378 results about "Pheromone" patented technology

The invention relates to the technical field of autonomous navigation, in particular to an AUV (Autonomous Underwater Vehicle) multi-sensor fusion autonomous navigation system based on ant colony-particle swarm collaboration.The AUV multi-sensor fusion autonomous navigation system is characterized in that a sensor weight decision module constructs a pheromone matrix based on an ant colony algorithm, retrieves a mapping relation between historical errors and pheromone concentration in real time and dynamically generates a sensor priority sequence; adaptive weight distribution in a data conflict scene is realized; the dynamic path correction module is combined with a particle swarm algorithm and pheromone concentration gradient constraint to balance global path optimality and real-time obstacle avoidance requirements in optical camera obstacle deviation correction; and the closed-loop coupling module is used for converting sonar and geomagnetic residual errors into pheromone concentration correction values and confidence coefficient regulation factors by fusing residual error compensation and path tracking error feedback, so that an error traceability-weight calibration-path optimization closed loop is formed, sensor drift is inhibited, and the long-endurance navigation precision is improved.

The invention provides an intelligent message pushing method and system, and the method comprises the steps: collecting the social behavior data and personal attribute data of a user in a social network; dividing the users into a plurality of groups by using the social behavior data and the personal attribute data based on an ant colony algorithm; analyzing a social relation and an interaction mode among users in the group; collecting message resources in the social network, and classifying and labeling messages; performing collaborative filtering processing on the to-be-pushed message, determining a target user group, and generating a message recommendation list; and pushing the recommended message to users in the target user group according to a preset pushing strategy. The user social behavior data and the personal attribute data are converted into the ant feature vectors based on the ant colony algorithm, similar feature vector ants are gathered through pheromone updating and path selection mechanisms, different user groups are formed, the user group division accuracy is improved, and user requirements are more accurately grasped.

The invention relates to a multi-mobile-robot path planning method based on swarm intelligence, and belongs to the technical field of robot path planning. The method comprises the following steps: setting the size of a map, starting and target positions and colors of a robot, creating a preset grid map, and initializing an ant colony algorithm, a genetic algorithm and a pheromone system; iteratively searching paths for the mobile robots with different starting points at the same time through an ant colony algorithm; a genetic algorithm is used for optimizing the path, conflict detection and processing are carried out after the path is optimized, and it is ensured that the final path is free of conflicts; and when the maximum number of iterations is reached, outputting the shortest path that each robot arrives at the target node and no collision exists between the robots. According to the path planning method, unnecessary turning can be reduced, the convergence speed of path searching is obviously improved, robot conflicts can be avoided, and the actual requirements of multi-robot path planning are met.

The invention provides a path planning method and system based on HER-ACO, and belongs to the technical field of robot path planning. The method comprises the following steps: S1, acquiring an environment grid map, wherein the grid map comprises a starting point, a target point and obstacle distribution information; s2, introducing an HER algorithm to improve a traditional ant colony algorithm ACO, and searching a feasible path from a starting point to a target point in the grid map by using the improved ant colony algorithm as an initial planning path; the improvement comprises the following steps: introducing an HER thought and a dynamic pheromone volatilization mechanism; increasing a direction weight factor, a neighborhood obstacle factor and a future obstacle factor; and S3, smoothing the initial planning path based on the feasibility check of the linear path, removing redundant intermediate nodes, and outputting a final planning path. A simulation result shows that the scheme has remarkable advantages in a complex environment, particularly has excellent performance in the aspects of path quality and convergence speed, and is suitable for scenes such as robot navigation and concrete robot path planning.

The invention relates to the technical field of machine path planning, and discloses an island ant colony path planning method for an unmanned trolley, which comprises the following steps: after generating a grid map, decomposing global path search into path exploration between adjacent islands; non-uniform pheromone initialization is adopted between adjacent islands, local paths between the adjacent islands are searched respectively, and the position of a next grid is selected in the searching process by combining an improved node transition probability with a heuristic function and pheromone concentration; and when global pheromone distribution is updated, an optimal path is rewarded, and a worst path is punished. And combining the local paths of the island pairs to obtain global paths, and selecting the global path with the shortest length as the optimal driving path. According to the method, a segmented island strategy is adopted, the complexity of single search is reduced, the early random probing process is shortened through non-uniform initialization pheromones, the convergence speed is increased, the number of deadlock ants is effectively reduced, and the precision, convergence and stability of path planning are improved.

