34 results about "Sequence search" patented technology

The invention discloses a multi-target multi-bar truss optimization method based on single-target sequence search assistance. The method comprises the following steps: preliminarily locking an angular solution region by using an angular solution search mechanism; introducing a crossover operator to communicate with a population history optimal individual to generate an excellent individual; a mutation operator is introduced, so that the population is more diversified; an adaptive strategy is introduced, so that the offspring population is more excellent; external archives are introduced to improve the error-tolerant rate during individual selection; the angular solution quality is improved by adopting an angular solution detection mechanism; using the obtained angular solution to guide a multi-target algorithm to carry out further diversity search; selecting a plurality of non-dominated solutions using a non-dominated sorting method and the congestion distance; and evaluating the result on a plurality of test problem sets. A two-stage search mode is adopted, in the first stage, targets are searched in sequence on the whole, and an angular solution and a non-dominated solution are obtained; in the second stage, the solution obtained in the first stage serves as an initial population, evolution is conducted through a multi-objective optimization algorithm, and therefore better convergence and non-dominated solution diversity are achieved.

The invention discloses a diffusion model reasoning acceleration method based on optimal time step sequence search and knowledge distillation, which constructs a unified search space covering a time step sequence and corresponding model architecture configuration on the premise of not performing overall fine adjustment on a pre-trained diffusion model, and searches an optimal time step sequence. And designing a knowledge distillation training method based on the optimal diffusion time step sequence obtained by searching, constructing a main distillation loss function in a discrete time step subspace limited by the optimal diffusion time step sequence, and introducing adjacent time step consistency loss to relieve discrete errors introduced by a non-uniform time step span. In the reasoning stage, a teacher model is frozen, a distilled student model is combined with an efficient sampler ACDMS based on UniPC and fused with flow matching dynamic correction, finite step sampling is carried out on an optimal time step sequence, and reasoning acceleration under generation quality maintenance is achieved.

The invention discloses a gene feature extraction method in gene data based on sequence search, and relates to the technical field of biological information. The problems that gene data is wide in source and diversified in format, data processing is extremely complex, data of different formats are difficult to integrate and analyze, and the accuracy and efficiency of feature extraction are affected are solved. According to the method, gene data are comprehensively preprocessed, low-quality and redundant parts are removed, reliable data quality is ensured, data distribution and data conversion are performed at the same time, high-similarity gene feature regions are accurately screened through sequence comparison, importance weights of gene features are determined by using clustering group features, key features are reasonably screened, and the accuracy of gene feature extraction is improved. Data dimensions are effectively reduced, the feature extraction efficiency and accuracy are improved, local and global features are fused to construct a comprehensive feature vector, the feature expression ability is enhanced, a screening result is verified by constructing a test data set, and the accuracy and reliability of the gene feature extraction method are continuously improved.

The invention discloses a hybrid sorting method and system integrating field embedded search and keyword search, and the method comprises the steps: selecting a text embedded model of a general field, and carrying out the field fine tuning of the embedded model; performing embedding expression on the search resources by using the fine-tuned domain embedding model, and storing vector data in an index database; constructing a keyword index for the search resources, and storing the keyword index in an index database; customizing a field retrieval sequencer for hybrid embedded search and keyword search, weighting search result sequencing scores according to data use preference characteristics, and sequencing search resources based on a final scoring result; the system comprises a fine tuning module, a storage module and a sorting module. According to the method, the search engine can better understand field professional contexts and semantics and can adapt to field professional sorting requirements; the semantic correlation and the keyword correlation are considered for sorting, so that the search efficiency is high, and the sorting result is more scientific.

