The invention relates to an Internet-of-vehicles
big data cross-
domain analysis fusion method, which is mainly characterized in that an Internet-of-vehicles
cloud data mining architecture is established, and
the Internet-of-vehicles
cloud data mining architecture comprises a distributed
data access engine, a parallel mining engine, proxy nodes and a
Web server cluster; performing
data mining by adopting an Internet-of-vehicles
data mining algorithm; and realizing a parallel function of the
shared memory by adopting a
shared memory parallel computing technology. According to the method, a clouddata mining architecture which is composed of a distributed
data access engine, a parallel mining engine, a
Web server cluster and agent nodes and can support
parallel computing is adopted, so that the supporting capability for
mass data is improved; through a data preprocessing technology, an
uncertain data preprocessing technology and an Internet-of-vehicles industry
data processing and fusiontechnology, support of Internet-of-vehicles specific data such as
streaming data is optimized; based on novel
data mining algorithms such as mining, analysis, clustering technology,
behavior recognition and
anomaly detection of
the Internet-of-vehicles
streaming data, the intelligent level of the
system is improved.