151 results about "Adaptive strategies" patented technology

Various embodiments are disclosed for a services policy communication system and method. In some embodiments, an intermediate networking device provides a service intermediary or intermediate connection between a network and one or more communications devices; implements a service profile set for assisting control of the intermediate networking device use of a service set on the network, wherein the service profile set includes one or more service profiles, each profile being associated with either the intermediate networking device or a communications device, each profile further including a plurality of service policy settings; and monitors use of the service set based on the service profile set, in which the implementation of the first service profile set is verified.

Various embodiments are disclosed for a services policy communication system and method. In some embodiments, a network device implements a service profile for assisting control of a communications device use of a service on a network, in which the service profile includes service policy settings for the communications device; monitors use of the service by the communications device based on the service profile; and modifies a service policy setting to achieve a service usage goal.

Various embodiments are disclosed for a services policy communication system and method. In some embodiments, a communications device implements a service profile for assisting control of the communications device use of a service on a network, in which the service profile includes service policy settings; monitors use of the service based on the service profile; and modifies a service policy setting to achieve a service usage goal.

A method of transmitting media to a client by an infrastructure device in a packet-switched network includes receiving a media stream at the infrastructure device. The method also includes determining an adaptation strategy according to at least one of one or more pieces of network information associated with the packet-switched network, one or more pieces of client information associated with the client, or one or more policies. The method further includes adapting the media stream according to the adaptation strategy to produce an output media stream.

The invention discloses a color image segmentation method, which comprises the following steps: processing an image to be segmented into a gray image; extracting a region profile map from the gray image by an Otsu threshold segmentation method, and determining an optimal threshold; taking the optimal threshold as a high threshold of a Canny operator, and extracting an edge map from the gray image by utilizing the Canny operator; and fusing the area profile map and the edge map, and outputting a segmentation result of a color image. The method adopts an operator threshold determining scheme combined with an adaptive strategy and an empirical value and overcomes the defect that an empirical value selecting method has application limitation; the local change intensity of a gray value is obtained through edge detection, so that over-segmentation of avoidable areas is limited; and residual edges are complemented through region segmentation, so that profiles of images after the segmentation are more clear and complete.

The invention provides a maneuvering target tracking method based on variable structure multiple models. The maneuvering target tracking method mainly solves the problems that in the prior art, target tracking accuracy is low and target tracking is not in time. The method includes the implementation steps that firstly, a target motion state detected by radar is sampled, and then a radar measured value is acquired; secondly, a maneuvering target tracking mathematical model is established according to target motion characteristics; thirdly, a maneuvering target motion model is established according to the target tracking mathematical model and is initialized; fourthly, through a model set adaptive strategy, a target motion model set at each moment is acquired; fifthly, according to the radar measured value and the target motion model sets, a variable structure interactive multi-model algorithm is operated, state estimation of a maneuvering target is acquired, and primary tracking of the target is achieved; sixthly, the fourth step and the fifth step are repeatedly executed until tracking is finished. On the premise that high tracking accuracy is guaranteed, the calculation quantity is reduced, and timeliness of maneuvering target tracking is improved.

The present invention discloses an injection period adaptive strategy-based insulation resistance detection device and a method. The insulation resistance exists between a locomotive chassis and a locomotive power supply system. The detection device comprises a first resistor, a second resistor, a third resistor, a fourth resistor, a sampling resistor, a signal injection circuit, a voltage signal acquisition circuit and a microcontroller. The voltage signal acquisition circuit is used for acquiring the voltage shared by the sampling resistor. The microcontroller is used for calculating the value of the insulation resistance. The detection method is provided for automatically adjusting the insulation resistance of an injection period. For the complex and changeable circuit structure of a high-voltage system, the injection period of a signal is automatically adjusted, so that the influence of the ground capacitance on the detection of the insulation resistance is eliminated. The real-time detection accuracy of the insulation resistance is improved. Meanwhile, the insulation resistance is effectively detected under the condition that the insulation of the positive electrode and the insulation of the negative electrode of the DC system are equivalently decreased.