The invention discloses a subsequence searching method, a comparison method, a system and equipment of a gene sequence. The subsequence searching method comprises the following steps: acquiring a preset number of sequencing data of a to-be-searched gene sequence; sequentially acquiring basic group data of a search interval corresponding to each piece of sequencing data on the reference gene sequence, and searching based on an acquisition result; the search interval corresponding to each piece of sequencing data is determined based on the to-be-searched base sequence of each piece of sequencing data; repeatedly obtaining the base data of the search interval of the next search, and searching based on the obtained result to obtain a target sub-sequence; the search interval of the next search is determined according to the next to-be-searched alkali of each piece of sequencing data and the search interval of the previous search. According to the search method, the basic group data of the search interval is obtained in advance, the sequencing data is processed in batches, calculation of other sequencing data can be processed when the prefetch result is waited, and the gene search efficiency is improved.

The embodiment of the invention provides a sequencing data file compression method and device and a storage medium. A compression scheme for a sequencing data file is provided, and for each sequencing sequence contained in the sequencing data file, at least two matching components are used for cooperatively determining a reference fragment for the same sequencing sequence on a reference sequence; on the basis of the determined reference fragment, comparison information between the sequencing sequence and the reference fragment can be constructed, and each piece of comparison information constructed under the to-be-compressed file is compressed. Therefore, through cooperative work of the at least two matching components, the efficiency of searching the reference fragment for the sequencing sequence can be improved, the matching results can be mutually verified among the matching components, and the matching accuracy of the reference fragment can be effectively improved, so that the compression ratio of the sequencing sequence is improved, and the compression ratio of a sequencing data file is further improved.

The invention provides a memory parking loopback detection method comprising the following steps: obtaining a pre-stored global track point set, track points comprising two-dimensional coordinates and course angles; starting from the current position of the vehicle, performing inverted search on global track points, and positioning a track point closest to the vehicle as a path planning starting point; traversing the global track point set, and storing the column index appearing for the first time by taking the two-dimensional coordinates of the track points as hash keys; when encountering points with the same two-dimensional coordinates and different course angles again, judging the points as path intersection points; if the path intersection is detected, marking indexes m and n, and deleting track points between m and n to eliminate the loopback path; and generating a local path of a first preset distance based on the cut trajectory, and outputting the local path to a vehicle control system to execute tracking. According to the method, sensor data are replaced by the track point coordinates / course angles, a camera / laser radar is omitted, and the computing power demand is greatly reduced. The comparison complexity is reduced through hash table optimization, and low-computing-power chip deployment is supported.

The application discloses a user operation log data exception identification method and device, medium and product, wherein different logs in acquired user operation log data are taken as network nodes, mutual information between different nodes is calculated, a non-directional edge is determined according to the mutual information between different nodes, a non-directional minimum support tree is constructed, nodes in the non-directional minimum support tree are oriented, a preliminary minimum support tree structure is determined, node sequence groups are obtained by performing node sequence search in the minimum support tree structure, different node sequences are taken as different individuals in an initial population, the fitness of different individuals in the initial population is calculated, the initial population is updated according to the fitness of different individuals and a preset population optimization strategy, and the node sequence of an individual with the maximum fitness in the updated population is taken as a user operation exception log. The application can improve the optimization efficiency and optimization accuracy.

A siRNA inhibition rate prediction method based on antisense chain multidimensional embedding representation, in the offline stage, a deep neural network is constructed and a multidimensional feature is constructed for the antisense chain sequence of siRNA for training, in the online stage, given the target gene name, all candidate siRNA sequences are obtained, and the trained deep neural network is used to predict the real-time input of the candidate siRNA sequence and sort the silence efficiency. The present application uses one-hot encoding and pre-training RNA-FM model embedding representation features as input for the antisense chain sequence of siRNA, constructs a siRNA inhibition rate prediction model in the form of a deep neural network, improves the effectiveness and accuracy of the prediction, and fuses it with the gene expression sequence search algorithm to construct a complete process from the target gene name input to the screening of efficient siRNA sequences.

