Accurate regional wind power prediction is of great significance to the wind farm clusters
integration and the economic dispatch of the regional power grid. The complex …

Density peaks clustering (DPC) is as an efficient clustering algorithm due for using a non-
iterative process. However, DPC and most of its improvements suffer from the following …

Clustering is a major approach in data mining and machine learning and has been
successful in many real-world applications. Density peaks clustering (DPC) is a recently …

Density peaks clustering (DPC) has been proved to be an effective clustering method and
applied to many scientific fields. It can detect the density peak within each cluster and assign …

Density peaks clustering (DPC) algorithm is proposed to identify the cluster centers quickly
by drawing a decision-graph without any prior knowledge. Meanwhile, DPC obtains arbitrary …

Clustering is a task used to group data from variegated sources, including Big Data, the
Internet of Things, and social media. Density peaks clustering (DPC) has become a popular …

Educational data-mining is an evolving discipline that focuses on the improvement of self-
learning and adaptive methods. It is used for finding hidden patterns or intrinsic structures of …

The study of parallel task models executed with predictable scheduling approaches is a
fundamental problem for real-time multiprocessor systems. Nevertheless, to date, limited …

Searching a suitable parking space in populated metropolitan city is extremely difficult for
drivers. Serious traffic congestion may occur due to unavailable parking space. Automatic …

在紧急疏散场景中, 个人具有的典型社会属性会对其疏散行为产生影响. 将个体对环境的熟悉
程度和个体所属团队这2 种社会因素引入并应用到人群疏散仿真中, 提出一种疏散仿真方法 …