6 results about "Sequence search" patented technology

The present disclosure provides a biomolecular sequence searching method and apparatus, a device, and a storage medium. The method comprises: acquiring an unknown biomolecular sequence; inputting the unknown biomolecular sequence into a sequence encoding model for sequence encoding, to obtain an unknown biomolecular sequence representation; performing similarity searching on different candidate vector sets in a biomolecular sequence vector database by means of the unknown biomolecular sequence representation, wherein candidate biomolecular sequences of candidate vectors in the candidate vector sets have a same sequence length; on the basis of the similarity searching result, searching each candidate vector set for a preset number of known biomolecular sequence representations; and screening known biomolecular sequences corresponding to the plurality of known biomolecular sequence representations for homologous biomolecular sequences corresponding to the unknown biomolecular sequence.

This invention discloses a dynamic phase sequence spherical decoding multi-step predictive control method for common-mode voltage suppression. It proposes incorporating a hard constraint mechanism for common-mode voltage during the search process, effectively suppressing common-mode voltage by pruning high common-mode voltage branch nodes, thus overcoming the problem of excessively high common-mode voltage in traditional spherical decoding predictive control. The method's computational reduction effect becomes more significant with increasing prediction step size. A dynamic phase sequence search strategy is proposed, periodically rotating the search phase sequence to achieve a uniform distribution of inverter switching frequency and reduce the risk of local overheating of the converter. This invention also proposes setting a hard constraint on the upper bound of the number of search nodes for spherical decoding predictive control, which can limit the algorithm's search time as needed and avoid a surge in the number of search nodes under operating condition disturbances. Simulation results based on a three-phase five-level active neutral-point clamped inverter verify that this method can achieve uniform switching frequency distribution, common-mode voltage suppression, capacitor voltage balance, and significantly reduce computational load.

The application provides a menu data acquisition method and device, relates to the technical field of data processing, and can be applied to the financial field or other technical fields.The method comprises the following steps: in response to an execution action of a target menu sequence searched by a user through a menu keyword, obtaining a candidate menu list corresponding to the menu keyword; calculating the similarity between each character data in the candidate menu list and the menu keyword to obtain a first menu sequence similar in semantics to the menu keyword; and generating the target menu sequence according to a second menu sequence containing historical click rate data corresponding to the user and the first menu sequence obtained in advance.The device executes the above method.The menu data acquisition method and device provided in the embodiment of the application can quickly and accurately find the menu data required by the user.

The application discloses a kind of optimal odd complementary sequence pair search method, framework, storage medium and equipment, belong to the cross field of signal processing and artificial intelligence, which comprises: initialization sequence prefix, search is carried out by the selection, expansion, evaluation, back transmission steps of MCTS;Wherein, evaluation step uses CNN to directly estimate the value of current sequence prefix, avoid the high computing overhead caused by random completion in traditional MCTS;The state, strategy and return information generated in the search process are independently managed and fixed length processing by replay pool, guarantee the stability and generalization ability of CNN training under different length sequence input;And update CNN parameter in closed loop mode, continuously optimize search strategy.The application can efficiently and stably search out optimal odd complementary sequence pair satisfying Krammer lower bound in the field of radar signal design, wireless communication channel estimation and synchronization, etc., significantly improve the efficiency and engineering practicability of sequence search.

A wind-solar carbon flow correlation analysis method and system based on PLHS sampling and sample optimization, comprising: constructing a wind-solar output probability distribution model; constructing a system carbon flow rate comprehensive analysis model under the coupling uncertainty of wind-solar output; using a hierarchical Latin hypercube sampling method to sample wind speed and light intensity to obtain a sample sequence; an adaptive sequence search algorithm is proposed, a composite index based on spatial dispersion is used as an optimization target to optimize the sample sequence, and the sample sequence is input into the wind-solar output probability distribution model to obtain a wind-solar output sample set; traversing the sample points in the wind-solar output sample set, the system carbon flow rate and its probability distribution characteristics are calculated; for each sample point in the wind-solar output sample set, the change amount of the system node, branch and network loss carbon flow rate caused by the wind-solar output injection is calculated respectively, and the weighted average of the change amount is obtained to obtain the average influence factor of the wind-solar output on the node, branch and network loss carbon flow rate. The present application realizes reliable evaluation of system carbon emission.

The application discloses a diffusion model reasoning acceleration method based on optimal time step sequence search and knowledge distillation, which constructs a unified search space covering time step sequences and corresponding model architecture configurations without overall fine-tuning of a pre-trained diffusion model, and searches for optimal time step sequences. Based on the optimal diffusion time step sequences obtained through the search, a knowledge distillation training method is designed, a main distillation loss function is constructed within a discrete time step subspace defined by the optimal diffusion time step sequences, and an adjacent time step consistency loss is introduced to relieve the discrete error introduced by a non-uniform time step span. In the reasoning stage, the teacher model is frozen, and the distilled student model is combined with an efficient sampler ACDMS based on UniPC and fusing flow matching dynamic correction to perform limited step sampling on the optimal time step sequence, so that reasoning acceleration is realized under the condition of keeping generation quality.