The invention relates to an ocean platform pipeline wiring method and system based on an ant colony optimization algorithm, and a medium, and belongs to the technical field of intelligent optimization algorithms. Comprising the following steps: S11, environment modeling: discretizing a three-dimensional space of an ocean platform into a grid model, marking an obstacle region and a feasible region, and calculating a grid node energy value; s12, parameter initialization: constructing a heuristic information matrix based on pipeline inlet and outlet coordinates and equipment parameters, and determining a node transition probability by the matrix through a direction probability allocation strategy and a distance sensitive function; s13, path optimization: generating candidate paths through dynamic smooth search, local pheromone adaptive adjustment and collaborative ecological niche search, and updating pheromones; and S14, constraint verification and result output: verifying whether the path meets the engineering constraint or not, and outputting the three-dimensional coordinate, length and bend number of the optimal pipeline path after iterative optimization. According to the method, efficient, safe and economical wiring of the offshore platform pipeline is achieved.

The invention is suitable for the technical field of crowd simulation and emergency evacuation, and provides an emotional infection and social force model coupling-based crowd evacuation method, which comprises the following steps of: constructing an emotional infection model based on an SEIRS framework, dividing individual emotional states into a susceptible state, an exposed state, an infected state and a recovery state, the infection rate and the recovery rate are dynamically adjusted through a feedback function; establishing a social force model, and embedding an emotion value into calculation of a target driving force and a repulsive force between individuals to realize real-time adjustment of the motion behavior by the emotion; global path planning and an ant colony pheromone mechanism are fused, a density perception cost function and pheromone guiding force are introduced, and dynamic blockage avoidance is achieved; a bidirectional feedback mechanism is designed, and local path reconstruction is triggered when congestion is detected. According to the method, bidirectional coupling of emotion propagation and behavior decision is realized, the authenticity and adaptability of evacuation simulation are improved, and a scientific basis can be provided for emergency management and evacuation strategy optimization in public places.

The embodiment of the invention provides a mobile communication PCI (Peripheral Component Interconnect) decision-making method and device based on an improved ant colony algorithm, and the method comprises the steps: obtaining MR (Measurement Report) data of a base station and a real-time network state; the base station MR measurement report data comprises a conflict matrix, a confusion matrix and a modulo 3 interference matrix; extracting a network topology feature vector according to the MR measurement report data of the base station; according to the network topology feature vector and the real-time network state, obtaining a heuristic weight and a pheromone volatilization rate parameter; based on an ant colony algorithm, obtaining an improved ant colony algorithm according to the heuristic weight and the pheromone occurrence rate parameter; based on the quantum revolving door, determining a three-level objective function according to the conflict matrix, the confusion matrix and the modulo 3 interference matrix; and based on an improved ant colony algorithm, generating an optimal PCI allocation scheme according to the conflict matrix, the confusion matrix, the modulo 3 interference matrix, the three-level objective function and a preset constraint condition. The problem of optimization target imbalance is solved, and the reliability of the PCI decision method can be ensured.

The invention belongs to the related technical field of underwater gravity matching navigation, and discloses a submersible vehicle route planning method, application and equipment based on an improved ant colony algorithm, and the method comprises the steps: (1) constructing an adaptability index matrix based on gravity adaptability characteristics, and carrying out the normalization and information entropy weighting to obtain comprehensive adaptability characteristics; (2) constructing an environment grid model according to the comprehensive adaptability characteristics; (3) taking a free space as a search area, carrying out path search based on an environment grating model and an improved ant colony algorithm, and further obtaining a track node sequence meeting the adaptability constraint, the path continuity and the shortest path target to complete track planning; wherein the improved ant colony algorithm is obtained by introducing an elite ant strategy to enhance the globally optimal path pheromone of the ant colony algorithm and adaptively adjusting a pheromone concentration factor, a heuristic function factor and a pheromone volatilization coefficient in the ant colony algorithm by using a particle swarm optimization algorithm. The search efficiency and the automation degree are improved.

