We consider the price-optimal earliest arrival problem in public transit (POEAP) in which we aim to calculate the Pareto-set of journeys with respect to ticket price and arrival time in a public transportation network. Public transit fare structures are often a combination of various fare...

Sustainable urban development involves many fields with complex data types and rich semantic relationships, such as the economic, societal, and ecological fields. Knowledge graphs provide a new means for sustainable urban development research by leveraging their strengths in the construction of...

Mean-field games (MFGs) are developed to model the decision-making processes of a large number of interacting agents in multi-agent systems. This paper studies mean-field games on graphs (𝒢-MFGs). The equilibria of 𝒢-MFGs, namely, mean-field equilibria (MFE), are challenging to solve for...

Graphical games describe strategic interactions among a specified network of players. The threshold protocol game is a graphical game that models the adoption of a lesser-used product in a population when individuals benefit by using the same product. The threshold protocol game has historically...

The threshold protocol game is a graphical game that models the adoption of an idea or product through a population. There are two states players may take in the game, and the goal of the game is to motivate the state that begins in the minority to spread to every player. Here, the threshold...

Information about decision-makers' preferences is essential for the efficient modeling of a conflict. However, obtaining this information becomes more challenging as the size of the conflict increases. To address this issue, this study proposes a new approach to the option prioritizing method...

In the digital economy age, carbon emission reduction is perhaps the most crucial contribution affecting national activities and international negotiations. In a potential carbon reduction conflict, a rational participant expects to select a suitable strategic opinion to reach another state with...

There has been significant interest in integrating sentiment analysis with graph neural networks (GNNs) for stock prediction tasks. This article thoroughly reviews the application of GNNs in conjunction with sentiment analysis for stock prediction. This study introduces the fundamental concepts...

The increasing popularity of digital twins, alongside the rapid evolution of connectivity driven by the Internet of Things, highlights their potential to greatly aid in the development of smart cities. Digital twins are employed more commonly as smart cities grow and societies become more...

Credit risk prediction for small and medium enterprises (SMEs) has long posed a complex research challenge. Traditional approaches have primarily focused on enterprise-specific variables, but these models often prove inadequate when applied to SMEs with incomplete data. In this innovative study,...

Community detection can help uncover and understand complex networks' underlying patterns and structures. It involves identifying cohesive groups with similar entities while being separated from other groups. Social networks are a prime example of an area where community detection is...

We study binary action network games with strategic complementarities. An agent acts if the aggregate social influence of her friends exceeds a transfer levied on the agent by a principal. The principal seeks to maximize her revenue while inducing everyone to act in a unique equilibrium. We...

In this study, we explore the financial and economic integration of BRICS nations (Brazil, Russia, India, China, and South Africa) and key emerging economies (Egypt, Saudi Arabia, and the UAE) using graph theory, aiming to map intersectoral connections and their impact on financial stability and...