33 results about "Dichotomic search" patented technology

The invention provides a cellular-free mMIMO (multiple input multiple output) system computing power resource allocation and beam forming optimization method and a cellular-free mMIMO system computing power resource allocation and beam forming optimization system, and belongs to the technical field of wireless communication. The method specifically comprises the following steps of: respectively establishing a double-queue model based on a first-in first-out criterion at a central processing unit (CPU) and an access point (APs), taking a dequeue rate at the CPU as an enqueue rate at the AP, constructing a data volume relationship in a queue of a current frame and a previous frame, and analyzing system downlink end-to-end time delay based on an M / D / 1 queuing model. In a first layer queue, a binary search algorithm is provided to design computing power resource allocation at a CPU, and in a second layer queue, a path tracking algorithm is provided to optimize a beam forming vector at an AP. According to the method, the instantaneous channel state information is utilized, the worst user time delay is minimized under an alternating iteration algorithm framework, the calculation complexity is reduced, and meanwhile an effective solution is provided for ultra-low time delay communication.

This invention relates to the field of multi-processor multi-task joint scheduling technology, specifically disclosing a typed task joint scheduling system and method based on a heterogeneous multi-core architecture. It introduces a joint scheduling mechanism to divide and sort tasks according to task size and priority. Based on this, for the time-limited characteristics of real-time tasks, an inertial weight coefficient particle swarm optimization method is used to iteratively update the load balancing strategy, minimizing the maximum response time of real-time tasks while meeting their schedulability requirements. Simultaneously, for the low-priority characteristics of non-real-time tasks, the problem-solving is simplified using a Lagrange-based convex optimization approach, and an energy-constrained binary search algorithm is employed to effectively reduce the average response time of non-real-time tasks, achieving optimal load distribution for the system.

A reinforcement learning-based energy efficiency optimization method for UAV-assisted MEC networks, belonging to the field of mobile communication, is proposed. First, the system is modeled and state information is collected. The state information is input into the policy model to generate flight and energy transfer actions, enabling UAV movement and service device selection. Next, an energy transfer and task offloading model is defined, and a gradient-based device offloading time allocation algorithm is initiated. Then, a binary search for the equilibrium marginal utility gradient is initialized, followed by a single iterative search, updating the search interval, and completing the equilibrium marginal utility gradient search. The final time allocation scheme is then determined, energy transfer and task offloading are executed, performance data is collected, the reward function is calculated, and experience is stored. Finally, the Critic network, Actor network, and target network are updated, and the optimal policy is obtained through iterative optimization. This invention significantly improves the overall energy efficiency and task processing throughput of the system.

This invention belongs to the field of radiation source individual identification technology, specifically relating to an open-set individual identification method based on closed-set model screening and binary search. This method leverages the intra-class clustering characteristics formed after training the closed-set model. First, it performs rapid screening of known classes on the test samples, reducing computational complexity while maintaining identification accuracy. Then, it adaptively determines the optimal discrimination threshold through a binary search strategy based on known class performance constraints, achieving the minimum missed detection probability while meeting engineering accuracy requirements. This significantly improves the system's open-set identification capability and real-time performance.

The application discloses a solar pumping system photovoltaic array capacity optimization method and device, relates to the field of new energy, and is used for minimizing photovoltaic array installed capacity design and energy storage capacity reduction. By acquiring basic parameters of a solar pumping system, the basic photovoltaic array installed capacity is obtained based on the peak water power of the system corrected based on the basic parameters. Under the condition of meeting the daily water supply constraint, the minimum feasible photovoltaic array installed capacity and the corresponding energy storage configuration are calculated based on the basic photovoltaic array installed capacity by using a dichotomy search method, with the minimum photovoltaic array installed capacity and energy storage capacity as the target. The application has the advantages of simple process, strong pertinence, robust optimization result, easy deployment, and strong expansibility.

