CN-121996981-A - Complex system dynamic modeling and flow control method based on C-topological structure

Abstract

The invention discloses a complex system dynamic modeling and flow control method and system based on a C-topological structure, and relates to the technical field of complex system modeling and intelligent information processing. The method comprises the steps of obtaining state data of a complex system unit, constructing a C-topology adjacent structure, executing dimensional change according to the system state to form a dynamic dimensional space, calculating and updating a state vector and a global vector field in the dynamic dimensional space, executing liquidity evolution on the C-topology structure by taking the vector field as a drive to realize dynamic conduction and convergence of information, energy, resources, probability or causality, and finally outputting the system state, prediction information or control instructions. The invention organically fuses the C-topological structure, the dimensional dynamic transformation, the vector field evolution and the mobility driving to form a unified bottom processing framework suitable for various complex systems, has the advantages of strong structural self-adaption, high modeling precision, wide universality, strong expansibility and the like, and can be widely applied to the fields of intelligent decision making, dynamic prediction, intelligent control, network optimization, artificial intelligence and the like.

Inventors

• JU ZHENG

Assignees

• 鞠正

Dates

Publication Date

20260508

Application Date

20260211

Claims (8)

1. 1. The complex system dynamic processing method based on the C-topological structure is characterized by comprising the following steps of: Acquiring state data of a plurality of units in a complex system, constructing a C-topology adjacent structure, and defining neighborhood relations, connection strength and boundary constraint among the units; Performing dimension change processing according to the current running state of the system, including dimension lifting, dimension compression or manifold projection, so as to form a dynamic dimension space matched with the system state; calculating state vectors corresponding to all units in a dynamic dimension space, updating a global vector field in real time, and representing the motion trend, action strength and association relation of the system units by vector directions and amplitude values; The global vector field is used as a driving mechanism, and the mobility evolution is executed on the C-topology adjacent structure, so that the dynamic conduction, diffusion and convergence of information, energy, resources, probability or causal relation in the system are realized; And outputting a system state identification result, prediction information or a control instruction according to the liquidity evolution result.
2. 2. The method of claim 1, wherein the C-topology adjacency structure supports dynamic addition and deletion of nodes, dynamic adjustment of connection relationships, and structure adaptive reconstruction.
3. 3. The method of claim 1, wherein the dimensionality variation process maintains a topology invariant of the C-topology, guaranteeing modeling stability.
4. 4. The method of claim 1, wherein the state vector comprises at least one of a trend vector, an intensity vector, a weight vector, and a correlation vector.
5. 5. The method of claim 1, wherein the mobility evolution employs an iterative update mechanism until a system state reaches a stable condition or a preset target threshold.
6. 6. The method of claim 1, wherein the method is applicable to artificial intelligence models, dynamic prediction systems, intelligent control systems, network optimization systems, and data processing systems.
7. 7. A complex system dynamic processing system based on a C-topology, comprising: the topology construction module is used for acquiring complex system unit data and constructing a C-topology adjacent structure; The dimension transformation module is used for executing dimension transformation processing and generating a dynamic dimension space; the vector field calculation module is used for calculating and updating the state vector and the global vector field; The mobility evolution module is used for driving the iterative evolution of the mobility of the system on the C-topological structure; and the output module is used for outputting the system state, the prediction result or the control instruction.
8. 8. A computer readable storage medium storing a computer program, which when executed by a processor implements the method of any one of claims 1-6.

Description

Complex system dynamic modeling and flow control method based on C-topological structure Technical Field The invention relates to the technical field of complex system dynamic modeling and flow control. Background In various complex systems such as artificial intelligence, industrial control, network communication, financial systems, smart cities and the like, the system structure has the characteristics of dynamics, openness and Gao Weixing. The traditional modeling method is mainly described by adopting a fixed dimension and a fixed topological structure, is difficult to adaptively match with the structural change and state evolution of the system, and meanwhile, lacks a unified expression mechanism for the internal trend, the conduction relation and the global flow of the system, so that the model has weak generalization capability, low prediction precision and poor control robustness. The prior art fails to organically integrate a topological structure, dimension dynamic transformation, vector field driving and system fluidity, and cannot form a bottom unified processing framework applicable to various complex systems. Therefore, a general modeling and control scheme capable of dynamically adapting to structural changes, supporting dimension adaptive adjustment, and quantitatively describing system trend and flow rule is needed. Object of the Invention Aiming at the defects existing in the prior art, the invention provides a complex system dynamic modeling and flow control method and system based on a C-topological structure, so as to realize unified modeling and efficient processing of complex system structure, dimension, trend and mobility and improve the accuracy and universality of complex system analysis, prediction and control. Technical proposal The invention discloses a complex system dynamic processing method based on a C-topological structure, which comprises the following steps: Acquiring state data of a plurality of units in a complex system, constructing a C-topology adjacent structure, and defining neighborhood relations, connection strength and boundary constraint among the units; Performing dimension change processing according to the current running state of the system, including dimension lifting, dimension compression or manifold projection, so as to form a dynamic dimension space matched with the system state; calculating state vectors corresponding to all units in a dynamic dimension space, updating a global vector field in real time, and representing the motion trend, action strength and association relation of the system units by vector directions and amplitude values; The global vector field is used as a driving mechanism, and the mobility evolution is executed on the C-topology adjacent structure, so that the dynamic conduction, diffusion and convergence of information, energy, resources, probability or causal relation in the system are realized; And outputting a system state identification result, prediction information or a control instruction according to the liquidity evolution result. Further, the C-topology adjacent structure supports the dynamic addition and deletion of nodes, the dynamic adjustment of connection relations and the self-adaptive reconstruction of the structure. Further, the dimensionality change process keeps the topological invariant of the C-topological structure, and modeling stability is guaranteed. Further, the state vector includes at least one of a trend vector, an intensity vector, a weight vector, and a correlation vector. Further, the fluidity evolution adopts an iterative updating mechanism until the system state reaches a stable condition or a preset target threshold. Further, the method is applicable to artificial intelligent models, dynamic prediction systems, intelligent control systems, network optimization systems and data processing systems. The invention also provides a complex system dynamic processing system based on the C-topological structure, which comprises: the topology construction module is used for acquiring complex system unit data and constructing a C-topology adjacent structure; The dimension transformation module is used for executing dimension transformation processing and generating a dynamic dimension space; the vector field calculation module is used for calculating and updating the state vector and the global vector field; The mobility evolution module is used for driving the iterative evolution of the mobility of the system on the C-topological structure; and the output module is used for outputting the system state, the prediction result or the control instruction. The invention also provides a computer readable storage medium storing a computer program which when executed by a processor implements any of the methods described above. Advantageous effects Compared with the prior art, the invention has the following remarkable beneficial effects: 1. The invention takes the C-topological structure as the bottom layer co