31 results about "Artificial Ants" patented technology

The application provides a method and system for controlling flight based on a cellular network. The method comprises the following steps: receiving flight waypoint coordinate information, neighboringpoint range information, and communication base station location information; connecting the aircraft through an enhanced machine type communication cellular network, and obtaining the coverage of the enhanced machine type communication cellular network by utilizing the channel gain relationship of signal transmissions between the aircraft and the communication base station; determining the number of neighboring points at each point in the region according to the neighboring point range, obtaining distances between the neighboring points by the neighboring point range information, obtaining the minimum distance between regular waypoints by using the minimum distance cycle evolution; and obtaining the minimum distance when the aircraft traversing the coordinates of all flight waypoints, the flight order of flight points and the order of flight paths by using the artificial ant colony algorithm and the minimum distance between regular waypoints to control the flight of the aircraft. Themethod and system realize the minimum flight distance of the aircraft and improve the control efficiency of the flight.

The invention discloses a wireless sensor network multipath reliable transmission fault-tolerant method. Three parts of a wireless sensor network initial path calculating and establishing method basedon an ant colony algorithm, the wireless sensor network multipath reliable transmission fault-tolerant method based on an immunization mechanism and a load balancing mechanism are included. The wireless sensor network initial path calculating and establishing method based on the ant colony algorithm is mainly used for considering factors induced by jumping / distance and artificial ant pheromones.The wireless sensor network multipath reliable transmission fault-tolerant method based on the immunization mechanism refers to relevant problem definitions of antibody antigen, path coding, adaptation degree, variable rule and the like which are achieved through the multipath transmission method based on immunization. The multipath load balancing mechanism is mainly used for distributing coded data pieces with unequal number to different paths according to the established transmission paths with unequal masses to improve the load balancing and transmission fault-tolerant capacity.

The invention discloses a regression test method for carrying out test case priority ranking based on an ant colony algorithm, which comprises the following steps: (1) converting a test set of a tested program into a graph G, and calculating and instantiating all artificial ants; (2) the artificial ants starting a weekly chart G to construct a problem solution, and before ant state transition eachtime, the artificial ants calculating heuristic information of all candidate nodes, and selecting a next target node to be transferred; (3) after all artificial ants finish the work of constructing the solution, updating the pheromone contents of all edges in the graph G through a global pheromone updating rule; (4) obtaining the sequenced test sleeves when an end condition is met, otherwise, returning to the step (2); and (5) sequentially carrying out regression test on the software by taking the sorted test sets as test cases. According to the method, the ant colony algorithm is used for searching the optimal test case execution sequence, so that the coverage rate of statements in the tested program is maximized, and the regression test efficiency is improved.

The invention relates to an artificial ant nest. According to the artificial ant nest, ants in the artificial ant nest can automatically stacks waste in a nest chamber to a designated position. The nest chamber of the artificial ant nest is divided into multiple areas, and each area is controlled by a gate. A ventilating area is set to be a garbage area and connected to the nest chamber. The distance from the garbage area to the nest chamber is shorter than that from the feeding active area to the nest chamber; or a channel from the nest chamber to the garbage area is easier for ants to crawl than a channel from the nest chamber to the feeding active area. According to the artificial ant nest, the ants in the artificial nest can automatically clean the garbage in the nest chamber and stacks the garbage to the designated position. The artificial ant nest can be suitable for all types of scientific researches, teaching, pets, toys and the like. With the principle and the structure, all kinds of ant nests can be cleaner, more conveniently cleaned and more suitably observed.

The invention belongs to the technical field of iris recognition, and particularly relates to a method for extracting eyelashes based on an improved ant colony algorithm. The method is implemented according to the following steps: (1) initializing pheromone in an eyelash extraction area; putting one artificial ant, and setting each parameter of the algorithm; (2) executing step (3) and step (4) in sequence by each artificial ant; (3) selecting the positions in the next step by the artificial ants, wherein the end condition is that the artificial ants walk specified step number s or have no way out; (4) carrying out pheromone updating on the positions where the artificial ants go through; (5) after the traversing of all the artificial ants is ended, obtaining the pheromone concentration at each position of an image, and then using an OTSU algorithm to extract eyelash edges; (6) integrating the obtained eyelash edges to obtain complete eyelashes; and (7) using a sequence sliding window to eliminate noise so as to obtain the final eyelashes. When the distances of the artificial ants take the pixel of about 25, the algorithm can guarantee the speed of eyelash detection and also can guarantee the effect of eyelash detection.

