11 results about "Dichotomic search" patented technology

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 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 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.

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.

Based on the integration of photovoltaic inverter high and low voltage ride through control parameters and electrical parameters identification method, including: building photovoltaic inverter semi-physical test platform, and under different conditions of high and low voltage ride through test, get the data set required for parameter identification; With the current and power measured value under high and low voltage ride through as the optimization target, the hybrid frog leap algorithm is adopted (the control parameters under corresponding control mode are identified respectively; According to the measured voltage value under high and low voltage ride through as the optimization target, the improved dichotomy search method is adopted to optimize the fault impedance, so that the simulation voltage and the measured voltage tend to be consistent; The PSASP photovoltaic mechanical model is established and the control parameters and electrical parameters identification results are brought in, and the error value of voltage, current and power under corresponding control mode is calculated. This method realizes the batch automatic identification and accurate setting of new energy mechanical and electrical simulation model impedance under voltage drop multi working condition, greatly improves the multi working condition setting precision and data acquisition efficiency of new energy mechanical and electrical simulation model.