The invention discloses a method for detecting a visual area of a super-large scale intelligent super-surface (RIS) auxiliary communication system, the RIS is a uniform planar array, and the method comprises the following steps: sequentially detecting the first unit, the second unit and the fifth unit on an RIS array plane, and judging whether the first unit, the second unit and the fifth unit are shielded or not; delimiting an initial area according to the shielding conditions of the five units, and judging whether the initial area is completely shielded or not; if the initial area is completely shielded, a DFS algorithm is used for all units on the boundary of the initial area in sequence, all shielded units are detected, and therefore the final visible area is recovered; if the initial area is not completely shielded, a binary search strategy is adopted, a shielded unit is detected firstly, then the unit serves as a starting point, all shielded units are detected through a DFS algorithm, and then the final visible area is recovered. According to the invention, accurate visual area detection is realized with low complexity and measurement overhead.

The invention discloses a large-scale MIMO beam training method and device, and the method comprises the steps: constructing a shared training system composed of a basic DFT codebook, a frequently repeated code target response matrix and a corresponding combined coding codebook, and carrying out the maximum posteriori decoding based on an energy observation sequence, thereby enabling the maximum posteriori decoding to be carried out under the time delay constraint condition that the number of training rounds is limited, and achieving the maximum posteriori decoding. And the beam forming vector with the maximum gain can still be accurately selected at a high probability. Compared with a traditional exhaustive search method, the inquiry frequency of beam training is remarkably reduced; compared with binary search and convolutional coding search schemes, the decoding accuracy is improved under the same number of training rounds, so that beam training performance improvement with low time delay and high accuracy considered is realized.

The invention relates to the technical field of industrial automation, in particular to a self-adaptive baud rate negotiation method, system and device and a medium, and the method comprises the steps: if the device supports an extended baud rate, obtaining an available baud rate list commonly supported by a master station and the device; performing binary search circular screening according to the available baud rate list, and determining the highest available baud rate; performing a packet loss rate test according to the highest available Baud rate, and determining a working Baud rate; when the master station and the equipment stably work according to the working baud rate, checking the communication quality of the master station and the equipment according to a preset period to obtain an error rate; and if the error rates of a plurality of cycles continuously exceed the preset error rate threshold, selecting the Baud rate of the next gear of the working Baud rate from the available Baud rate list to execute the packet loss rate test to update the working Baud rate, thereby improving the data transmission performance under an excellent channel.

This invention provides a microservice optimization method for industrial edge networks based on dynamic orchestration and migration expansion, comprising: abstracting the industrial edge network into an intelligent industrial network model composed of heterogeneous edge nodes and links; modeling industrial application requests as request chains composed of multiple microservices with data dependencies; calculating microservice instance deployment schemes and request routing schemes; statistically analyzing time-varying request flows; and utilizing a method based on... m / m / c This invention utilizes a multivariate performance analysis model of queue networks and a binary search algorithm to analyze and statistically determine the minimum number of cores that satisfy latency constraints. It then dynamically scales and adjusts the core resources of deployed microservice instances. Based on the preliminary dynamic scaling and adjustment results and migration costs, it solves a mixed-integer nonlinear programming migration decision problem to optimize the optimal collaborative deployment and request routing of microservice instances among edge nodes. This invention improves the service continuity and overall energy efficiency of industrial edge network systems.

The application provides a method and system for improving the diversity of bit-level autoregressive image generation, and relates to the technical fields of artificial intelligence and computer vision, and has the characteristics that in the sampling process of a bit-level autoregressive image generation model, for each generation scale k, the original prediction logits of all token bits at the scale are obtained; based on the original prediction logits, an adaptive temperature coefficient τk is dynamically solved by a binary search algorithm, so that after the logits are scaled by the τk and normalized by softmax, the difference between the actual average maximum bit probability of the current scale k and the preset target average maximum bit probability Sk is less than the preset tolerance; an adaptive temperature coefficient τk is dynamically determined by binary search, so that after the softmax normalization is applied to the τk. The application has the advantages that the generation diversity is improved by adaptively smoothing the early prediction distribution, and the visual quality is maintained by means of energy-based path search; the method mainly operates in the early stage with low computational overhead, and the inference delay is only slightly increased, and the core design can be extended to similar autoregressive generation models.

