46 results about "Sequence search" patented technology

The invention discloses an automatic wiring and optimizing method for a superconducting quantum chip, and belongs to the field of automatic design of superconducting quantum chips. According to the method, in a modeling stage, a'combined wiring template 'model under a fine-grained grid is adopted, a problem is discretized through a combined wiring template, complex geometric operation of the arc wiring problem in the solving process is avoided, and the search space of an algorithm is greatly reduced; in the legal solution search stage, a single-side wiring algorithm is adopted, a line sequence search problem is extended according to wiring result characteristics of the algorithm, a line sequence tree search framework is designed, and on the basis, the blocking relation between lines is explored, and a series of search optimization strategies are designed; an exchange winding action is adopted to meet the special wire sequence requirement of a read wire; in the wiring optimization stage, an iterative optimization wiring scheme based on space limitation is adopted, and multi-stage target optimization is performed on the overall wiring result on the basis of a legal solution, so that the wiring result meets design requirements.

The invention provides a process identification method based on model features, which comprises the following steps that: a process knowledge graph is constructed by extracting a relation node triple in a standard process description text, and the node types of the graph comprise feature nodes, process nodes, equipment nodes, cutter nodes and clamp nodes; the relation between every two adjacent nodes comprises an available process, a preorder process, available equipment, initial machining, tool assembling and clamp assembling. Obtaining a geometric model of a to-be-machined mechanical part, extracting geometric feature attributes of the to-be-machined mechanical part, and determining a feature topological relation to obtain machining features; and starting from the feature nodes corresponding to the machining features by adopting an inverted sequence search method, screening out nodes meeting the machining requirements of the to-be-machined mechanical part from the process knowledge graph, and obtaining a complete process scheme. The method can deeply excavate the correlation between the geometric features of the part model and the machining process, improves the process identification accuracy, and is wide in applicability.

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 disease control big data analysis method and system, and the method comprises the following steps: obtaining a data set X comprising a plurality of class attributes, and carrying out the preprocessing; performing independent optimal sequence search on each category attribute in the data set to obtain an optimal sequence, determining a distance structure suitable for disease control big data analysis, calculating distance measurement between a sample and a cluster according to the obtained optimal sequence, and constructing a clustering model; and by minimizing a target function, updating a sample attribution matrix and sequence, and dynamically adjusting a clustering result. Compared with the prior art, the method has the advantages that the system can adaptively adjust the clustering result by dynamically learning the optimal value sequence of the data and the corresponding distance structure, so that the clustering accuracy is remarkably improved, and visual interpretation is provided for understanding of the data.

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 discloses a method, a system and a medium for reducing a search space of a compilation option sequence, and the method comprises the following steps: starting programs in a single compilation option sampling template program set item by item, and obtaining speed-up ratio data relative to a preset compilation option sequence under each compilation option; calculating a harmonic average value, and screening out an effective compiling option set; constructing a two-dimensional option matrix, comparing acceleration effects of the binary option sequence, and establishing a compilation option relation directed graph; applying depth-first search to obtain a to-be-selected compilation option sequence set; and carrying out iterative optimization on the target program by adopting a genetic algorithm to generate an optimal compilation option sequence with the shortest running time. The method aims at solving the problem of low optimization efficiency caused by numerous compiling options and complex association of a compiler, the search space is reduced by establishing the compiling option relation model and generating the sequence set of the to-be-selected compiling options, the number of iterations of a genetic algorithm is reduced, and the compiling optimization overhead is remarkably reduced while it is guaranteed that program performance is optimized.

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 invention provides a same-frequency mixed signal demodulation method based on optimal sampling and related equipment, and relates to the technical field of wireless communication. The method comprises the following steps: down-converting a received mixed signal into a baseband signal so as to estimate a channel parameter of each path of signal; according to the estimated channel parameters of each path of signals, constructing sufficient statistics about the received mixed signals; and constructing a transfer metric according to the sufficient statistics, thereby performing sequence search according to a Viterbi recursion relationship, finding a path with a maximum accumulated metric value, and backtracking a decision symbol according to the path to obtain a decision symbol sequence. A PCMA signal test result shows that compared with an existing method, the performance of the method is greatly improved and approximates to theoretical performance.

The invention discloses a character sequence searching method and related equipment, and the method comprises the steps: obtaining a to-be-searched first character sequence, and carrying out the compression processing of the first character sequence through employing a target compression mode, and obtaining a first compressed character sequence corresponding to the first character sequence; a query index is obtained, the query index is constructed based on second compressed character sequences corresponding to second character sequences included in the character sequence set, and each second character sequence is compressed in a target compression mode to obtain the corresponding second compressed character sequence, the query index defines an index structure used during character sequence search, and the query index is used for indicating a character sequence search rule; and searching a second character sequence matched with the first character sequence in the character sequence set based on the first compressed character sequence and the at least one second compressed character sequence according to the indication of the query index. The search efficiency can be improved based on the compressed character sequence and the query index.

The invention relates to a gene family screening method based on sequence composition, and belongs to the field of bioinformatics and genome research. The sequences of the same gene family are a group of highly similar sequences. Not only key regions of the sequences are required to be similar, but also the whole sequences are required to be similar, however, a method based on BLAST similar sequence search and a method based on structural domain search focuses on key region search of the sequences. According to the invention, the overall characteristics of protein are measured through sequence composition, and on the basis, verification is carried out through sequence similarity and a structural domain, so that the whole and key areas of screened gene family members are very similar, and screening deviation is reduced. The invention has a very important value for research related to gene families.

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.