BDE

Current intersection signal control studies mainly consider the passage of motor vehicles, with too little consideration given to pedestrians and non-motorized factors. This has led to many unsafe hazards in slow-moving traffic at intersections, such as ...

Bearing fault diagnosis is an extremely important application in production and daily life. With the development of big data technology, deep learning has become one of the main methods for bearing fault diagnosis. However, when encountering unknown ...

The RNS based Software Defined Networks usually apply single link failure recovery technique as routing approach. Implementations of SDN often result in multiple link failures. Therefore, network functioning becomes highly dependent on the resiliency of ...

Deep learning frameworks have achieved extraordinary results in popular technological frontiers, which also greatly inspires considerable researchers in recommender system. As one of the mainstream research frontiers, click-through rate (CTR) predictions ...

With the proliferation of the internet, credit card fraud has become a pressing issue, leading to substantial financial losses and undermining trust among consumers. This research aims to elucidate the determinants associated with credit card fraud. By ...

Supply chain management is vital to the development of businesses. In order to maximize the benefits of supply chain management and improve the level of supply chain system management, this paper proposes a data-driven supply chain management ...

This study proposes a multi-factor prediction model to forecast the box office performance of movie sequels. Both endogenous and exogenous variables related to sequel and predecessor films are examined, including budget, runtime, genre, changing of ...

Finding the k-nearest-neighbor (k NN) of a query node in a large graph is a fundamental problem. Existing CPU-based local search for random walk methods can solve this problem but are not suitable for dense graphs. Recently, many k NN query algorithms ...

Recommender systems are essential information technologies today, and recommendation algorithms combined with deep learning have become a research hotspot in this field. The recommendation model known as LFM (Latent Factor Model), which captures latent ...

In this paper, we propose a CLIP-based extraction model of Chinese character content and font style. The model utilizes an embedding layer to encode Chinese characters and font style, a residual network to extract features from images, and a contrast ...

With the continuous deepening of financial business informationization, the rapid spread of all kinds of financial data, promoting the financial field to enter the era of big data, and the structural transformation and dynamic development of the ...