The application belongs to the technical field of natural language processing and information extraction, and specifically relates to a fine-grained entity extraction method and system for complex documents, which comprises the following steps: obtaining an OCR text box set of a document image, extracting text content and coordinate information of each text box, and fusing the text features and visual features to generate a multi-modal fusion feature matrix; calculating geometric position relationships according to the coordinate information of each text box, modeling and fusing spatial correlations by using a multi-scale kernel function to generate a spatial bias matrix; dividing all attention heads into geometric constraint heads and global free heads, calculating attention and fusing after multi-head linear projection to obtain context-enhanced features; and calculating label emission scores, combining sequence constraint values to optimize model parameters, and outputting entity extraction results through global optimal sequence search. The application does not require external pre-training data, has small parameter quantity and fast reasoning speed, and can be used for entity extraction of complex documents such as government forms and commercial bills.

The present invention discloses a multi-wavelength phase unwrapping method and an object height measurement method and height measurement system. The multi-wavelength phase unwrapping method is used to obtain the optimal phase sequence of the coordinates at the surface of the object to be measured at the optical wavelength based on a multi-wavelength off-axis digital hologram of the object to be measured at the optical wavelength, using a height distribution model based on synthetic wavelength chain guidance and phase sequence search: the height distribution of any coordinate at the surface of the object to be measured at the optical wavelength in the hologram is used as an initial value, and a phase sequence is searched for at a certain interval within a preset range of the initial value. The phase sequences found by the search are used to form a criterion function. When the minimum value of the envelope of the criterion function is taken, the corresponding phase sequence is considered to be the optimal phase sequence. The present invention determines the optimal phase sequence by searching for the minimum value of the envelope of the criterion function, rather than by finding the minimum value of the criterion function. This greatly solves the problem of errors in the optimal phase sequence caused by noise damage to the criterion function.

The present invention provides a causal interpretation method and device for deep knowledge tracing based on genetic algorithms, including: constructing a causal attribution measurement framework. Genetic encoding operation, converting the interpretable problem of deep knowledge tracing into an optimal sub-sequence search problem for genetic algorithm to solve; initialization population operation; universality evaluation operation, performing universality evaluation on the encoded population to generate offspring and their corresponding individual causal effect values ​​and storing them in the experience matrix; individual selection operation, introducing penalty terms to generate a sparser offspring; adaptive crossover operation; based on the current number of iterations, the position of the basis and the causal correlation value of the experience matrix to guide the offspring to complete the adaptive mutation operation; decoding operation on the output final individual to interpret the subsequence and causal effect value. The present invention combines the causal framework and adopts the out-of-the-box heuristic algorithm of genetic algorithm to achieve knowledge tracing that is readable, efficient, flexible and faithful.

The present invention discloses a method for automatic wiring and optimization of superconducting quantum chips, belonging to the field of automated design of superconducting quantum chips. In the modeling phase, the method adopts a "combined wiring template" model under a fine-grained grid. The combined wiring template is used to discretize the problem, avoiding the complex geometric operations in the arc wiring problem solution process and significantly reducing the algorithm's search space. In the legal solution search phase, a one-sided wiring algorithm is adopted. Based on the wiring result characteristics of the algorithm, the line sequence search problem is extended and a line sequence tree search framework is designed. On this basis, the blocking relationship between lines is explored and a series of search optimization strategies are designed. An exchange winding action is adopted to meet the special line sequence requirements of the read line. In the wiring optimization phase, an iterative optimization wiring scheme based on space constraints is adopted. Based on the legal solution, the overall wiring result is optimized at multiple levels of objectives to ensure that the wiring result meets the design requirements.

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.

The invention provides a multi-target antibacterial peptide sequence optimization method and system. The method comprises the following steps: constructing a sequence search tree based on an initial peptide fragment sequence; scoring the nodes, and selecting the current node; performing point mutation operation on the current node; copying each candidate peptide fragment into a corresponding sub-population based on an improvement demand, performing local optimization to obtain new candidate peptide fragments, and evaluating each new candidate peptide fragment; scoring each node again according to the evaluation result, and reselecting the current node; and when an iteration stop condition is met, selecting a peptide fragment sequence based on the score and outputting the peptide fragment sequence. According to the application, antibacterial peptide sequence mutation is modeled into a tree structure search path, and multi-target co-evolution is introduced in a simulation stage, so that efficient coupling between global search and attribute balance is realized, joint modeling can be performed on pharmacological attributes such as antibacterial activity, host toxicity and half-life period at the same time, and efficient and refined optimization of the antibacterial peptide sequence is completed.