The invention discloses an LEACH (Low-Energy Adaptive Clustering Hierarchy) protocol optimization method based on an ant colony algorithm. In a wireless sensor network, selection of random cluster heads is easy to cause non-uniform energy loss of nodes in the network and reduction of a network life cycle, so monitoring blind spots are formed in the later period of network lifetime and the integrated performance of the network is influenced. The method provided by the invention comprises the steps that a sink node obtains a network topology and network energy; the nodes with relatively high energy are taken as the cluster heads; the cluster heads finish fusing data and remove redundant data; artificial ants search next hop nodes according to a method combining a transfer probability and the annular model limited distance; if paths searched by adjacent three times are the same within the iteration times or the maximum of the iteration times reaches, the search is finished. According to the method, the energy consumption is reduced and the relatively high performance is achieved in an aspect of improving the network life cycle.

The invention discloses a method for site selection of a land consolidation project based on ant colony optimization algorithm. The method comprises the steps of integrating spatial information data of land utilization and nature and social economy attribute data to form a set of space units for site selection of the land consolidation project; establishing an objective function for maximum added cultivated land potential, an objective function for highest land consolidation suitability and an objective function for continuous space concentrated areas, determining an implementation scale and an added cultivated land ratio as constraint conditions, and constructing an implementation scale constraint condition expression and an added cultivated land ratio constraint condition expression; constructing a model for site selection of the land consolidation project based on ant colony optimization algorithm, establishing a mapping relation between a solving problem and an artificial ant colony, and solving space layout of the land consolidation project; adjusting and optimizing the space layout of the land consolidation project to produce a conceptual drawing for site selection of the land consolidation project. The invention can better coordinate three conflicting optimization goals and can obviously optimize the space layout of the project and improve the social and ecological benefits on the basis of ensuring the economic benefit of the land consolidation.

The invention belongs to the technical field of general control or adjustment systems, and particularly relates to a deviation rectification control method and device for shield tunneling postures. The deviation rectification control method comprises the steps that a deviation rectification principle model of a shield tunneling machine is constructed; the deviation rectification principle model comprises a deviation rectification track curve; the minimum deviation rectification radius of the deviation rectification principle model is determined; the minimum deviation rectification radius of the deviation rectification principle model is the curvature radius of the deviation rectification track curve; preset shield tunneling machine parameters are processed by using an artificial ant colony algorithm to obtain an optimal feature subset; according to the minimum deviation rectification radius and the optimal feature subset, a deviation rectification mathematical model of the shield tunneling machine is constructed; based on the deviation rectification mathematical model, the optimal feature subset is optimized through an artificial bee colony algorithm to obtain control parameters; and a tunneling posture of the shield tunneling machine is controlled to rectify deviation according to the control parameters. The optimal feature subset can be screened out by introducing the ant colony algorithm, and the optimal feature subset is used as an initial population of the artificial bee colony algorithm, so that the solving quality can be improved, the deviation rectification precision can be improved, and a better deviation rectification effect can be achieved.

The invention discloses a numerical simulation method and device for oil-gas migration in a tight reservoir and relates to the technical field of petroleum. Hydrocarbon source rock grids are equivalent to formicaries, artificial ants representing oil gas are released from multiple hydrocarbon source rocks according to the hydrocarbon-generating intensity, paths of the artificial ants and the shut-down grids, namely the grids in an enrichment region set, are recorded, and paths of all the artificial ants and the enrichment region set are acquired. Compared with a Darcy seepage manner simulation method, the method is simpler and more convenient, the effect more approaches practical conditions, the prediction precision is high, and meanwhile, quick calculation is realized due to simplicity of the method.

