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Process Modelling and Creating Predictive Models of Sensory Networks Using Fuzzy Petri Nets

机译:使用模糊Petri网的流程建模和创建感官网络的预测模型

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The current period is evidence of the massive replacement of human power with the results of the mental cognitive work of researchers. This mainly concerns the area of industrial production, where the aim is to apply new technologies on the principle of artificial intelligence, using the possibilities of a new direction in the use of a technology called the Internet of Things (IoT). With this idea, however, the question of the user disappears, who in this chaos of massive information can get into a state, where his activities will no longer be manageable. To cope with this situation, it is necessary to examine the impact of these technologies on the quality of life in the work and home environment. This paper investigates process modelling and the creation of predictive models to obtain the emotional state of users. The created predictive models will later allow the simulation of complex sensory systems, which will be able to predict the emotional states of users based on their physiological states. The aim is to also find connections between physiological states and basic emotions to be able to classify user emotions with the highest possible accuracy in the classification process.
机译:目前的时期是与研究人员的精神认知工作的结果大规模更换人力的证据。这主要涉及工业生产领域,目的是利用新方向在使用一种称为物联网(物联网)的技术中的新方向的可能性来应用新技术。然而,通过这种想法,用户的问题消失,在这种大规模信息的混乱中可以进入一个国家,他的活动将不再可管理。为了应对这种情况,有必要检查这些技术对工作和家庭环境的生活质量的影响。本文调查了过程建模和创建预测模型,以获得用户的情感状态。创建的预测模型后来将允许模拟复杂的感官系统,这将能够根据其生理状态预测用户的情绪状态。目的是发现生理状态和基本情绪之间的联系能够在分类过程中以最高可能的准确性对用户情绪进行分类。

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