The present invention provides a method used by a user to customize a recommendation system in an online system, and belongs to the technical fields of data mining and network application. The method aims at a problem that an algorithm in a previous recommendation system is fixed and therefore a personalized recommendation system that meets demand of each user cannot be constructed. According to the method, a user customizes a personalized recommendation engine; a policy that a system algorithm self-adapts to a user is realized; moreover, relatively good recommendation diversity and relatively high recommendation accuracy are ensured; and the time period of a system in learning a user behavior is effectively shortened. The method comprises the following steps: step 1, according to a personal demand, a user starting setting of a recommendation engine in an online system; step 2, via a recommendation engine configuration page designed by the system, the user setting a recommendation engine parameter to customize a personalized recommendation algorithm that meets a personal preference of the user; and step 3, storing the configured recommendation engine and applying the configured recommendation engine in a recommendation system, so that according to the recommendation engine parameter set by the user, the system uses a combination policy to form a hybrid recommendation algorithm through combination, so as to calculate a recommendation list.

The invention discloses an improved particle swarm optimization-based mobile robot path planning method. According to the method, a global optimal update strategy of disturbance is implemented in RDSAPSO (random-disturbance self-adaptive particle swarm optimization), small random disturbance is added to a global optimal position in a population, so that non-stagnation attributes in the RDSAPSO are obtained; an adaptive strategy is adopted to finely adjust three control parameters of particles in the RDSAPSO, so that global search capability and local search capability can be better balanced in the RDSAPSO, and a convergence guarantee parameter selection principle is provided for the RDSAPSO; and the constraint conditions of a path planning problem are solved through using a feasibility rule, and therefore, optimization difficulty can be decreased, and diversity can be decreased; and the developed RDSAPSO is utilized, so that an RDSAPSO-based path planning method framework is completed. With the method of the invention adopted, an effective method is provided for the path planning problem of a mobile robot.

The invention relates to a real-time space target feature point tracking method suitable for a space tethered robot. The method is mainly formed by a feature point extraction algorithm, a feature point matching algorithm, discrete point elimination, accurate positioning and a self-adaptive strategy. Feature points extracted through an improved SURF algorithm are strong in robustness and stability. The method enables the feature point matching accuracy and target positioning accuracy to be high, and is suitable for stable tracking of targets which have rapid changes in positions and gestures and are simple in structure in a multi-scale image sequence. The method has robustness in various types challenging situations, and the tracking process has short-term anti-occlusion capacity. The method can be used for achieving the real-time detection and tracking of a plurality of types of targets, is suitable for real-time robustness tracking for the space targets which have rapid changes in positions and gestures and are simple in structure in the multi-scale image sequence.

The invention discloses a robot path planning method based on a self-adaptive genetic algorithm. The method comprises the following steps: constructing a raster map as an environment model of a robot,optimizing an intermediate node by adopting an improved genetic algorithm, and supplementing a path between the nodes by using algorithm for solving shortest path through Dijkstra, wherein the pathsobtained through this way are feasible solutions, and a discrete problem is converted into a continuous problem; setting the shortest distance as a fitness function, proposing a selection method of combining a championship selection method with an optimal saving strategy, an arithmetic crossover way and a random variation strategy, and setting the crossover rate and the variation coefficient by adopting a self-adaptive strategy in the AGA-SNS; and finally simulating and verifying the effectiveness and feasibility of the improved algorithm. Through the planning method disclosed by the invention, the algorithm performance is improved by adopting a way of self-adaptively performing nonlinear conversion on the crossover rate and the variation coefficient between the average fitness and the maximum fitness along with the fitness, and the safest and effective path is found out.