The invention discloses an interrupt drive program atomicity violation detection method based on a partial order guide event graph, which comprises the following steps: acquiring a symbolized memory event in a program to be detected, and extracting a partial order of the symbolized memory event; based on the partial sequence, identifying a potential atomic violation event group from the symbolized memory events to obtain a key rf sequence; generating a skeleton of the event graph based on the partial sequence, and expanding edges of the event graph to obtain a stable event graph; and searching the stable event graph according to the key rf sequence to obtain an actually occurring atomic violation event. According to the method provided by the invention, the event graph of the SME is generated through the partial sequence, and the event graph is searched based on the rf sequence of the potential atomicity violation event group to detect the actually occurring atomicity violation event; the partial order relationship between events is visually represented, so that the interpretability of the detection process can be improved; moreover, the implementation cost is low, the adaptability is good, and the detection precision is high.

The application discloses a search method and system for a Costas sequence based on multithreading, and the method comprises the following steps: inputting the order of the Costas sequence to be searched; establishing a framework data structure of a bidirectional linked list, and generating a permutation matrix corresponding to the order through recursive iteration; generating a task for judging a check matrix corresponding to the permutation matrix, and submitting the task; submitting the task received by S2 and S3, creating a thread pool by using a thread pool technology, and performing multithread operation by combining a task stealing technology, so as to accelerate the judgment on the check matrix; and collecting the tasks, finally obtaining the number of the Costas sequences and the search time, and comparing with a traditional multithread search. The search method and system for the Costas sequence based on the multithreading realize efficient utilization of threads, improve the search speed, and provide a wider application prospect.

The invention relates to the field of signal sorting, and provides a reliable extraction and utilization method of complex pulse stream sequence features, and the whole process is divided into three stages of feature sequence preprocessing, feature extraction and feature utilization. For feature sequence preprocessing, PA sequence coarse segmentation, outlier removal, smooth noise reduction, sequence characterization and approximate equal interval processing are carried out; for extraction of complex pulse flow sequence features, from the perspective of a time sequence, possible complex pulse flow sequence features in a radar sample database are mined through similarity measurement and complete sequence search of the sequences; for the utilization of complex pulse stream sequence features, the features have certain randomness, are rough and are difficult to be finely applied to signal sorting, simple fuzzy matching is adopted to extract target pulse data, and signal sorting is completed. According to the method, reliable extraction and utilization of complex pulse sequence features are realized, and the signal sorting accuracy can be further improved.

The invention discloses an optimal odd complementary sequence pair searching method, a framework, a storage medium and equipment, and belongs to the crossing field of signal processing and artificial intelligence, and the method comprises the following steps: initializing a sequence prefix, and carrying out searching through the steps of MCTS selection, expansion, evaluation and return; according to the evaluation step, CNN is adopted to directly carry out value estimation on a current sequence prefix, and high calculation overhead caused by random completion in a traditional MCTS is avoided; state, strategy and return information generated in the search process are subjected to independent management and fixed-length processing through a playback pool, and the stability and generalization ability of CNN training under input of sequences of different lengths are guaranteed; cNN parameters are updated in a closed-loop mode, and a search strategy is continuously optimized. In the fields of radar signal design, wireless communication channel estimation and synchronization and the like needing high-performance sequences, the optimal odd complementary sequence pair meeting the Cramer-Rao lower bound can be efficiently and stably searched, and the sequence searching efficiency and the engineering practicability are remarkably improved.

