64 results about "Gene pool" patented technology

The invention discloses a unified management method and device for multi-protocol Internet of Things equipment, and relates to the technical field of Internet of Things communication and protocol management, and the method comprises the steps: constructing a cross-protocol semantic knowledge graph through a graph neural network based on a structured gene-semantic mapping table, and generating a dynamic semantic relation matrix through a node embedding method; according to the dynamic semantic relationship matrix, deploying a genetic algorithm engine at an edge node to dynamically recombine and optimize protocol genes, screening protocol variants adapted to a network environment through an evolution sandbox pressure test, and generating an optimized protocol gene pool; and based on the optimized protocol gene pool, performing real-time conversion on the heterogeneous protocol message in a protocol conversion gateway in combination with a multi-thread parallel analysis architecture to generate a standardized semantic data stream. Unified expression and management of complex heterogeneous protocols are achieved, the protocol conversion process is simplified, cross-protocol semantic understanding and compatibility are improved, and device flexibility and analysis efficiency are improved.

The invention discloses an intelligent monitoring management system and method for a wire harness production line, and relates to the technical field of wire harness manufacturing, and the method comprises the steps: extracting data of crimping force and mold temperature from historical wire harness production data, coding the data into a real number coding gene chain, generating an initial gene pool in combination with material attributes, and constructing a digital twin model; the method comprises the steps of simulating stress field distribution and a heat conduction effect in a wire harness crimping process through finite element simulation, obtaining a twinning predicted value, pre-verifying process parameters in an initial gene bank based on a digital twinning model, screening process parameter combinations with deformation errors smaller than an error threshold value, and issuing the process parameter combinations to a crimping machine through a production line control center. According to the method, data of real-time wire harness deformation quantity is obtained, the data of the real-time wire harness deformation quantity is compared with a twinborn predicted value frame by frame, a deformation error rate is generated, and an abnormal traceability report is generated based on the deformation error rate, pre-verification is performed by constructing an initial gene pool and combining a digital twinborn model, so that optimization of process parameters is more accurate and effective.

The invention discloses a network attack perception induction method, and relates to the technical field of network security attacks, and the method comprises the steps: obtaining an APT malicious software gene model, obtaining behaviors generated during the operation of malicious software, carrying out the analysis, and constructing an APT family gene pool; obtaining an APT family gene bank, and performing classification extraction on the APT family gene bank to obtain an APT malicious behavior gene bank; acquiring an APT malicious behavior gene bank, identifying APT attack behaviors, establishing an attack path prediction model, determining an APT attack path and predicting a next APT activity; identifying the predicted bait most similar to the next attack target through a target similarity detection method, guiding the attack to migrate to the bait, and attracting an attacker to attack the bait; according to the method, the attack behavior can be induced, the attack can be actively carried out, the attack information can be more comprehensively captured, the defense capability of the network attack is greatly improved, and the network security is maintained.

The invention provides an AI-based urban governance application system intelligent generation method and system, and belongs to the technical field of application system generation. The method comprises the following steps: acquiring urban governance multi-source data, and extracting spatio-temporal characteristics to construct a digital twinborn model; converting front and rear end components into gene sequences through gene coding, and constructing a component gene pool; inputting urban governance scene generation component requirements, and constructing a multi-target fitness function and a genetic operator by using a multi-target genetic algorithm; establishing a reinforcement learning agent in combination with an optimization target of the function, and performing collaborative search and local optimization through a genetic operator and the agent to obtain an optimal component combination; optimal component combinations are distributed through a federated learning framework, evaluation model parameters are aggregated, and a component quality evaluation standard is constructed; operating data are collected on line, the using effect is evaluated, and the component gene pool and the digital twinborn model are updated. According to the invention, the assembly selection intelligence of the urban governance application system is realized, and the assembly selection search efficiency is improved.

The invention relates to the technical field of artificial intelligence-driven digital marketing, in particular to an AI-based new media intelligent marketing method, which comprises the following steps of: 1, carrying out cross-platform user behavior fusion modeling; 2, constructing a multi-modal content gene pool: analyzing a visual focus area and a text emotional tendency of historical content, and generating a content gene vector; 3, dynamic content generation and real-time optimization, wherein initial marketing content is generated according to the space-time behavior matrix retrieval gene bank; user interaction behaviors are monitored in real time, elements in a visual focus area are dynamically replaced, and the emotion intensity of the copywriting is adjusted; and step 4, closed-loop strategy optimization: a dynamic effect index is calculated by fusing multi-platform indexes, a gene variation mechanism is triggered when the index continuously decreases, and cross-platform compensation content is generated based on failed user behaviors. By analyzing the cross-platform behavior and the content preference of the user, the user demand can be accurately predicted, and the content more conforming to the personalized preference of the user is provided.