The invention discloses a vehicle route optimization method. The vehicle route optimization method includes that defining a vehicle route problem into a graph model, solving an inter-cluster cost route from a global view to acquire a feasible solution space, and optimizing the feasible solution space through a Monte Carlo method, genetic manipulation, a quantum rotating gate adaptive strategy and the like. The vehicle route optimization method is capable of solving the vehicle route problem in the global connection, optimizing the time and space complexity in the problem solving process, and avoiding premature convergence. The vehicle route problem refers to that a certain number of customers have different numbers of goods demands, a distribution center provides goods for the customers, one motorcade is responsible for distributing goods, and proper driving routes are organized to meet the demands of the customers and achieve the aims of shortest journey, lowest cost, shortest time consumption and the like under a certain constraints.

The invention discloses a method for generating a metamorphic test case based on an adaptive random strategy, and aims at randomly automatically generating a test case based on an adaptive strategy. The method comprises the steps of randomly generating a first group of original test cases; generating additional test cases according to metamorphic relation; forming a selected test case through the two cases; dividing an input field to obtain a subfield without being covered with the selected test case; generating a plurality of test cases randomly in the subfield; selecting one group of test cases as the candidate original test cases; generating the additional test cases according to the metamorphic relation; then selecting the test cases with the maximum distance as the next group of text cases according to the distance from the candidate test cases to the selected test cases and the distance from the candidate original test cases to the additional test cases. The test case generation method is simple and clear; the dispersion, effectiveness and coverage rate of the test cases in the input field are greatly improved.

The invention discloses a self-adaptive ant colony optimization based flexible workshop dispatching technology. According to the technology, the ant colony optimization algorithm is applied to the flexible workshop dispatching problem. In order to always obtain ideal performance of the algorithm on different problem instances, a self-adaptive strategy, which can automatically select heuristic information and guidance force control parameters according to the problem instances to be solved and the current search state, is introduced into the ant colony optimization algorithm, which greatly improves the algorithm optimization efficiency and provides a new path for solving the flexible workshop dispatching problem. Based on experiment of standard test library for the flexible workshop dispatching problems, the technology provided by the invention can efficiently find a dispatching scheme with shortest construction period or nearly shortest construction period.

The invention discloses a file storage method for a distributed file system. The method comprises the following steps of acquiring attribute parameters of a file; generating an adaptive strategy for regulating a strip according to the attribute parameters of the file; regulating the size of the strip according to the adaptive strategy, and storing the file in the strip. According to the method, a mechanism for generating the adaptive strategy according to the size of a written file is established to dynamically regulate the strip, so that the performance and the adaptability of the distributed file system are improved, and the application range of the distributed file system is widened.

The invention relates to real-time numerical simulation, network communication, computer programming and visual display. In order to provide a virtual simulation platform integrating real-time simulation, data monitoring, data storage, visual display and performance evaluation, the virtual simulation platform is used for verifying feasibility, applicability and effectiveness of an RLV reentry three-dimensional real-time trajectory optimization and tracking method and a robust adaptive strategy. The invention, RLV virtual simulation platform design and implementation method, designs the Simulink model and the control algorithm of the reusable carrier RLV on the computer, forms the Simulink model library and the control method library, and the control method library includes the super spiralsliding mode, the terminal and the adaptive dynamic programming control algorithm to compile the Simulink model into C code that can be run in the dSPACE simulator and download it to the dSPACE simulator through a computer. The invention is mainly applied to RLV simulation occasions.

The invention belongs to the field of intelligent algorithm and production management and relates to a flexible job shop scheduling method based on a multi-heuristic information ant colony system, including: extraction drawing model building, initialization; construction of the solution set of FJSP; pheromone updating; peuristic information file updating; termination condition check. The inventionintroduces six kinds of heuristic information into the ant colony system, so that the algorithm can obtain ideal performance in different problem instances, thus avoiding falling into local optima, and an adaptive strategy capable of automatically selecting the heuristic information and the guiding force control parameters thereof according to the problem instance to be solved and the current search state is used, the heuristic information design of the whole ant colony converges to the current optimal design which can produce high-quality solution, improves the speed of sword collection, improves the optimization efficiency of the algorithm, and improves the efficiency of the flexible job shop scheduling.