The invention discloses an over-path traffic solving method for a completely-crowded large-scale public transportation network, and the method comprises the steps: obtaining a getting-on arc and a corresponding effective departure frequency through a first algorithm; the second algorithm calculates the use probability of passing through all the upper turning arcs under the super path, so that the complete upper turning arc flow distribution of the super path, the use probability vector of the upper turning arcs and the use probability vector upper turning arcs of the nodes are obtained; then, adopting column generation to construct an OD pair sub-problem, and determining the optimal transfer amount from a non-reference super path to a reference super path in the OD pair sub-problem through binary search; and the fourth algorithm obtains an over-path traffic equilibrium solution under the public transportation network equilibrium condition. Therefore, by setting the first algorithm, the second algorithm and the like, a complete algorithm capable of processing large-scale public transportation network distribution is constructed, so that the super path is constructed based on the effective departure frequency, and the method is suitable for practical application of the city-level large-scale public transportation network.

The invention discloses a photovoltaic array capacity optimization method and device for a solar lifting irrigation system, relates to the field of new energy, and is used for minimizing photovoltaic array installed capacity design and energy storage distribution reduction. The method comprises the following steps: acquiring basic parameters of a solar lift irrigation system, and correcting peak water power of the system based on the basic parameters to obtain basic photovoltaic array installed capacity; under the condition that the daily water supply constraint condition is met, the minimum feasible photovoltaic array installed capacity and the corresponding energy storage configuration are calculated through a binary search method based on the basic photovoltaic array installed capacity with the purpose of minimizing the photovoltaic array installed capacity and the energy storage capacity. The method is simple in process, high in pertinence, robust in optimization result, easy to deploy and high in expansibility.

The embodiment of the invention provides a mobile edge computing uplink communication and computing joint optimization method and related equipment, and belongs to the technical field of wireless communication and edge computing. The method comprises the following steps: constructing a base station equipped with a steerable antenna array and an uplink mobile edge computing system model of multiple terminals; deriving a maximum calculation time delay expression of the system; establishing a joint optimization mathematical model by taking minimization of the time delay as a target; for a non-convex problem, an alternating optimization framework is adopted to decompose the non-convex problem into a calculation side sub-problem and a communication side sub-problem for iterative solution; wherein the calculation side sub-problem is solved through a closed-form solution and a convex optimization technology; the communication side sub-problem further optimizes beam forming through positive semidefinite relaxation and binary search, and optimizes antenna orientation through fractional programming and continuous convex approximation. According to the invention, through collaborative optimization of antenna space orientation and communication computing resources, a wireless channel is actively improved, the maximum computing delay of the system is effectively reduced, and the service capability of the system for low-delay services is improved.

The application belongs to the technical field of safe operation analysis of power distribution system, and particularly discloses a power distribution network safety domain evaluation method and system considering double-end tie-in backup, which comprises the following steps: constructing a power distribution network model containing distributed power supply and energy storage system under double-end tie-in, performing linear extrapolation on the safety boundary distance searched by the first two rays to predict the safety boundary distance of the current ray; constructing an adaptive reduced search interval; if the safety check is passed, performing standard dichotomy search in the adaptive reduced search interval to finally locate the safety domain boundary point in the direction of the current ray; calculating the discrete curvature of each safety domain boundary point and the chord-length-curvature error between two adjacent boundary points to determine whether local encryption is triggered; and performing safety domain boundary search on the encrypted curve again to obtain the final power distribution network safety domain. The application can maintain search robustness when boundary prediction fails through endpoint safety check and full-interval back-off mechanism.

The application discloses a capacity-limited unmanned aerial vehicle charging pile optimal distribution method. Under the condition that the spatial positions of unmanned aerial vehicles and charging piles and the capacity constraint of the charging piles are known, the method firstly determines the maximum flight distance constraint allowed by the unmanned aerial vehicles, and constructs a feasibility judgment model based on network flow under the distance constraint, which is used for judging whether there is a charging distribution scheme of the unmanned aerial vehicles meeting the capacity constraint; the maximum flight distance is subjected to dichotomy search, and the feasible distance range is gradually reduced, so that the charging scheduling result of minimizing the maximum return flight distance of the unmanned aerial vehicles is determined. The application can effectively reduce the system scheduling complexity under the premise of ensuring that all unmanned aerial vehicles complete the charging distribution, improve the efficiency and stability of large-scale unmanned aerial vehicle cluster charging scheduling, and is suitable for high-concurrency and capacity-limited unmanned aerial vehicle charging application scenarios.