The present invention discloses a method, system and medium for reducing the search space of compilation option sequences. The present invention includes sequentially enabling programs in a single compilation option sampling template program set, and obtaining speedup data relative to a preset compilation option sequence under each compilation option; calculating the harmonic mean, and screening out an effective compilation option set; constructing a two-dimensional option matrix, comparing the acceleration effects of binary option sequences and establishing a directed graph of compilation option relationships; using depth-first search to obtain a set of candidate compilation option sequences; and using a genetic algorithm to iteratively optimize on a target program to generate an optimal compilation option sequence with the shortest running time. The purpose of the present invention is to address the problem of low optimization efficiency caused by numerous and complexly related compilation options of a compiler. By establishing a compilation option relationship model and generating a set of candidate compilation option sequences, the search space is reduced, the number of iterations of the genetic algorithm is reduced, and while ensuring the optimization of program performance, the compilation optimization overhead is significantly reduced.

Embodiments of the present invention disclose a music score sequence extraction method, a music search method, an apparatus, and a device, relating to the field of artificial intelligence technology. These methods are capable of improving the accuracy of music score sequence extraction under varying image quality conditions, thereby enhancing the precision and efficiency of subsequent searches based on the music score sequence. The music score sequence extraction method comprises acquiring a music score image to be identified, detecting all notes in the image to be identified, extracting the note heads of all notes, inputting the note heads into a classification model to obtain their positions within the staff, and generating a music score sequence based on the notes and the positions of their corresponding note heads within the staff. The present invention is applicable to electronic devices for music score sequence extraction and / or electronic devices for music search.

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 discloses an application method of a sequence search tool CircBLAST considering gene sequence evolution rearrangement, and belongs to the technical field of bioinformatics. The method flow comprises the following steps: firstly, all protein sequences are cut according to the length of a required word_size, a data set is constructed in combination with sequence annotation data, and is written into a database; then, a request sequence is prepared, and is cut into small fragments of word_size; further, a search matching, construction of a circular sequence and sequence alignment are carried out to complete a retrieval process; finally, an alignment result containing matching fragments, a similarity score and the like information is generated, is used for presenting to a user for viewing and judging the reliability of matching. The application considers the evolution rearrangement of gene sequences, significantly improves the accuracy of sequence alignment, and can find more reordered sequences.

Provided in the embodiments of the present application are compression methods for a sequencing data file, a device and a storage medium. Provided is a compression solution for a sequencing data file, comprising: for each sequencing sequence contained in a sequencing data file, proposing to use at least two matching components to cooperatively determine a reference fragment for the same sequencing sequence on a reference sequence; and, on the basis of the reference fragment determined accordingly, constructing comparison information between the sequencing sequence and the reference fragment, and compressing each piece of comparison information constructed under a file to be compressed. Thus, by means of cooperative operation of at least two matching components, the efficiency of searching reference fragments for sequencing sequences can be improved, and matching results can be mutually verified among matching components, thus effectively improving the matching accuracy of reference fragments.

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 invention relates to the technical field of aerospace assembly, in particular to an interactive aircraft strength test assembly body assembly sequence rapid planning method which comprises assembly body assembly state extraction, an ant-grey wolf heuristic disassembly sequence searching method and a single-step optimal principle disassembly sequence calculation method. Wherein the assembly state extraction is used for extracting required data from an assembly model and storing the data according to a disassembly sequence evaluation requirement; an ant-grey wolf heuristic method is used for generating a feasible disassembly sequence according with an evaluation criterion according to the sequence evaluation criterion and by utilizing the extracted model assembly information; according to the single-step optimal principle method, a new assembly sequence is quickly generated according to a given evaluation criterion, model assembly information and additional sequence constraint conditions. According to the method, the advantages of the two sequence generation methods are comprehensively utilized, the intention of a designer is fused into an algorithm result in an interactive mode, and the high-quality assembly sequence of the assembly is rapidly and flexibly generated through iteration.

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.

Methods and systems for encoding digital information in nucleic acid (e.g., deoxyribonucleic acid) molecules without base-by-base synthesis, by encoding bit-value information in the presence or absence of unique nucleic acid sequences within a pool. Described in this specification are methods for enumerating all elements of a combinatorial search space and searching for a solution, where a solution is described by constraints over categorical variables. A set of variables are mapped to an identifier nucleic acid sequence, the search space to a set of identifiers, and a constraint to a chemical method that selects a subset of identifiers satisfying the constraint.