граф

This article analyzes three most common approaches to the GNN architecture implementation on the AWS cloud for the use case of the risk assessment in the insurance area. The paper is split to several chapters, with the first one being the overview of 3 approaches to the GNN architecture, the second one describing prerequisites for the implementation, and finally development of the approaches on the cloud infrastructure, testing them on graph insurance data and comparison of all the approaches to select the most suitable for the risk assessment task.

This article embarks on an insightful journey through the realm of advanced data analysis techniques which can be used in the insurance area, with a keen focus on the applications and capabilities of Graph Neural Networks (GNN) in the following sector.

Побудовано та досліджено базовий варіант моделі процесу планування вантажо- перевезень, що складається з послідовності обраних окремих підзадач, утворених відібраною системою спрощувальних припущень, що дає змогу розв’язати поставлену задачу в умовах багатокритеріальності та наявності часових обмежень.

We construct and study a basic version of the model planning process cargo. It consists of a sequence of individual subtasks that created the system of simplifying assumptions. It allows you to solve the task in bahatokryterialnosti and available time limits.

This paper proposes a new application of the stochastic game model to solve the problem of self- organization of the Hamiltonian cycle of a graph. To do this, at the vertices of the undirected graph are placed game agents, whose pure strategies are options for choosing one of the incident edges. A random selection of strategies by all agents forms a set of local paths that begin at each vertex of the graph. Current player payments are defined as loss functions that depend on the strategies of neighboring players that control adjacent vertices of the graph.

мережа загального користування, модель, граф, випадкова функція, загроза, захищеність, потік Пуассона.