This invention discloses an adaptive information distribution resource catalog generation method, apparatus, and product, relating to the field of text generation, to improve catalog generation accuracy and reduce manual intervention workload. The invention includes: information resource feature acquisition; segmenting and encoding the features of each information resource to obtain a resource gene sequence for each information resource; obtaining user behavioral fingerprints; matching each resource gene sequence with a catalog gene pool based on the behavioral fingerprints; if a match is successful, outputting the catalog information of the matched catalog gene sequence; if a match fails, generating a new catalog gene sequence based on the resource gene sequence and updating the catalog gene pool with the new catalog gene sequence. This invention reduces classification error rate through multi-dimensional feature extraction and encoding mechanisms, performs feature matching based on user behavioral fingerprints, adapts to the personalized needs of different users, reduces manual intervention workload, and improves environmental compatibility.

The invention provides a radar digital control method and system, and relates to the technical field of radars, and the method comprises the steps: obtaining a radar working environment parameter, carrying out the similarity matching of the radar working environment parameter and a historical environment characteristic mode in an environment gene pool, and rapidly recognizing the characteristics of a current working environment. And then the optimal parameter combination corresponding to the target historical environment characteristic mode with the highest reliability weight in the plurality of historical environment characteristic modes with the similarity greater than or equal to the preset threshold is deployed to the radar, so that rapid, automatic and accurate adjustment of radar deployment parameters is realized. According to the method, the optimal deployment parameters can be quickly adapted according to the actual working environment of the radar, the anti-interference capability and the detection performance of the radar are effectively improved, and the working efficiency and the reliability of the radar are remarkably improved.

The invention relates to a software homology analysis method and device, computer equipment and a readable storage medium. The method comprises the following steps: acquiring a target family classification result of to-be-analyzed software by a pre-trained target classification model, and interpreting and analyzing the target classification model based on the target family classification result, so as to acquire the influence degree of each binary code snippet in the to-be-analyzed software on an output result of the target classification model; then, according to a target family classification result, a family gene pool of a target family and a software sample in the target family are obtained from a pre-established family gene resource center, and according to the family gene of the to-be-analyzed software, the family gene pool of the target family and the software sample in the target family, the software sample in the to-be-analyzed software can be analyzed according to the family gene of the to-be-analyzed software, the family gene pool of the target family and the software sample in the target family. According to the method, the homology analysis result of the to-be-analyzed software and the target family is determined, the to-be-analyzed software is traced, the time for tracing the to-be-analyzed software is shortened, and the homology analysis efficiency is improved.

The invention discloses a transcription factor AcWRKY84 gene for regulating and controlling gray mold resistance of kiwi fruits. After the expression of the gene is silenced, the gray mold resistance of kiwi fruits can be remarkably reduced. The AcWRKY84 gene is cloned, and the anti-gray mold effect of the AcWRKY84 gene in kiwi fruits is proved, specifically, after an experimental group is inoculated with viruses, compared with a control group, the disease symptoms of the fruits of the experimental group are aggravated, the infected area is obviously enlarged, and the enzyme activities of SOD, POD and CAT in the fruits are obviously reduced compared with the control group; sufficient gene resources can be provided for a kiwi fruit gray mold resistance gene pool, so that the possibility of successfully breeding high-gray mold-resistance varieties subsequently is greatly increased.

The invention discloses a molecular marker closely linked with a thin-skinned muskmelon bacterial fruit blotch resistance gene and application thereof, and belongs to the field of muskmelon disease resistance identification. According to the method, a disease-resistant muskmelon strain and a susceptible muskmelon strain are subjected to interspecific hybridization, genetic analysis is carried out on BFB-resistant characters of muskmelons by utilizing an F2 group, a high-resistance gene pool and a high-susceptibility gene pool are constructed on the basis, and resistance candidate genes of the muskmelons are mined by utilizing a BSA-seq technology and a molecular marker technology. Research results can provide a research basis for disease resistance character gene mining and mechanism research, and the method has important scientific significance for screening and application of muskmelon disease-resistant germplasm resources. The molecular marker KASP988272 is developed according to the genotype difference between candidate gene parents, and the genotype identification accuracy of the molecular marker in an F2 group is as high as 80%. The developed molecular marker closely linked with the bacterial fruit blotch resistant gene is used for rapidly and efficiently identifying the bacterial fruit blotch resistant thin-skinned muskmelon variety, and a technical support is provided for selection of the bacterial fruit blotch resistant thin-skinned muskmelon variety.