The application discloses an address matching method and device, a storage medium and a program product, and belongs to the technical field of communication. In the method, the address to be matched is matched with a hash table corresponding to a first node in a binary search tree. If the address matches a target prefix mark in the hash table corresponding to the first node, heuristic information corresponding to the target prefix mark is obtained. The heuristic information refers to information associated with at least one heuristic information node. The at least one heuristic information node is a node corresponding to a hash table in which a prefix of the target prefix mark is projected. A longest prefix matched with the address is found based on the heuristic information corresponding to the target prefix mark. Since the target prefix mark corresponds to heuristic information, the search range can be reduced based on the heuristic information, and it is not necessary to traverse all nodes on a right subtree of a node corresponding to the hash table in which the target prefix mark is located. Therefore, the number of traversed nodes can be reduced, and the routing search efficiency is improved.

The application relates to a method, system and device for allocating a maintenance aircraft parking position and a storage medium, wherein the method comprises the following steps: acquiring a data set corresponding to the maintenance aircraft; encoding the arrangement order and the safety distance of the maintenance aircraft based on the data set through an encoding mechanism to obtain a corresponding target encoding mode; optimizing the arrangement order of the maintenance aircraft to obtain a candidate solution set and a target hangar utilization rate corresponding to the candidate solution set, with the maximum hangar utilization rate as an optimization target; optimizing the safety distance of the candidate solution set through a safety distance fast optimization algorithm based on a dichotomy search iteration to obtain an optimal safety distance and an arrangement order corresponding to the optimal safety distance; and inputting the optimal safety distance and the arrangement order corresponding to the optimal safety distance into an aircraft arrangement strategy based on a matching degree to arrange the maintenance aircraft and obtain a target arrangement scheme. The application is beneficial to improving the allocation efficiency of the aircraft parking position.

The invention belongs to the technical field of projection, and particularly relates to a projection keystone correction method for efficiently solving a maximum inscribed axis aligned rectangle, which comprises the following steps: acquiring four vertex coordinates of a distorted image generated by projection, and determining a corresponding distorted quadrangle; calculating an inner side half-plane equation of each edge of the distorted image; determining vertex coordinates of a distorted image boundary bounding box; initializing the maximum zoom factor and the minimum zoom factor of the zoom factor of the rectangle to be measured; calculating a maximum feasible scaling factor through binary search; determining four vertex coordinates of the maximum inscribed axis aligned rectangle; and mapping a distorted quadrilateral region corresponding to the distorted image into the maximum inscribed axis aligned rectangle, and realizing final geometric correction on the projection trapezoid. According to the scheme, the huge calculation amount and precision dependence in an exhaustion method are avoided, and the calculation speed and the real-time performance are greatly improved; the method is suitable for a complex distortion situation caused by any posture of the projector, and has good robustness and universality for various projection environments.

The invention discloses an incomplete constraint vehicle path planning method based on a computing resource constrained environment, and solves the problems of computing resource waste, easy local optimum and insufficient scene adaptation of an existing grid sampling method. The method is applied to a qualified area scene with a tolerance range, and comprises the following steps of: defining a fuzzy target domain and a linear search interval which are formed by an ideal center point and the tolerance range, constructing a cost evaluation function containing factors such as path length and gear shifting times, generating a tentative path by adopting interval binary search iteration, and reducing the interval according to a cost trend, so as to obtain a tentative path; after the optimal target point is locked, a Reed-Shepp path is generated; and the search precision is dynamically adjusted through the processor load rate. The method does not need full sampling, reduces calculation overhead, adapts to resource-limited environments such as a vehicle-mounted low-end chip and embedded teaching equipment, and is especially suitable for low-speed close-range path planning such as back-up parking and side parking in a driving training scene.

Methods and apparatus determine a location of a boundary of a given material in a sample, based on classification of reciprocal space images at respective positions. A diffraction image at a given position is classified to identify a material at that position. Imaging and classification at multiple positions can quickly and reliably find the boundary with sub-micron accuracy. Binary search provides speed-up. Classification is performed by neural network. The technique is suitable for distinguishing monocrystalline, polycrystalline, and amorphous silicon, high-Z materials (tungsten), or low-Z materials (carbon), among others. The technique integrates into automated workflows, with precise positioning of further imaging, probing, or milling operations based on the located boundary. Examples and variations are disclosed.

