Foundations and Modeling of Dynamic Networks Using Dynamic Graph Neural Networks: A Survey
نویسندگان
چکیده
Dynamic networks are used in a wide range of fields, including social network analysis, recommender systems, and epidemiology. Representing complex as structures changing over time allow models to leverage not only structural but also temporal patterns. However, dynamic literature stems from diverse fields makes use inconsistent terminology, it is challenging navigate. Meanwhile, graph neural (GNNs) have gained lot attention recent years for their ability perform well on science tasks, such link prediction node classification. Despite the popularity proven benefits models, there has been little focus networks. To address challenges resulting fact that this research crosses survey networks, work split into two main parts. First, ambiguity terminology we establish foundation with consistent, detailed notation. Second, present comprehensive using proposed
منابع مشابه
dynamic coloring of graph
در این پایان نامه رنگ آمیزی دینامیکی یک گراف را بیان و مطالعه می کنیم. یک –kرنگ آمیزی سره ی رأسی گراف g را رنگ آمیزی دینامیکی می نامند اگر در همسایه های هر رأس v?v(g) با درجه ی حداقل 2، حداقل 2 رنگ متفاوت ظاهر شوند. کوچکترین عدد صحیح k، به طوری که g دارای –kرنگ آمیزی دینامیکی باشد را عدد رنگی دینامیکی g می نامند و آنرا با نماد ?_2 (g) نمایش می دهند. مونت گمری حدس زده است که تمام گراف های منتظم ...
15 صفحه اولDynamic Sliding Mode Control of Nonlinear Systems Using Neural Networks
Dynamic sliding mode control (DSMC) of nonlinear systems using neural networks is proposed. In DSMC the chattering is removed due to the integrator which is placed before the input control signal of the plant. However, in DSMC the augmented system is one dimension bigger than the actual system i.e. the states number of augmented system is more than the actual system and then to control of such ...
متن کاملComputational modeling of dynamic decision making using connectionist networks
In this research connectionist modeling of decision making has been presented. Important areas for decision making in the brain are thalamus, prefrontal cortex and Amygdala. Connectionist modeling with 3 parts representative for these 3 areas is made based the result of Iowa Gambling Task. In many researches Iowa Gambling Task is used to study emotional decision making. In these kind of decisio...
متن کاملModeling and Control of Gas Turbine Combustor with Dynamic and Adaptive Neural Networks (TECHNICAL NOTE)
متن کامل
A DSS-Based Dynamic Programming for Finding Optimal Markets Using Neural Networks and Pricing
One of the substantial challenges in marketing efforts is determining optimal markets, specifically in market segmentation. The problem is more controversial in electronic commerce and electronic marketing. Consumer behaviour is influenced by different factors and thus varies in different time periods. These dynamic impacts lead to the uncertain behaviour of consumers and therefore harden the t...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Access
سال: 2021
ISSN: ['2169-3536']
DOI: https://doi.org/10.1109/access.2021.3082932