The invention discloses an education content recommendation method and system based on group intelligence, and the method comprises the steps: constructing a user dynamic cognition knowledge graph, and carrying out the dynamic attenuation of the memory intensity attribute of a knowledge point node based on a cognition forgetting model in combination with the memory stability; defining utilization pheromones on edges of the knowledge graph, and strategically injecting exploration pheromones according to forgetting states of users or knowledge breadth indexes; guiding a swarm intelligence algorithm to construct a learning path according to a rule jointly influenced by bimodal pheromones; and finally determining an optimal path and generating recommendation. According to the method, accurate intervention on a learning process and intelligent guidance on knowledge exploration are realized through deep fusion of a recognition scientific model and a swarm intelligence algorithm of bimodal pheromones, the learning stability is remarkably improved, information cocoon houses are effectively broken, and the interpretability of recommendation is enhanced through path intention analysis.

The invention provides a die-casting robot micro-spraying path planning and control method and system, and relates to the technical field of path planning, and the method comprises the steps: obtaining three-dimensional data of a workpiece to extract feature point information, calculating spraying accessibility data, carrying out path planning through employing an ant colony algorithm, and dynamically adjusting a search weight through employing a self-adaptive pheromone updating strategy. And an optimal spraying path sequence is generated, and track smooth transition is realized through track interpolation and optimization. The spraying quality and uniformity can be improved, waste of spraying materials is reduced, and the stability and accuracy of robot movement are improved.

The invention relates to the technical field of scenic spot route planning, and provides a scenic spot global collaborative touring planning method and system, and the method comprises the steps: constructing a scenic spot environment depth model, and deploying an ant colony algorithm on the constructed scenic spot environment depth model through key parameter initialization and tabu table initialization; path selection is carried out by executing ant colony movement, and real-time information updating and ant colony collaborative obstacle avoidance are carried out in the movement process; constructing a pheromone updating rule to update global pheromones, and judging and outputting an optimal path through iterative convergence; and performing multi-dimensional verification on the output optimal path, and generating a personalized touring scheme according to the path passing the verification. According to the invention, collaborative planning and dynamic optimization of the scenic spot sightseeing path are realized, the sightseeing efficiency of tourists is effectively improved, the queuing time is reduced, the information interaction comprehensiveness is enhanced, and the overall operation efficiency and tourist experience of the scenic spot are remarkably improved.

The invention provides a mobile robot path planning method based on an improved ant colony algorithm, and relates to the technical field of robot path planning, and the method is technically characterized in that the method comprises the following steps: carrying out environment modeling by adopting a grid method, and constructing a multi-target performance evaluation function; an improved ant colony algorithm is adopted to carry out optimal path search, path planning is carried out on a grid map from a starting node to a target node, and the improvement of the ant colony algorithm comprises the steps of distributing pheromone concentration by adopting a non-uniform initialization method; improving a state transition rule; differentiating a pheromone updating strategy; and smoothing the path. An initial pheromone distribution optimization strategy is introduced, heuristic information based on a triangular inequality, a steering angle suppression function and a state transition rule of artificial potential field force are combined, a differential pheromone updating strategy based on a multi-target performance evaluation index is adopted, and finally a planned path is smoothed. Therefore, the convergence speed, the path quality and the environment adaptability of the algorithm are remarkably improved.

The invention discloses a cooperative control method for a multi-domain unmanned system. The method comprises the following steps: acquiring an original sensor sequence and a late message set; according to the original sensor sequence, calculating a dominant function and anti-fact regret to obtain a value signal; generating a time delay weight according to the late message set; constructing a space-time source item based on the value signal and the time delay weight; constructing a neural pheromone field by solving partial differential equation dynamics by using space-time source items and pheromone field parameters; under the guidance of the neural pheromone field, sampling to generate a candidate path set; and selecting a cooperative path from the candidate path set for the unmanned system to execute. According to the method, the problems of value characterization and timeliness under asynchronous communication are solved, deep coupling of a decision strategy and a physical model is realized, and the robustness and the adaptive ability of collaborative decision are improved.

The invention discloses an LED lamp energy consumption optimization control method and system adopting an ant colony algorithm, and particularly relates to the field of LED lamp energy consumption optimization control, and the method comprises the steps: constructing a path network model of a multi-node illumination region, obtaining the movement track information of a user in the illumination region in real time through a collection module of LED illumination equipment, and generating path use frequency data; and performing pheromone optimization enhancement processing on the path use frequency based on an ant colony algorithm, and driving an existing illumination control module to select an LED lamp corresponding to the current high-frequency path area to perform activation response. By introducing pheromone attenuation control, a negative pheromone suppression mechanism and a virtual individual tentative activation strategy into a path frequency atlas, outdated paths are identified and suppressed, and new user behavior paths are detected and enhanced, so that time sequence sensitive scheduling of lighting resources and real-time optimal updating of energy consumption configuration are realized, and the optimal scheduling efficiency is improved. And the response capability and the energy-saving efficiency of the system to behavior transition are improved.

