混合智能系统的发展及其应用 从工程系统到复杂系统

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摘要翻译：
本文介绍了多连通智能粒子系统(MACIPS)的一般框架。粒子之间的连接和互连得到了这样一个简单系统（系统中的系统）的复杂行为，自然计算在信息粒化理论下的贡献是这个广阔骨架的主要主题。在此基础上，我们整理了几种主要的智能计算和近似推理方法，如自组织特征映射(SOM)[9]、神经模糊推理系统[10]、粗糙集理论(RST)[11]、协同聚类、遗传算法和蚁群系统。在此基础上，我们将我们的算法应用于几个工程系统，特别是民用和矿物加工中出现的系统。在另一个过程中，我们研究了如何将我们的算法作为政府-社会互动的一个链接，在这个链接中，政府捕捉各种行为时尚：固体（绝对）或灵活。因此，通过连通性参数（噪声）从有序到无序的变化，可以推断出这种社会的转变。此外，人们可能会发现金融系统和最终的市场波动与MACIPS之间的间接映射。在下面的章节中，我们将提到所建议的方案的主要主题，所建议的算法的简要细节可以在参考文献中找到。
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英文标题：
《Development of Hybrid Intelligent Systems and their Applications from
  Engineering Systems to Complex Systems》
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作者：
Hamed 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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一级分类：Computer Science        计算机科学
二级分类：Multiagent Systems        多智能体系统
分类描述：Covers multiagent systems, distributed artificial intelligence, intelligent agents, coordinated interactions. and practical applications. Roughly covers ACM Subject Class I.2.11.
涵盖多Agent系统、分布式人工智能、智能Agent、协调交互。和实际应用。大致涵盖ACM科目I.2.11类。
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英文摘要：
  In this study, we introduce general frame of MAny Connected Intelligent Particles Systems (MACIPS). Connections and interconnections between particles get a complex behavior of such merely simple system (system in system).Contribution of natural computing, under information granulation theory, are the main topic of this spacious skeleton. Upon this clue, we organize different algorithms involved a few prominent intelligent computing and approximate reasoning methods such as self organizing feature map (SOM)[9], Neuro- Fuzzy Inference System[10], Rough Set Theory (RST)[11], collaborative clustering, Genetic Algorithm and Ant Colony System. Upon this, we have employed our algorithms on the several engineering systems, especially emerged systems in Civil and Mineral processing. In other process, we investigated how our algorithms can be taken as a linkage of government-society interaction, where government catches various fashions of behavior: solid (absolute) or flexible. So, transition of such society, by changing of connectivity parameters (noise) from order to disorder is inferred. Add to this, one may find an indirect mapping among finical systems and eventual market fluctuations with MACIPS. In the following sections, we will mention the main topics of the suggested proposal, briefly Details of the proposed algorithms can be found in the references.
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PDF链接：
https://arxiv.org/pdf/0806.2356

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关键词：复杂系统 工程系 Intelligence Applications Presentation 噪声 our 建议 government Upon