The invention discloses an automatic plug seedling transplanting path optimization method based on an artificial ant colony. The method comprises the steps that the health conditions and position information of plug seedlings in seedling trays with plug holes to be filled with seedlings and plug seedlings in transplanting seedling trays are determined through the machine vision method, and a seedling tray matrix is generated, positive and negative node numbering is carried out, and the concentration of pheromones is initialized; next access nodes are selected by artificial ants through the roulette method, accessed nodes are added into a taboo table so that the nodes will not be repeatedly accessed, and access paths of the artificial ants are recorded to obtain the length of the shortest path and the numbering sequence of all the nodes of the shortest path; the pheromones are comprehensively updated, and the taboo table is cleared after updating is finished; the steps are repeatedly executed, and the shortest path of each turn of access of the artificial ants is recorded to obtain the shortest path. By means of the method, the motion path of a transplanting claw can be effectively shortened in the process of filling the plug holes with seedlings, working efficiency is improved, an excellent optimization effect is also achieved in the process of dealing with a large number of empty plug holes, and a signal empty plug hole can be dealt with as well.

The invention discloses a wireless cloud computing system resource distribution method, and belongs to the technical field of cloud computing. Regarding a wireless cloud computing system, the conceptof jump reaching rate is provided; by combining an artificial ant colony algorithm with a tabu search algorithm, a new algorithm is provided and used for transferring users in a region above the jumpreaching rate in the wireless cloud computing system into a region below the jump reaching rate. The wireless cloud computing system resource distribution method includes the steps that firstly, a region is divided into equal-area regions, and system deployment is conducted; then, through designed algorithm iteration, an ant value is transferred, and transferring information is updated till an endcondition is met; finally, the new algorithm is simulated on the system. Verification results show that by the adoption of the new algorithm, computing resources of the system can be evenly distributed, the number and ratio of user jams of the system can be significantly reduced, and the user experience is improved.

The invention belongs to the technical field of iridodiagnosis, and particularly relates to a method for extracting a curling wheel on the basis of a two-stage ant colony algorithm. According to the method, secondary iteration needs to be carried out, a first stage has a task of carrying out iteration for a small number of times by using a great quantity of artificial ants to determine an approximate position of an ANW, and the position is used for determining initial positions of the artificial ants in a next stage; and in a second stage, a small quantity of artificial ants are used for carrying out repeated iteration to obtain a final curling wheel extraction result. In each iterating process, by introducing a guiding factor in a local direction and a guiding factor in a global direction, the artificial ants can be rapidly close to the ANW direction; and by using a pheromone update strategy based on a point density, concentration of pheromones near an edge of the ANW can be rapidly increased, and finally, according to a concentration value of the pheromone, a final ANW curve is extracted.

The invention discloses a task scheduling method of a Ketle cluster server, which comprises the following steps: performing coordination filtering based on the completion time of each task on each server to obtain a recommendation score of each server for each task; obtaining a load condition score of each server based on the state index of each server; based on the recommendation score of each server for each task and the load condition score of each server, obtaining a heuristic factor of each task transferred between any two servers; and performing iterative search in the cluster server based on the heuristic factor of each task transferred between any two servers in combination with an ant colony algorithm to obtain a final task scheduling allocation scheme. the data processing tasks on the Ketle system are scheduled and distributed by utilizing an artificial ant colony algorithm; the resource utilization rate of the Kettle server cluster system can be maximized, the load balance of the servers is achieved, the system performance is improved, the efficiency of the data cleaning, extracting and loading process is improved, then the customer experience is improved, the working efficiency is improved, and the benefits of enterprises are improved.

The invention discloses a precipitation prediction method and system. The method comprises the steps of collecting historical precipitation data; processing the historical precipitation data to obtainprocessed precipitation data; decomposing the processed precipitation data by adopting an MEEMD method to obtain a plurality of decomposition items and remainder items with different frequencies; determining a precipitation prediction model; wherein the precipitation prediction model comprises a trained convolutional neural network, an optimized support vector machine and an optimized BP neural network; and predicting the precipitation through the precipitation prediction model according to the decomposition items and the remainder items. According to the method, the MEEMD is utilized to decompose the precipitation data into different decomposition items, the convolutional neural network, the particle swarm optimization support vector machine and the BP neural network optimized by the artificial ant colony algorithm are adopted to establish the combined prediction model for the different decomposition items, prediction errors caused by data non-smoothness are reduced, and the prediction precision is improved.

