Optimizing location of manufacturing industries in the context of economic globalization: A bi-level model based approach

2018 ◽  
Vol 501 ◽  
pp. 327-337 ◽  
Author(s):  
Shanhua Wu ◽  
Zhongzhen Yang
Keyword(s):  
Economic Globalization ◽  
Manufacturing Industries ◽  
Model Based ◽  
Level Model

scholarly journals Logistics digital transformation model based on a platform solution

2021 ◽  
Vol 258 ◽  
pp. 02024
Author(s):  
Aleksandr Kozlov ◽  
Anna Smirnova ◽  
Irina Zaychenko ◽  
Yevhenii Shytova ◽  
Joanna Kalkowska
Keyword(s):  
Digital Transformation ◽  
Transformation Model ◽  
Interaction Models ◽  
Model Based ◽  
Stakeholder Interaction ◽  
Level Model ◽  
The Creation

This paper is devoted to researching the major aspects of the digital transformation of the logistical field. Provided are the suggestions for constructing logistical process stakeholder interaction models. One of the major trends in digital logistics is platform solutions that will come to replace specialized digital solutions. Based on this trend, authors provide the 3-level model of stakeholder interaction on the logistical platform which could form the foundation of a future platform solution architecture. The creation of the logistical platform is the next step in the digital transformation of logistics which aims to create a unified logistical ecosystem.

A High Level Model of a Conscious Embodied Agent

2010 ◽  
Vol 2 (3) ◽  
pp. 62-78 ◽  
Author(s):  
Jirí Wiedermann
Keyword(s):  
Cognitive Functions ◽  
Mirror Neurons ◽  
Semantic Knowledge ◽  
Neural Nets ◽  
Imitation Learning ◽  
Model Based ◽  
Level Model ◽  
Higher Cognitive Functions ◽  
High Level ◽  
Embodied Agent

In this paper, the author describes a simple yet cognitively powerful architecture of an embodied conscious agent. The architecture incorporates a mechanism for mining, representing, processing and exploiting semantic knowledge. This mechanism is based on two complementary internal world models which are built automatically. One model (based on artificial mirror neurons) is used for mining and capturing the syntax of the recognized part of the environment while the second one (based on neural nets) for its semantics. Jointly, the models support algorithmic processes underlying phenomena similar in important aspects to higher cognitive functions such as imitation learning and the development of communication, language, thinking, and consciousness.

Variable cycle control model for intersection based on multi-source information

2018 ◽  
Vol 32 (13) ◽  
pp. 1850160 ◽  
Author(s):  
Zhi-Yuan Sun ◽  
Yue Li ◽  
Wen-Cong Qu ◽  
Yan-Yan Chen
Keyword(s):  
Traffic Flow ◽  
Programming Model ◽  
Control Model ◽  
Transmission Model ◽  
Signal Control ◽  
Hysteresis Phenomenon ◽  
Source Information ◽  
Model Based ◽  
Proposed Model ◽  
Level Model

In order to improve the efficiency of traffic control system in the era of big data, a new variable cycle control model based on multi-source information is presented for intersection in this paper. Firstly, with consideration of multi-source information, a unified framework based on cyber-physical system is proposed. Secondly, taking into account the variable length of cell, hysteresis phenomenon of traffic flow and the characteristics of lane group, a Lane group-based Cell Transmission Model is established to describe the physical properties of traffic flow under different traffic signal control schemes. Thirdly, the variable cycle control problem is abstracted into a bi-level programming model. The upper level model is put forward for cycle length optimization considering traffic capacity and delay. The lower level model is a dynamic signal control decision model based on fairness analysis. Then, a Hybrid Intelligent Optimization Algorithm is raised to solve the proposed model. Finally, a case study shows the efficiency and applicability of the proposed model and algorithm.

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