The invention provides an unmanned aerial vehicle cluster weapon target collaborative allocation method and system under space-time constraint, and the method comprises the steps: defining a collaborative allocation object, constructing a collaborative combat scene target function, defining a collaborative combat scene constraint condition, and finally solving the target function through employing a multi-gene population parallel ant colony algorithm, encoding the weapon set, the target set and the unmanned aerial vehicle set into a weapon gene sequence, a target gene sequence and an unmanned aerial vehicle gene sequence respectively to generate an initial population, and performing staged joint optimization by fusing a pheromone guiding mechanism of an ant colony algorithm and crossover mutation operation of a genetic algorithm, the optimal cooperative allocation scheme is searched when the constraint condition is satisfied, the unmanned aerial vehicle task allocation result can be better obtained and optimized through the cooperative allocation mode, and the unmanned aerial vehicle cooperative allocation efficiency is improved.

The invention relates to the technical field of industrial network communication, in particular to an SDN (Software Defined Network) industrial network routing method based on deep traffic classification and dynamic pheromone optimization. According to the method, an SMOTE algorithm is improved, a target sub-region is selected through an adaptive boundary to perform oversampling to balance sample data, the problem of flow imbalance of the SDN multi-access interconnection architecture is solved, meanwhile, a CNN-LSTM model fused with an attention mechanism is established, and depth feature extraction is performed on samples after the samples are balanced so as to meet dynamic features of the flow in a short sequence.

The application relates to a power substation unmanned aerial vehicle (UAV) three-dimensional path planning method based on an improved ant colony algorithm, which comprises the following steps: generating a power UAV inspection three-dimensional environment model and performing adaptive grid division; initializing the ant colony in the power UAV inspection three-dimensional environment model after grid division to perform path searching; each ant individual in the ant colony selects a next node according to a dynamic transfer probability calculation model, the ant individual determines an actually moved next node through a variable step length search behavior, and records path information from a starting point to an ending point of each ant individual; when all the ant individuals reach the ending point, the optimal ant individual of this iteration is screened and a worker ant foraging behavior is performed, and pheromone concentration of each path in the space is updated; iteration is repeated until a preset iteration number is reached, and the path with the highest pheromone concentration is selected as a final path of the UAV.

The invention relates to the field of data processing, in particular to an automatic optimization method for a laser drilling path of a circuit board, and introduces a dual-pheromone ant colony algorithm to overcome the defect that a traditional algorithm only pursues a shortest path but neglects a heat accumulation effect. Two independent pheromones of path length and heat distribution are constructed, a hole site neighborhood heat influence factor and a path global heat entropy are defined to quantify the heat dissipation performance, and an algorithm is guided to consider the distance and heat during path selection, so that the processing efficiency and heat control are effectively balanced, the algorithm is prevented from falling into a suboptimal solution due to local heat concentration, and the processing efficiency is improved. And finally, a comprehensive optimal path considering the path length and the heat dissipation effect is found. According to the method, the path length pheromone and the heat distribution pheromone are constructed and independently updated by adopting the dual-pheromone ant colony algorithm, so that the drilling path length and heat control are balanced, and the optimal solution is found.

The invention relates to a storage AGV path planning method based on a hierarchical collaborative ant colony algorithm, belongs to the field of storage robot path planning, and aims to solve the problem of realizing better path planning in a complex storage environment. The method comprises the following steps: constructing an environment model of intelligent storage based on a grid method; an ant colony algorithm is improved on the basis of a hierarchical cooperative system, an ant colony is divided into scout ants responsible for exploration and foraging ants responsible for optimization, a heuristic function comprehensively considering the distance, the corner and a new exploration area is constructed, an improved pheromone updating strategy based on ant layering and the pheromone concentration on a self-adaptive volatilization factor updating path are adopted, and a new exploration area is obtained. The transfer strategy fuses three modes of random selection, probability selection and determinacy selection, and finally an improved ant colony algorithm is obtained; an improved algorithm is utilized to plan a global path for each AGV, and secondary optimization is performed in a targeted manner, so that the path length is shorter, and the smoothness is higher. And an effective solution is provided for AGV path planning in a complex storage environment.