The invention provides a vehicle detection method and device based on an adaptive key point heat map, and belongs to the technical field of computer vision and target detection and recognition. The method comprises the steps that a key point heat map is rendered through an adaptive variable-radius Gaussian kernel, the center point of a vehicle target is extracted, and then information such as thesize and the position of the vehicle target is obtained through regression according to the width and the height of the vehicle target; rendering of the key point heat map adopts a self-adaptive strategy, the Gaussian kernel radius changes along with the change of the target width and height, a boundary frame predicted under the condition of road congestion is more compact, the calculation coordinate range is reduced from the whole feature map into the target boundary frame, and network convergence can be accelerated; the method can effectively solve the problems of missing detection, false detection and low detection precision among densely shielded vehicles in a crowded road video scene, can meet the requirements for vehicle detection speed and accuracy in a crowded road monitoring video, and is of great significance to intelligent traffic management work.

The invention provides a parameter adaptive fractional order active disturbance rejection automatic generation control method. The method combines a fractional order control idea and an active disturbance rejection algorithm with a component number order active disturbance rejection algorithm, and then applies a parameter adaptive strategy to the fractional order active disturbance rejection algorithm. The method of the invention improves the control performance of the fractional order through a computer to improve the control performance of the automatic generation control system. The methodcan eliminate the fussy process of manually adjusting controller parameters. The method automatically adjusts the parameters of the system by using a parameter adaptive algorithm, and the adjusted fractional-order auto-disturbance rejection model can obtain high control performance without good manual adjustment parameters, and the anti-interference ability is good.

The embodiment of the invention provides an intelligent body building realization method, an intelligent body building realization device and an intelligent body building realization system. A body sensing engine sensor can be arranged on a terminal; the sport state of a user is determined through that the user correction information about a specific user is acquired by the body sensing engine sensor; when the value of a difference between the correction information and the information synchronously acquired by the body building equipment is smaller than a set value, the correction information can be sent to the body building equipment, the body building equipment is enabled to adjust the state according to the correction information and a self-adaption strategy corresponding to the specific user. Since the state is adjusted according to the corrected information and the state is adjusted according to the self-adaption strategy corresponding to each user, the state adjustment is more selective and accurate, specific sport demand of the users can be satisfied, and the safety of the users is ensured.

The invention relates to a real-time intrusion detection method based on data mining. An ASM (adaptive strategy management) module and an AMM (adaptive model management) module are added into a distributed real-time system framework and used for automatically generating and distributing detection strategies and detection models of an intrusion detection system based on data mining respectively. By the aid of the structure, the problems in terms of automation of related data, automatic generation and distribution of the detection models and the detection strategies, and real-time data evaluation can be solved. A distributed system comprises some components which can be flexibly changed in the system framework to adapt to different environmental changes and meet the demands of users.

The invention relates to an embedded Linux multimedia information collection processing device and relative transmission method. Said device comprises: an embedded server, several client terminals and a cloud platform, wherein, said embedded server and cloud platform are connected via the RS485 bus; the embedded server and the client terminal process interactive control and data transmission via the RTP / RTCP to use the RSVP to realize QoS resource preparation. The invention uses safety strategy to prevent the impact on the server to confirm the safety of server authorization and safety of flow media in the network transmission. The network self-adaptive strategy of user terminal can make said device realize the balance between the band width process and the replay possibility when transmitting data in limit network. The invention can apply the remote control area, especially the unattended remote area to apply stable real-time interactive acoustic-virtual detection.

The invention discloses a software middleware oriented intelligent decision supporting frame and a working method thereof. The intelligent decision supporting frame comprises a perceptron module, an intelligent decision engine module, a knowledge base module and an interpreter module, wherein the intelligent decision engine module comprises a decision submodule, a learner submodule and a utility evaluation submodule, and the like. The working method of the intelligent decision supporting frame comprises the following steps of: according to an adaptive strategy definitional language, defining a goal, a utility function, a strategy rule and an ontological knowledge; analyzing a decision goal or contextual information, the strategy rule, and the like; respectively forwards reasoning system contexts; backwards reasoning the decision goal; analyzing reasoning results into actual system service; acting the actual system service into a system; and according to the evaluation function, evaluating the reasoning results and regulating the strategy rule. If the intelligent decision supporting frame does not stop, the steps are repeatedly carried out. The invention provides the adaptive strategy definitional language, can support the decision mechanisms of reasoning, planning, learning, and the like, and provides two loop structures of intelligent decisions and strategy update.

