6 results about "Artificial immune algorithm" patented technology

The application discloses a low-orbit satellite congestion control method based on an artificial immune algorithm, which comprises the following steps: a satellite node periodically monitors the occupancy rate of an output queue in each direction, when congestion is detected, the satellite generates a congestion warning packet as an antigen and sends it to a directly adjacent node; the adjacent node receiving the congestion warning packet finds a matching item of an affected destination node in a historical memory cell library through the similarity between the current scene and the historical record, as the routing strategy of the destination node; when no match is found, the optimal bypass strategy is determined based on the direction of the congestion link and the position information of the satellite; the satellite comprehensively evaluates the generated control strategy within a time window; when the affinity continues to fail to reach a threshold, the satellite continuously monitors the queue occupancy rate change trend, and when it is found that a continuous multiple periods show an upward trend, the shunt proportion is increased; the application improves the response speed of the congestion control, network performance and service quality.

The application discloses a coal and gas outburst danger prediction method based on HDAIA, and relates to the field of intelligent coal mine gas sequence prediction.The application predicts the coal and gas outburst danger by using an artificial immune algorithm, introduces Hamming distance to calculate the affinity between antibodies and antigens in AIA and between antibodies, improves the coal and gas outburst danger prediction, uses an interpolation function to construct a correlation matrix of the coal and gas outburst indexes in the algorithm, and uses the Hamming distance to quickly scale the affinity between antibody strings, calculates the minimum Hamming distance, and thus obtains the prediction result with the maximum accuracy.The application effectively predicts the coal and gas outburst danger, has beneficial effects on the prevention and treatment of the coal and gas outburst disaster, and can be used for guiding the coal mine engineering practice.

The invention discloses a cleaning robot autonomous path planning control method based on deep learning, and the method comprises the following steps: obtaining the pose and obstacle information of a cleaning robot, and generating a data packet containing obstacle distribution and blocked coordinates when detecting that a path is blocked; activating a reconnaissance granulocyte antibody family, generating a plurality of micro-paths constrained by curvature, evaluating the accessibility, and outputting safety direction information; encoding the path data and the safety direction to form an antigen vector, and generating a candidate antibody set; executing cloning, variation, concentration inhibition and negative selection according to the matching degree, and screening an optimal antibody path as a repair segment for output; and performing phagocytic recovery on the invalid antibody and updating variation prior, and performing closed-loop splicing on the repair path and the original path to generate an executable track. According to the invention, a reconnaissance granulocyte antibody family and a phagocytosis-recovery mechanism are introduced into an artificial immune algorithm, so that the path continuity and the operation stability in a complex environment are remarkably improved.

The application relates to a zero-trust medical network security immune defense method and system. The method comprises the following steps: constructing an abnormal behavior feature database based on an artificial immune system; dynamically adjusting vaccine resources distributed to a subserver by a central server based on the abnormal behavior feature database and a Lagrange optimization method; and optimizing attack detection rules of a firewall based on the vaccine resources and an artificial immune algorithm, and performing network attack defense by using the attack detection rules. That is to say, by constructing a fine-grained network abnormal behavior feature database, introducing a dynamic vaccine distribution mechanism to distribute detectors to all terminal nodes in a medical internal network, and using an artificial immune algorithm for abnormal detection, strict behavior monitoring is realized for each access, attack behaviors are discovered, blocked and traced in a timely manner, and the above-mentioned technologies can cope with network security problems in the current medical network environment and make up for the disadvantages of traditional medical network security boundary protection.

The invention discloses an AMI communication network security situation assessment method, and relates to the technical field of network security. Comprising the following steps: filling acquired power information missing data by utilizing a knn algorithm; acquiring safety observation data in the power network by adopting a counter algorithm; describing a change process of a network security state through a Markov model, and calculating a transition probability matrix between different states by using an artificial immune algorithm; correcting the state transition matrix by utilizing the situation assessment error; probabilities of different safety states at different moments are calculated, and a safety situation assessment value is finally obtained by combining the risk loss vector. According to the method, the network security situation of the AMI system can be evaluated, related security defects in the system can be accurately found, the security state of the power grid can be mastered, and intelligent electric power security operation and maintenance can be constructed.

The embodiment of the specification provides an embryo electronic cell array electronic cell granularity optimization method and device, wherein the method comprises the following steps: acquiring an electronic cell granularity parameter, and establishing an embryo electronic cell array reliability analysis model and an intracellular auxiliary resource proportion analysis model based on the electronic cell granularity parameter; based on the embryo electronic cell array reliability analysis model and the intracellular auxiliary resource proportion analysis model, an electronic cell granularity optimization model is established with the maximum embryo electronic cell array reliability as the target; a self-adaptive immune operator is determined according to the algorithm iteration number and the population quality, so as to determine an improved self-adaptive artificial immune algorithm, and the improved self-adaptive artificial immune algorithm is used to realize the solution of the embryo electronic cell array electronic cell granularity optimization according to the electronic cell granularity optimization model.