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Polarized marketing resource planning model for super descreate micro agent knowledge system using applied cooperate finance model connected with geometric economic researches

机译:结合几何经济学研究的应用合作财务模型建立超级微代理知识系统的极化营销资源计划模型

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In this paper, I intend to describe some network architectual views about installable syntaxual invisible tacitly accounting elements which should be planned according to common knowledge system structures under ubiquitous conditions which are also suitable for geometric economics studie conditions. And on these issues, we should discuss syntaxual accounting element measurabilities, and optimized modeling about social structures which should be suit to super extensive client agent models. This paper mainly due to macro economics based descriptions convolluted syntaxual knowledge elements, which should be adoptable for Arrow's convexity agent model for equibrium ecocomic theory. This paper shows that multiplex and segmented conversion from social non descreate syntaxual soicial conditions toward semantic knowledge geometries can be describe by adoptable Kullback - Lieber newral macro conversion models in bench models. And therefore several KL conversion scopes about graphical geometries and other sort of studies and experimentals should obtain alternative application discourse for semistrong semantic knowledge description. And then, we should discover efficienftagent gatherings by genetic algorithum based acknowledge models.
机译:在本文中,我打算描述一些有关可安装的语法不可见的默认计算元素的网络体系结构视图,这些元素应根据普遍存在的条件下的通用知识系统结构进行规划,这些条件也适用于几何经济学研究条件。在这些问题上,我们应该讨论语法上的会计元素可度量性,并应针对社会结构进行优化建模,以适合超广泛的客户代理模型。本文主要是由于基于宏观经济学的描述混淆了语法知识元素,因此应将其用于平衡经济理论的阿罗的凸代理模型。本文表明,可以在工作台模型中采用可采用的Kullback-Lieber newral宏转换模型来描述从社交非消极语法语法条件向语义知识几何的多重转换和分段转换。因此,关于图形几何以及其他种类的研究和实验的几种KL转换范围应获得半强语义知识描述的替代应用话语。然后,我们应该通过基于遗传算法的认知模型发现有效的药物聚集。

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