The invention relates to an assessment factor rating method for land resources based on an ant colony clustering model. The method comprises the steps of inputting indexes of scale of each assessment factor; establishing a two-dimensional planar grid according to assessment factor objects, and randomly distributing each assessment factor object on the two-dimensional planar grid; setting artificial ants and randomly distributing the artificial ants on the two-dimensional planar grid; and iteratively picking up and dropping the assessment factor objects in probability through the artificial ants so as to obtain a rating result of the assessment factor objects. The assessment factor rating method for the land resources based on the ant colony clustering model can automatically rate the assessment factor objects and provide technical support for rational use of the land resources.

The invention discloses a heterogeneous unmanned aerial vehicle cluster-oriented coupling multi-task allocation method and device. The method comprises the steps: quantifying the capability indexes of all unmanned aerial vehicles in an unmanned aerial vehicle cluster, and quantifying the capability demands of all tasks; establishing constraint conditions based on the capability indexes and the capability demands; based on the constraint conditions, establishing a multi-task allocation model by taking the shortest total voyage as a target; establishing an artificial ant matrix based on the task model; determining the relative task capability of each ant in the artificial ant matrix; based on the determined relative task capability of each artificial ant and the pheromone intensity on each path, circularly executing state transition, and determining a current task path; based on the current task path, cyclically updating the pheromone intensity until an optimal task path is determined; and controlling the unmanned aerial vehicle cluster based on the obtained optimal task path. According to the method disclosed by the invention, heterogeneous unmanned aerial vehicle cluster multi-task allocation with different coupling strengths and different complexity degrees in different scenes can be processed under a unified framework.

The invention discloses a multi-energy system capacity optimization method based on a hydrogen-heat hybrid energy storage device. The invention belongs to the technical field of multi-source energy storage of multi-energy systems. According to the method, the source-load characteristics and the advantages and disadvantages of a hydrogen storage device and a heat storage device are fully combined,the hydrogen storage device and the heat storage device are combined to form a hydrogen-heat hybrid energy storage system, and when source output of a multi-energy system cannot meet the load requirement, a hydrogen-oxygen fuel cell and temperature difference power generation are adopted for supplementing the vacancy electric energy. According to the invention, the capacity optimization configuration model taking the investment cost of the hydrogen-heat hybrid energy storage device as the target function is established based on the hydrogen storage device model, the heat storage device model and the net load power, and the optimal energy storage capacity configuration is optimized by adopting the artificial ant colony algorithm, so that the investment cost can be reduced on the premise ofensuring the reliable energy supply of the system.

The invention relates to a multi-level joint routing and survivability strategy based on economic factors and belongs to the field of communication networks. The establishment of an economic objectivefunction is researched and planned under the framework of a planning and optimization model, and a multi-level joint routing algorithm considering the economic factors is adopted to provide a route calculation function for network planning, and at the same time, an optimization protection and recovery strategy based on shared resources is researched. Through analyzing the granularity and the service level of affected service, a recovery strategy is selected, for service with large granularity and a strict recovery time requirement, a corresponding optical layer recovery is adopted, and for service with small granularity and a long recovery time or no time requirement, resources in a shared resource pool are used to take corresponding recovery measures at an IP layer. In addition, throughinteraction between the artificial ant processes, a differential routing calculation problem is solved, the generation of a large number of useless solutions is avoided, and the efficiency of route search is improved.

