摘要翻译：
本文介绍了信息粒化理论在岩石工程流程图设计中的应用。首先，给出了一个基于信息粒度理论的总体流程。信息粒化理论以清晰的（非模糊的）或模糊的形式，在设计过程的每一步都能考虑到工程经验（尤其是模糊的形状--不完全信息或多余信息）或工程判断，同时采用合适的仪器建模。利用自组织映射(SOM)、神经模糊推理系统(NFIS)和粗糙集理论(RST)的三种组合，从监测数据集中获得了清晰和模糊颗粒，并扩展了软建模工具。算法的核心是在开闭迭代过程中，在非模糊信息（初始粒）内平衡清晰粒（粗粒或非模糊粒）和次模糊粒。利用不同的平衡准则，得到了最佳颗粒（信息袋）。重点介绍了我们提出的方法在伊朗什瓦山大坝岩体原位渗透率数据集上的验证。
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英文标题：
《Rock mechanics modeling based on soft granulation theory》
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作者：
H.Owladeghaffari
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最新提交年份：
2008
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分类信息：

一级分类：Computer Science        计算机科学
二级分类：Artificial Intelligence        人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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英文摘要：
  This paper describes application of information granulation theory, on the design of rock engineering flowcharts. Firstly, an overall flowchart, based on information granulation theory has been highlighted. Information granulation theory, in crisp (non-fuzzy) or fuzzy format, can take into account engineering experiences (especially in fuzzy shape-incomplete information or superfluous), or engineering judgments, in each step of designing procedure, while the suitable instruments modeling are employed. In this manner and to extension of soft modeling instruments, using three combinations of Self Organizing Map (SOM), Neuro-Fuzzy Inference System (NFIS), and Rough Set Theory (RST) crisp and fuzzy granules, from monitored data sets are obtained. The main underlined core of our algorithms are balancing of crisp(rough or non-fuzzy) granules and sub fuzzy granules, within non fuzzy information (initial granulation) upon the open-close iterations. Using different criteria on balancing best granules (information pockets), are obtained. Validations of our proposed methods, on the data set of in-situ permeability in rock masses in Shivashan dam, Iran have been highlighted.
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PDF链接：
https://arxiv.org/pdf/0805.4560