5results about How to "Improve evolution effect" patented technology

The invention discloses a regional multi-microgrid cluster-oriented collaborative operation system, which relates to the technical field of power system dispatching and control, and comprises an asynchronous sensing fusion module, an asynchronous receiving and time axis reconstruction module, a time axis reconstruction module and a time axis reconstruction module, which are used for carrying out asynchronous receiving and time axis reconstruction on operation state data reported by a plurality of microgrid nodes; the credibility level is determined based on the communication link state and the data integrity, and weighted merging is carried out in the same time window according to the credibility level to form a unified state view; and the prediction difference modeling module is used for extracting state change characteristics among micro-grid nodes based on the state view, determining state offset information and a historical change boundary thereof, and taking the state offset information and the historical change boundary as numerical constraints of scheduling calculation. According to the system provided by the invention, through the asynchronous sensing fusion module, time axis reconstruction is realized on the basis of asynchronous data receiving, the credibility level of each piece of data is dynamically evaluated in combination with a communication link state and data integrity, and then weighted fusion is carried out in a unified time window.

The invention discloses an equestrian competition performance prediction system based on multi-modal monitoring, and relates to the technical field of equestrian sport monitoring and intelligent prediction. The system comprises an acquisition module, a processing module, a prediction module, a display module and a data closed-loop optimization mechanism. The acquisition module is used for acquiring horse video and physiological and environmental multi-modal data through multiple types of equipment; the processing module is used for realizing data fusion processing, gait behavior recognition and facial expression emotion evaluation; the prediction module outputs a competitive performance quantitative score and risk early warning based on a machine learning model; the display module provides a visual interaction interface; and the data closed-loop optimization mechanism realizes model iterative optimization through competition result return. According to the method, the problems of single monitoring dimension, data splitting, lack of prediction capability and the like in the prior art are solved, comprehensive perception of horse states and accurate prediction of competitive performance are realized, the scientific level of training management is improved, and the method has wide practical prospects and industrialization values.

This invention discloses a reconfigurable network security service construction system and method, belonging to the field of network security technology. The method specifically includes: acquiring network service intent and operational constraint information; generating a set of security invariants corresponding to the network service intent based on a pre-set threat semantic library; mapping the set of security invariants to a pre-built security service primitive library; generating multiple primitive chain candidate sets that satisfy the same security invariant; calculating the attack surface metric for each primitive chain candidate set based on network topology and operational environment information; determining the target security service function chain through multi-objective constraint solving, under the premise of satisfying the set of security invariants; and deploying the target security service function chain. This application enables bounded reconfiguration selection among multiple candidate service chains, enhancing the adaptability and evolutionary capability of security service construction.

The invention discloses a virtual sensor configuration optimization method and system for industrial soft measurement, and the method comprises the steps: generating a plurality of different initial virtual sensor configuration schemes based on a candidate physical sensor set of to-be-monitored equipment; for each virtual sensor configuration scheme, calculating a synthesis evaluation index, and determining an optimal synthesis index and an optimal configuration scheme; under any number of iterations, selecting, exchanging and mutating the virtual sensor configuration scheme, updating the virtual sensor configuration scheme, and determining a corresponding optimal synthesis index and an optimal configuration scheme; and outputting a corresponding optimal configuration scheme until the difference of the optimal synthesis indexes under adjacent iterations is smaller than a preset threshold value. According to the method, the configuration scheme is iteratively optimized by constructing the multi-dimensional synthesis evaluation indexes fusing the detection performance, the information efficiency, the cost complexity and the system robustness, and the optimization target of meeting the requirements of industrial soft measurement precision and stability is achieved.

This invention relates to the field of network security technology, specifically to an industrial control threat detection system based on an enhanced threat intelligence graph. The system includes: collecting and parsing multi-source industrial data to generate a feature stream; constructing a threat intelligence graph to identify entities and relationships; performing correlation reasoning and attack path prediction based on the graph structure; multi-agent collaborative allocation of defense tasks to implement blocking and isolation; and achieving closed-loop security control through result verification and feedback. This invention constructs a spatiotemporally correlated data stream by parsing industrial communication messages and extracting multi-dimensional features. Combined with a threat intelligence database, it achieves dynamic mapping of threat entities and attributes to form an evolutionary graph. Based on the graph topology, it performs path search and risk assessment to predict attack paths. Multi-agent collaborative decision-making is introduced to decompose and execute defense tasks in parallel, improving response efficiency. Closed-loop feedback verifies the results and updates the knowledge base, enabling adaptive optimization and continuous evolution of the defense system.