The invention provides a multi-unmanned-aerial-vehicle cooperative path planning method, device and system and electronic equipment, relates to the technical field of multi-unmanned-aerial-vehicle path planning, and realizes global guidance of a multi-unmanned-aerial-vehicle scene by establishing closed-loop feedback of path optimization-pheromone dynamic attenuation characteristics-pheromone updating. By quantifying the collision cost and individual contribution in the path updating process, the conflict resolution logic corresponding to the two-dimensional decision index is embedded into the final planning path, and the problems of multi-machine collision and airspace resource competition under the distributed architecture can be effectively solved. Finally, precision improvement (conflict-free and global optimum) and efficiency improvement (efficient search and rapid iteration) of multi-unmanned aerial vehicle cooperative path planning are realized, and task execution requirements in a complex environment are met.

To provide a sustained release pheromone preparation that is easily installed and stably retained at an installation site.SOLUTION: Provided is a sustained release pheromone preparation 10 composed of at least one polymeric capillary or polymeric thin rod containing a pheromone substance 3 with each end 2 sealed. In the sustained release pheromone preparation 10, (a) the polymeric capillary or thin rod is bent into an arc and crossed to form, in front view, a single closed space 6 while remaining uncrossed in side view, (b) a curvature radius R of the bent and crossed arc is 6 to 17 mm, (c) a straight distance D from an apex of the bent and formed arc to an intersection 5 is 25 to 65 mm, and (d) in front view, when the intersection 5 is opened to provide a separation distance G of 20 mm, the repulsive force is 0.5 N or greater.SELECTED DRAWING: Figure 1

The invention discloses an application and a method for preventing and controlling longhorn beetles by using a disotropic agent, and belongs to the technical field of prevention and control of agricultural pest longhorn beetles. The component of the lysimachia christinae disruption agent is trans-9-tetradecene-2, 2-difluoroacetate, and the disruption effect of the lysimachia christinae disruption agent is superior to that of a lysimachia christinae disruption pheromone disruption substance under the same dosage. According to the isotropic agent, 100-200 mg of trans-9-tetradecene-2, 2-difluoroacetate is dissolved in liquid chlorinated paraffin and added into a polyvinyl chloride (PVC) capillary tube to be prepared into isotropic filaments, 30-60 isotropic filaments are arranged per mu in the using process, and the result shows that the field lasting period of the isotropic filaments is longer than 3 months, and the isotropic rate is larger than 80%. The isotropic agent disclosed by the invention can be used for remarkably interfering the mating of male and female jettilonghorn beetles, is safe to the environment and natural enemies, is simple to operate, can be used for preventing and treating the pests in a large area, and has important significance on comprehensive treatment of the jettilonghorn beetles.

The present application relates to the technical field of large model parameter adjustment, in particular to a large model fine-tuning method based on ant colony dynamic mechanism, on the basis of the existing LoRA+MoE method, first, an ACO optimizer is constructed based on the adaptive characteristics of the ant colony optimization algorithm, in each training round, the hyperparameters including rank, scaling factor and number of selected experts are adaptively adjusted according to the feature complexity of each layer of the pre-trained large model, and the pheromone concentration of the ant colony optimization algorithm is updated with the performance index of the model as the guide, realizing intelligent optimization of parameter configuration, so that the fine-tuned large model can automatically adjust the rank configuration according to the feature complexity to adapt to different task requirements; and, the present application improves the existing gating network, constructs an ACO-MoE gating network, allocates experts with the ant colony optimization algorithm, and further constructs a load balancing loss based on the usage rate of the experts to avoid the problem of model performance degradation caused by unbalanced expert load.

The invention provides an intelligent terminal outdoor cooperation method and system based on an ant colony algorithm. The method comprises the following steps: acquiring outdoor navigation data, processing the outdoor navigation data into navigation data fragments, and distributing the navigation data fragments to a plurality of intelligent terminals; screening out a main relay node; when entering the target area, determining the intelligent terminal as main navigation equipment, and controlling the gas intelligent terminal to enter a low-power-consumption mode; summarizing the navigation data fragments stored in the intelligent terminals through the main relay node, forwarding the summarized navigation data fragments to the main navigation equipment, and splicing to generate complete navigation data of the target area; and the main navigation equipment obtains and generates navigation information and synchronizes the navigation information to each intelligent terminal through the main relay node. Through pheromone dynamic iteration of the ant colony algorithm and a distributed decision-making mechanism, efficient cooperation of multiple intelligent terminals on division storage and group collaborative splicing is realized, and on the premise of guaranteeing complete navigation data splicing precision and real-time navigation reliability, the overall energy consumption is remarkably reduced, and the equipment endurance is prolonged.