The invention belongs to the technical field of iris recognition, and in particular relates to a method for extracting eyelashes based on an improved ant colony algorithm, which is implemented according to the following steps: (1) initializing the pheromone in the eyelash extraction area; placing an artificial ant, and setting each parameter of the algorithm; (2) ) each artificial ant executes step (3) and step (4) in turn; (3) the artificial ant selects the position of the next step, and the end condition is to finish the prescribed number of steps s or to have no way to go; (4) the artificial ant Update the pheromone at the passed position; (5) After all the artificial ants have traversed, get the pheromone concentration at each position of the image, and then use the OTSU algorithm to extract the edge of the eyelashes; (6) Integrate the edge of the eyelashes to get a complete eyelashes; (7) Sequential sliding windows are used to eliminate noise to obtain the final eyelashes. In the present invention, when the distance between artificial ants is about 25 pixels, the algorithm can not only ensure the speed of eyelash detection, but also ensure the effect of eyelash detection.

The invention discloses a fast-converging ant colony routing establishment method based on a vehicle-mounted short-distance communication network, comprising the following steps: a node receives heartbeat information of surrounding nodes, and determines the distance and driving direction of surrounding nodes according to the heartbeat information; from a source node to a destination The nodes determine the selection zone step by step; number the nodes in the selection zone and the selection zone; initialize the pheromone of the source node and each intermediate node according to the number; use the improved ant colony algorithm to establish a route; Excellent transmit power. The present invention makes full use of the characteristics of the V2X network, improves the ant colony algorithm, not only reduces the invalid walking of artificial ants, but also greatly increases the convergence speed of the ant colony algorithm, and proposes a routing establishment method suitable for V2X networks .

The invention discloses a resource allocation method of a wireless cloud computing system, which belongs to the technical field of cloud computing. The present invention proposes the concept of jumping arrival rate for the wireless cloud computing system. By combining the artificial ant colony algorithm and the tabu search algorithm, a new algorithm is proposed to transfer users above the jumping reaching rate in the wireless cloud computing system. To the area below the jump reach. This method first divides the area into equal-area areas for system deployment, and then iteratively performs the transfer of ants and the update of transfer information through the designed algorithm until the termination condition is met. Finally, the algorithm is simulated on the system, and the verification results show that, By using this algorithm, computing resources of the system can be distributed in a balanced manner, the number and proportion of user congestion of the system can be significantly reduced, and user experience is improved.

The invention discloses an insect catching device, and particularly relates to solenopsis invicta collecting equipment which is technically characterized by comprising a movable cart and a cylinder for covering an ant cave, an expelling mechanism for forcing the solenopsis invicta to leave the ant cave by increasing the internal humidity of the cylinder and an artificial ant cave for receiving and transferring solenopsis invicta communities are arranged in the cylinder; and the expelling mechanism comprises a limiting assembly used for spraying steam to the cylinder, the limiting assembly comprises a water storage ring which is arranged on the inner wall of the cylinder, liquid flows in the water storage ring, a plurality of spray heads are arranged on the surface of the water storage ring, piezoelectric ceramic pieces used for atomizing the liquid in the water storage ring into steam and spraying the steam out of the spray heads are arranged at the joints of the water storage ring and the spray heads, and the artificial ant cave comprises a box body with a plurality of notches in the surface and a lifting part used for lifting the box body. By using the solenopsis invicta collecting equipment, the relatively complete solenopsis invicta communities can be obtained under the condition that the ant cave is not damaged.

The present invention discloses an artificial ant colony algorithm optimization-based particle transfer method. According to the particle transfer method, before re-sampling is performed on particles, an ant colony algorithm is used to improve the a posteriori distribution of the particles; the entire distribution of the particle set is transferred to a high-likelihood region through a probability-based selection method; a random number method is used to generate new particles; and with the above strategies adopted, when the particles move to the high-likelihood, the diversity of the particles can be maintained, and therefore, the estimation accuracy of particle filtering can be improved. The invention also discloses an artificial ant colony algorithm optimization-based particle transfer device. With the particle transfer device adopted, same effects realized by the particle transfer method can be also realized.

