IAI：不完全人工智能

“不完全人工智能”（Incomplete Artificial Intelligence）在计算机领域常被缩写为“IAI”，这一简称便于书写和快速使用。该术语用于描述功能或认知能力尚不完善的人工智能系统，在相关技术讨论和文档中较为常见。

Rough Set Theory is an extension of Set Theory and a relatively new soft computing tool to analyze and process incomplete information effectively, which has been successfully applied in artificial intelligence, data mining, pattern recognition and other related research areas in recent years.
粗糙集理论是集合论的扩展，是一种新的软计算方法，可以有效地分析和处理不完备信息，近年来被成功地应用于人工智能、数据挖掘、模式识别等诸多领域。
Rough set theory is a mathematical tool that can process information of incomplete and inaccuracy, Which is widely used in data mining and artificial intelligence.
粗糙集理论作为一种能够对不完全和不确定信息进行处理的数学工具，被广泛应用于数据挖掘和人工智能等领域。
Rough Set Theory is a Data Mining approach capable of dealing with incomplete and inaccurate data, and it has been successfully applied to Artificial Intelligence and Knowledge Discovery, Pattern Recognition and Classification, and Fault Detection.
粗糙集理论是数据挖掘的方法之一，它是处理模糊和不确定知识的一种数学工具，已在人工智能与知识发现，模式识别与分类，故障检测等方面得到了较好应用。

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