The invention relates to the technical field of welding robots, in particular to an arc welding robot collision-free path planning method, computer equipment and a computer readable storage medium. The method comprises the steps of building a welding environment model in a grid method and bounding box method hybrid modeling mode, and determining an obstacle object and a guide space; searching forcollision-free transfer tracks between weld joints through an RRT method to form a transfer matrix; and discretizing a difference method through a discrete strategy, dynamically adjusting the variation step length by adopting an adaptive strategy, screening the collision-free transfer tracks in the transfer matrix by taking the welding sequence and the welding direction as objects, and determiningthe shortest collision-free welding path. A complete solution of model establishment, track planning and path planning is provided for a complex welding task, the calculation speed and precision areboth considered, a path reference can be provided for engineers in the face of new products, the experience acquisition cost is reduced, and the development cycle is shortened.

The invention discloses a green energy-saving algorithm for use in LTE (long-term evolution) hierarchical cell architecture and belongs to the technical field of wireless communications. The algorithm comprises the steps of first, establishing a macrocell and small cell architecture communication system for LTE hierarchical cells; second, for certain period of time T started from moment t, setting transmitting power of a hibernating base station to 0 by using a base station hibernation strategy on the premise of saving energy and ensuring lowest QoS balance of users; third, calculating energy consumption E and energy-saving rate Rho of each small-cell base station to ensure that the energy-saving rate Rho is maximum; within next period of time T, using a base station transmitting power adaptive strategy to adjust transmitting powers of the base stations according to time-varying characteristics of channels in order to reduce interruptions; fourth, carrying out simulation verification; base station energy-saving effect and user QoS are balanced, it is guaranteed that energy consumed by base stations can be saved as much as possible, and it is also guaranteed that good QoS is provided for a user.

The invention discloses a method for obtaining optimal planning of the transmission grid under new energy access. The method comprises steps that a transmission network planning model containing the new energy is established; a corresponding transmission network grid structure is established according to individual particles of the EPSO particle swarm optimization algorithm for the transmission network planning model; the transmission grid network structure is repaired to ensure the transmission network grid structure connected; the probabilistic DC power flow method is utilized to obtain thepower flow of each branch of the transmission network grid corresponding to the individual particles, and the individual particles which do not meet constraints of the transmission network planning model are determined; a fitness function value is calculated, and the adaptive strategy is utilized to select the optimal PSO strategy for multiple iterations to obtain the globally optimal individual particles; the globally optimal individual particles are transformed to form an optimal configuration scheme for transmission network planning. The method is advantaged in that the generalization ability and robust performance of the calculation process are enhanced, and the high-precision high-guided optimal configuration scheme for planning of the transmission network grid structure under new energy access can effectively obtained.

The invention provides a control method for three-way vibration of an underground floating slab based on magneto-rheological fat vibration isolators. Four semi-active magneto-rheological fat vibration isolators are arranged under the underground floating slab so that vibration energy of the underground floating slab on the vertical direction, rolling and pitching can be restrained. The advantage of being capable of controlling damping of the magneto-rheological fat vibration isolators is fully utilized, and a vertical-rolling-pitching vague vibration isolation control not relaying on a mathematical model and a self-adaptation strategy are adopted. The transmission of the vibration energy of the floating slab to a foundation is reduced respectively on the vertical direction, the horizontal direction and the longitudinal direction within a broadband range. The series defects that a traditional passive vibration isolator can not self-adaptively adjust a damping value along with changes of exciting vibration, and is poor in low frequent vibration isolation effect, and the like are overcome, and the problem of broadband vibration isolation of multi-directional vibration coupling of a rail of the underground floating slab can be solved.