The invention relates to clock synchronization, in particular to a low-complexity clock offset synchronization method for quantum key distribution, which comprises the following steps: Alice and Bob agree in advance to determine the maximum level of maximum recoverable offset and interleaving degree; the Alice sends a starting signal to the Bob through the data channel; alice generates a synchronization mode and sends the synchronization mode to Bob through a quantum channel; after Bob receives the starting signal, single photon events are collected, and clock skew is recovered by adopting a binary search algorithm; according to the technical scheme provided by the invention, the defects of high calculation complexity, high resource consumption and need of a large amount of information interaction in the prior art can be effectively overcome.

The invention discloses an impedance correction system and method based on segmented multi-type offset compensation, and belongs to the technical field of electronic measurement. The method comprises the following steps: configuring multi-mode segment compensation, and creating a plurality of time domain segments capable of independently setting offset types; dynamically generating a slope compensation formula, and automatically calculating linear formula parameters according to starting and ending values input by a user; intelligent pre-verification is carried out, and real-time check and early warning are carried out on segment interval continuity and type conflicts; and performing efficient compensation calculation, positioning the segment to which the current time point belongs by using binary search, and performing addition, multiplication or slope compensation calculation according to the segment type. According to the method, the problems that the existing impedance correction technology is single in compensation mode and cannot adapt to complex time-varying scenes are solved, and the precision and the flexibility of impedance measurement are remarkably improved through a segmented multi-type hybrid compensation mechanism.

The invention discloses a method and system for adjusting an anti-surge valve of a turbine compressor, electronic equipment and a medium, and the method comprises the steps: monitoring the operation power of the compressor in real time, comparing the operation power with preset protection surge power and a power dead zone boundary, and automatically selecting an opening or closing adjusting mode of the anti-surge valve according to power deviation; a historical stable opening degree concept is introduced, the target opening degree is calculated in combination with a binary search algorithm, and the valve can be rapidly and accurately adjusted to the optimal position; the valve position is continuously optimized through an intelligent learning mechanism, and energy consumption is remarkably reduced while safe operation of the compressor is ensured; the problems that traditional anti-surge control is lagged in response and insufficient in adjusting precision are effectively solved, and the method has the advantages of being high in self-adaption and good in energy-saving effect.

The invention discloses a tensegrity unmanned aerial vehicle air-drop trajectory planning method, and belongs to the technical field of unmanned aerial vehicle control, and the method comprises the steps: unconstrained analytical solution: constructing a trajectory planning problem into a time-optimal minimization Jerk problem under the condition of neglecting the kinematics constraints such as speed, and solving the minimization Jerk problem; obtaining the theoretically optimal trajectory and the shortest time T0 thereof by solving a quintic polynomial; and carrying out constrained iterative optimization, taking T0 as a search lower bound under the condition that all kinematic constraints are met, adjusting the total duration of the trajectory through iterative methods such as binary search until the shortest feasible time T * meeting all the constraints is found, and generating a final trajectory. According to the method, the complex non-convex optimization problem is decomposed into two stages of analytical solution and iterative optimization, the strict requirement for accurate control of the tail end speed when the tensegrity unmanned aerial vehicle executes the air-drop task is met, and the task success rate and safety are improved.

The application discloses a kind of based on the joint optimization method of transmitting beam and RIS discrete phase shift matrix of dual-function radar and communication system, the method includes the following steps: constructing intelligent reflecting surface assisted dual-function radar and communication system, under the constraint of sensing and communication, constructing the joint optimization problem of transmitting beam shaping vector and phase shift matrix;For beam shaping vector, based on dichotomous search algorithm, approximate optimal closed solution solving method is constructed using Lagrange dual decomposition method, global optimal solution is obtained;Quantize the discrete phase shift matrix of RIS, based on optimization minimization method, convert quadratic constraint quadratic programming into semi-definite relaxation problem for solving, complete the alternate optimization process of target problem solving.The application improves the radar detection performance of DRC system in the path loss serious environment by the deployment of RIS, jointly optimizes RIS phase shift matrix and beam shaping vector, and proposes RIS discrete phase shift design method to reduce hardware complexity, effectively improves the performance of DRC system.

