Hybrid clustering method for simulating bifurcation and brain inspiration cognition

A clustering method and bifurcation technology, applied in character and pattern recognition, instruments, computer components, etc., can solve problems such as poor robustness and initial point sensitivity

Pending Publication Date: 2022-04-26
上海图灵智算量子科技有限公司
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Problems solved by technology

As a conventional solution, the K-means algorithm is widely used to solve traffic clustering problems, but it has limitations such as sensitivity to initial points and poor robustness.

Method used

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  • Hybrid clustering method for simulating bifurcation and brain inspiration cognition
  • Hybrid clustering method for simulating bifurcation and brain inspiration cognition
  • Hybrid clustering method for simulating bifurcation and brain inspiration cognition

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Embodiment Construction

[0095] Below in conjunction with each embodiment, the scheme of the present invention is clearly and completely set forth, and the described embodiment is only the embodiment that the present invention is used for describing and illustrating but not all embodiments, based on these embodiments, people in the art The solutions obtained by technicians without creative work belong to the protection scope of the present invention.

[0096] see figure 1 , the urban transportation system is a dynamic open system with a complex large structure, and the massive traffic data is mainly reflected in the diversity of data types. For example, the collection of all data can be set to {x i}, the data type includes car trip data with geographical location information, the total number of data is set to N, i∈{1, 2,..., N}. Geographic location information can usually be expressed in the field by information such as longitude and latitude.

[0097] see figure 1 , the realization of intelligen...

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Abstract

The invention relates to a hybrid clustering method for simulating bifurcation and brain heuristic cognition. Initializing a cluster core, extracting distribution characteristics of data points through combinatorial optimization clustering, and automatically obtaining the gravity center of the data points from a global perspective, namely the initial cluster core; a cognitive technology of brain excitation is introduced, and a selective attention mechanism is introduced, so that attention is focused in a middle region of a cluster kernel. And solving the established QUBO model through a quantum heuristic algorithm. Iterations are repeated until convergence is achieved and the clustering result is kept unchanged.

Description

technical field [0001] The present invention mainly relates to the technical field of brain-inspired computing and control, more precisely, relates to a hybrid clustering method combining simulated bifurcation and brain-inspired cognition. Background technique [0002] With the deepening of the urbanization process, problems such as difficulty in maintaining the resource dependence model, intensified environmental problems, insufficient potential for sustainable economic development, and simplification of urban planning and construction models have become increasingly prominent. Therefore, urban revitalization requires a strong and intelligent brain to participate in the adjustment of urban metabolism. A typical problem is increased traffic congestion. While urbanization has brought modernization in recent years, it has also caused key problems such as traffic congestion, parking conflicts, and tidal traffic phenomena. Therefore, cities need a smarter brain to form a smart...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06V10/762
CPCG06F18/23
Inventor 方波
Owner 上海图灵智算量子科技有限公司
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