2 results about "Self-stabilization" patented technology

This invention discloses a consensus decision-making method, system, and storage medium based on distributed feedback, belonging to the field of internet collaborative decision-making technology. The method constructs a fully implicit autonomous decision-making system, including: collecting feedback data from network nodes on a target object; weighting the feedback data based on the implicit real-time reputation weights of the nodes to generate a consensus quantification result; silently updating the system state of the target object according to the consensus quantification result; and dynamically and silently adjusting the implicit reputation weights of the nodes in the background according to the state update result. This invention severs the direct causal chain between the perceptible behavior of nodes and system feedback, encapsulating consensus decision-making as a background environmental law unknown to the nodes. This fundamentally reduces the motivation for strategic gaming and malicious attacks by nodes, thereby improving the system's anti-attack capability, stability, and decision quality. It achieves game-resistant, self-stabilizing, and sustainably optimizing group decision-making, effectively solving governance problems such as information overload and the proliferation of low-quality content in large-scale digital communities.

The invention discloses a time sequence anomaly detection method based on multi-window clustering symbolization, and relates to the technical field of anomaly detection, and the method comprises the following steps: building a cross-window feature drift capture baseline, segmenting an input time sequence according to sliding time windows, extracting the feature distribution of each time window, and building a continuous mapping model; and extracting the transition gradient of the clustering centroid according to the characteristic distribution change between the adjacent time windows, and generating a dynamic drift monitoring matrix for describing the dynamic change of the centroid. Through cross-window feature drift capture and centroid synchronous remapping, space-time continuous updating of symbol mapping is realized, faults and failures caused by centroid mutation are eliminated, and the accuracy and stability of anomaly detection are improved; and through abnormal mapping freezing control and symbol consistency closed loop, a self-healing regulation and control mechanism is constructed, so that the system has self-recovery and self-stabilization capabilities, and continuity, reliability and robustness of a detection process are ensured.