The application discloses a media scanning task execution method and device, equipment and medium, relates to the multimedia playing technical field, and comprises the following steps: triggering a media scanning service, using a dichotomy search algorithm to traverse a target directory of an external storage device to obtain a target subdirectory; storing file information to be parsed selected from first file information of the target subdirectory in a first queue; a parsing thread pool parses the file information to be parsed to obtain parsed file information, and a storage thread generates a database operation object from the parsed file information and stores the database operation object in a second queue; a copy of the database operation object is saved in an operation array, the copies in the operation array are processed in batches, a target identifier corresponding to the copies is generated and saved in a third queue; and media file information in a media database is updated based on the target identifier, so that the media scanning task is completed. The media scanning task execution speed is improved, and the media file information loading speed is improved.

The embodiment of the invention provides a large model reasoning load balancing method and device based on iterative search, equipment and a storage medium, and the method comprises the steps that a reasoning task set and the number of calculation units are obtained, according to the reasoning task set, determining the total calculation amount of all reasoning tasks in the reasoning task set and the maximum single task calculation amount; based on the total calculation amount of all the reasoning tasks, the maximum single task calculation amount and the number of the calculation units, the maximum distribution capacity threshold value of the calculation units and the reasoning tasks distributed to the calculation units and corresponding to the maximum distribution capacity threshold value are determined through a binary search iterative algorithm; the distributed reasoning tasks are sent to all the calculation units, so that all the calculation units execute the distributed reasoning tasks and output reasoning results, load planning is continuously optimized through global iterative search, loads among all the calculation units are better balanced, the maximum scheduling length is reduced, and idle resources are reduced.

This application discloses a sparse adaptive reconstruction method based on dynamic adjustment and binary search. This method obtains compressed observations by constructing a random Gaussian observation matrix and uses discrete wavelet transform to sparsely represent the original signal. During the iterative reconstruction process, this application introduces for the first time a dynamic adjustment mechanism for the cumulative energy ratio atoms guided by a dynamic scaling factor, and employs a binary search strategy to achieve efficient sparse estimation. This method successfully creates a power quality disturbance signal reconstruction scheme that simultaneously possesses sparse adaptiveness, fast convergence, and high robustness to noise. Compared with methods such as OMP and the original SAMP, this method can reduce the number of iterations by 60%–80%, improve the reconstruction signal-to-noise ratio by 8–12 dB, and reduce the root mean square error by 10%–25%. It exhibits higher robustness and real-time performance in power quality disturbance signal reconstruction and is suitable for scenarios such as compressed sampling, edge computing, and high-speed signal reconstruction in power quality monitoring systems.

This invention discloses a secure covert communication method based on cognitive radio, investigating a delay-tolerant relay covert unmanned aerial vehicle (UAV) and a cognitive radio framework involving multiple colluding eavesdroppers and listeners. In this framework, a legitimate UAV acts as an airborne relay, enabling communication when the direct link between the ground transmitter and receiver is blocked. Subsequently, considering the uncertainty of the locations of multiple eavesdropping and listening nodes, a robust optimization problem is constructed. By jointly optimizing the UAV's trajectory and power, and the transmitter's transmission power, a tractable version is constructed using Pinsk inequalities, Jensen inequalities, and a binary search method for extremely complex covert constraints. Following this, an algorithm based on alternating optimization is proposed to solve the optimization problem. Achieving low complexity, algorithms based on primal-dual search and continuous convex approximation are designed for each subproblem. Numerical results demonstrate the effectiveness of our proposed algorithm.

The invention relates to a road width calculation method and system, electronic equipment and a storage medium, and relates to the technical field of oil and gas geophysical exploration and acquisition. The road width calculation method comprises the following steps: constructing a polygon structure of a road of which the width is to be calculated according to road data; constructing a model for determining the road width, wherein the model comprises decision variables, constraint conditions and a target function; determining a preset area tolerance value; calculating a critical buffer distance based on the model by adopting a binary search algorithm, wherein the critical buffer distance is a corresponding buffer distance when the buffer area is smaller than or equal to a preset area tolerance value; and calculating the width of the road according to the critical buffer distance. According to the method, road width calculation is converted into a mathematical optimization problem, traditional road width calculation depending on experience or subjective parameters is converted into a quantitative process with clear logic, subjective interference caused by manual parameter setting is thoroughly avoided, and objectivity and accuracy of a calculation result are ensured.