The present disclosure relates to a data analysis method, device, storage medium and electronic equipment, so as to reduce the calculation amount of data analysis request and improve the data analysis efficiency. The method comprises: receiving a data analysis request; in response to the data analysis request, updating the data analysis result of a pre-stored first business model according to the changed data corresponding to the target pheromone, to obtain the updated data analysis result corresponding to the first business model, the target pheromone being the pheromone recording the data change in response to the business data change, the first business model being a business model including the target pheromone, and the business data change including changing the data in part of the pheromones; and outputting at least the updated data analysis result corresponding to the first business model.

This invention discloses a device and method for the propagation, release, and rewilding training of large yellow croaker fry, relating to the field of marine biological resource conservation technology. The device includes: a water tank containing water, with multiple artificial reefs placed inside; a light source positioned above the water tank; multiple wave-making pumps evenly distributed along one side of the inner wall of the water tank; a release structure for releasing predator pheromones into the water tank; a camera mounted on the inner wall of the water tank; and a controller electrically connected to the camera, light source, and wave-making pumps. The camera collects behavioral characteristic information of the large yellow croaker during rewilding training and sends this information to the controller. A fish behavior analysis system comprehensively analyzes the swimming and reef usage of the large yellow croaker fry in the water tank to determine the effectiveness of the rewilding training. The advantages of this invention are enhanced ability of large yellow croaker fry to adapt to the marine environment and improved survival rate of released fry.

The application provides a ship path planning method and device for a near-shore environment and electronic equipment, and belongs to the technical field of artificial intelligence. The method comprises the following steps: rasterizing a near-shore environment image to obtain a sailing space model; setting initial parameters of an improved potential field-ant colony algorithm and initializing a path taboo table, then determining path point pheromone distribution and a combined potential field force, calculating a transfer probability of an ant transferring to other nodes to determine a next node, and updating the taboo table; after an ant traverses all nodes to reach a target point, updating the pheromone distribution and recording a traversal path; after all ants traverse all nodes, obtaining traversal paths of all ants and determining an optimal path. The application improves the potential field-ant colony algorithm, introduces potential field information, and dynamically adjusts a heuristic information function; adjusts a path selection probability optimization algorithm structure; and considers the sailing characteristics of a ship itself to ensure the demand for autonomous sailing of the ship.

The invention discloses an air-ground robot mountainous area path planning method based on a multi-strategy improved ant colony algorithm. The method comprises the following steps: establishing a mountainous area three-dimensional environment model; an air-ground robot is initialized; non-uniform initial pheromones in normal distribution are generated; designing a heuristic function considering the air-ground bimodal and the motion direction; constructing a state transition probability which simultaneously considers motion smoothness, safety and grid importance; perfecting a pheromone updating mechanism; and a multi-strategy improved ant colony algorithm is adopted to complete path planning and obtain an optimal path. By using the method, the planning efficiency of the air-ground robot can be effectively improved, and the feasibility and practicability of path planning are enhanced. The open space robot mountainous area path planning method based on the multi-strategy improved ant colony algorithm can be widely applied to the technical field of robot path planning.

A method, system, device, and medium for delay-tolerant network caching based on the minimax ant colony algorithm are disclosed. The method includes: first, classifying information; when a new message arrives, if the cache is not full, the new message is allowed into the cache; otherwise, the total pheromone concentration of the new message determines whether to allow it into the cache. Regardless of whether the new message is allowed into the cache, the pheromone concentration of similar messages in the cache is updated, and the updated pheromone concentration of similar messages is compared with a given pheromone concentration range. If the pheromone concentration does not exceed the range, caching ends; if it exceeds the range, the upper or lower limit of the given pheromone concentration range is used. The system, device, and medium are used to implement a delay-tolerant network caching method based on the minimax ant colony algorithm. This invention introduces the concept of pheromone concentration to determine whether the total pheromone concentration of a new message entering the cache is minimum, thus deciding whether to discard the new message. This has the characteristics of improving the message arrival rate in delay-tolerant networks and reducing network overhead.