性。实验结果表明,NITTRF比现有的ETTRF模型产生了更好的结果。结果还表明,MBS-TTRF适用于协助用户/决策者,作为预测税收收入的替代模型,并减少了主要依赖于人类专业知识的泰国税收收入预测操作的时间。

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