The invention belongs to the technical field of iris diagnosis, and in particular relates to a method for extracting crimping wheels based on a two-stage ant colony algorithm; the method needs to be iterated twice, and the task of the first stage is to use a large number of artificial ants to perform a few iterations to determine the ANW Approximate position, which is used to determine the initial position of the artificial ants in the next stage; in the second stage, a small number of artificial ants are used to perform multiple iterations to obtain the final extraction result of the crimping wheel. In the process of each iteration, the artificial ants can quickly approach the ANW direction by introducing the local direction guidance factor and the global direction guidance factor; by using the pheromone update strategy based on the point density, the pheromone concentration near the edge of the ANW can be Rapid growth, and finally extract the final ANW curve according to the concentration value of pheromone.

The invention discloses a pilot scheduling method applicable to massive MIMO (multiple-input multiple-output) cellular mobile communication networks. The pilot scheduling method includes steps of (1),acquiring state information of channels between base stations and users in the base stations; (2), initializing heuristic information and information elements on construction graphs; (3), generatinga plurality of artificial ants and allowing the ants to completely walk on the construction graphs; (4), recording walk paths of the ants and generating pilot allocation matrixes; (5), judging whetherstop conditions are met or not, stopping actions if the stop conditions are met, and outputting the pilot allocation matrixes; (6), updating the information elements on the construction graphs and skipping to the step (3). The pilot scheduling method has the advantages that the pilot scheduling method for relieving the influence of pilot contamination in massive MIMO systems is proposed on the basis of ant colony optimization tools, and the available information rates of the systems can be maximized.

The invention belongs to the technical field of general control or adjustment systems, and specifically relates to a deviation correction control method and device for shield tunneling posture. The method includes: constructing a deviation correction principle model of a shield machine; the deviation correction principle model includes a deviation correction trajectory curve; determining the deviation correction principle The minimum correction radius of the model; the minimum correction radius of the correction principle model is the curvature radius of the correction trajectory curve; the artificial ant colony algorithm is used to process the preset shield machine parameters to obtain the optimal feature subset; according to the minimum correction radius and the most The optimal feature subset is used to construct the deviation correction mathematical model of the shield machine; based on the deviation correction mathematical model, the control parameters are obtained by optimizing the optimal feature subset through the artificial bee colony algorithm; and according to the control parameters, the tunneling posture of the shield machine is controlled for deviation correction. By introducing the ant colony algorithm, the optimal feature subset can be screened out, and the optimal feature subset can be used as the initial population of the artificial bee colony algorithm, which can improve the solution quality, improve the accuracy of deviation correction, and achieve better deviation correction effect.

The invention relates to the technical field of ant breeding, and discloses a nest construction method of odontomachus monticola. The construction method comprises the following steps that 1, a transparent box body with an opening in the top and a top cover used for sealing the top of the box body are selected; 2, bottom holes are formed in the bottom of the box body; 3, a plurality of unit modules and filling parts for filling gaps in the box body are selected; 4, chamber grooves communicated with the bottom holes are formed in the two sides of each unit module, wherein a main inlet, a firstauxiliary inlet and a second auxiliary inlet which are communicated with the chamber grooves are formed in the top of each unit module; 5, the multiple unit modules and the filling parts are put intoand fully filled into the box body, and then detachable fixing pieces are used for fixing; and 6, the top of the box body is sealed by using the top cover. According to the scheme, the problem that anexisting artificial ant nest is inconvenient to disassemble and expand is mainly solved.

The invention discloses a regression testing method for prioritizing test cases based on an ant colony algorithm, comprising the steps of: (1) converting a test suite of a program under test into a graph G, calculating and instantiating all artificial ants; (2) The artificial ants start to travel around the graph G to construct a solution to the problem. Before each ant state transition, the artificial ant calculates the heuristic information of all candidate nodes and selects the next target node to be transferred; (3) when all the artificial ants are After completing the work of constructing the solution, the global pheromone update rule will be used to update the pheromone content of all edges in the graph G; (4) get the sorted test suite when the end condition is reached, otherwise return to step (2); (5 ) Use the sorted test suites as test cases to perform regression tests on the software in turn. The invention uses the ant colony algorithm to search for the optimal execution order of test cases, thereby maximizing the coverage rate of statements in the program under test and improving the efficiency of regression testing.