The invention provides a feature gene selection method and system based on deep learning attribution analysis and beam combination optimization, and relates to the technical field of signal analysis, and the method comprises the following steps: obtaining single cell RNA sequencing data and batch RNA sequencing data; the method comprises the following steps: based on single-cell RNA sequencing data, obtaining an initial gene pool aiming at a plurality of disease subtypes through a consensus screening strategy fusing XGBoost multi-dimensional importance measurement and deep learning SHAP attribution analysis; performing first-stage optimization on the gene list of each subtype by taking the initial gene pool as a starting point and adopting beam combination search and based on a global discrimination objective function to obtain a first-stage optimized gene set; integrating the first-stage optimized gene set with the differential expression gene set of the batch RNA sequencing data, and carrying out second-stage optimization by adopting bundle combination search again to obtain a second-stage optimized gene set; and performing cross validation integration on the second-stage optimized gene set, and outputting a final feature gene set.

The present application relates to the field of molecular genetic technology, in particular to a KASP molecular marker TMSK23 related to eggplant reverse temperature-sensitive male sterility and application thereof. The molecular marker site is obtained by crossing 05ms as female parent and S132 as male parent, and obtaining F2 separation population. According to the published high-quality eggplant genome information, the whole genome resequencing technology is used to pool and sequence the homozygous dominant fertile plants and homozygous recessive sterile plants in the F2 generation of eggplant, and the SNP difference sites of the fertile gene and sterile gene pool are screened out, and the difference sites are verified by KASP gene typing method and protein three-dimensional structure prediction. The present application solves the problems of large workload in hybrid seed production in the prior art, avoids the problem of a large number of measurement and matching in the transgenic process, improves the breeding efficiency and has other advantages.

A transcription factor for regulating resistance of kiwifruit to botrytis blight AcWRKY84 The application relates to a gene, and after the expression of the gene is silenced, the resistance of kiwifruit to botrytis blight is significantly reduced. AcWRKY84 The application clones the gene and proves the role of the gene in resisting botrytis blight in kiwifruit, and specifically, after the experimental group is inoculated with the virus, the disease symptoms of the experimental group are more serious, the infected area is obviously increased, and the SOD, POD and CAT enzyme activities in the fruit are significantly reduced compared with those of the control group, so that sufficient gene resources can be provided for a botrytis blight resistance gene library, and the possibility of realizing successful breeding of a high botrytis blight resistance variety is greatly increased.

The present invention relates to a malicious code detection method based on software genes and an improved Siamese network, comprising: data preprocessing, static analysis and dynamic analysis of the code file to be detected, and extraction of basic features; converting the basic features into gene fragments, mapping them to gene expressions, and constructing the gene sequence of the code; using the improved Siamese network, performing a similarity comparison between the extracted gene sequence and a known malicious code gene library to obtain a similarity calculation result; judging whether the code file contains malicious gene features based on the similarity calculation result, and further determining the malicious code family to which the malicious code belongs if malicious code is detected; and updating and optimizing the malicious code gene library based on the detection results so that the malicious code gene library covers the latest malicious code samples and variant features. The present invention significantly improves the effectiveness of malicious code detection tasks by combining malicious code gene features with AI models.

The present invention provides a radar digital control method and system, which relates to the field of radar technology. This method obtains radar operating environment parameters and performs similarity matching with historical environmental characteristic patterns in an environmental gene library. This method can quickly identify the characteristics of the current operating environment. It then deploys the optimal parameter combination corresponding to the target historical environmental characteristic pattern with the highest reliability weight among multiple historical environmental characteristic patterns with a similarity greater than or equal to a preset threshold to the radar, achieving rapid, automatic, and precise adjustment of radar deployment parameters. This method can quickly adapt the optimal deployment parameters based on the actual operating environment of the radar, effectively improving the radar's anti-interference capability and detection performance, and significantly enhancing the radar's operating efficiency and reliability.

The invention discloses a power distribution network three-phase imbalance dynamic regulation and control method based on a hybrid intelligent optimization algorithm, and belongs to the field of power system automation. Establishing a dynamic regulation and control model taking minimization of three-phase current unbalance degree and minimization of switch action times as double targets; solving the model based on an improved genetic algorithm fusing an experience knowledge guidance mechanism, a Pareto optimal selection mechanism and a global and local collaborative search mechanism; and generating a commutation control instruction according to the obtained optimal commutation scheme, and issuing the commutation control instruction to a load commutation switch for execution. By introducing a gene pool to guide a breeding process, a multi-target selection mechanism based on non-dominated sorting and a local optimization strategy combined with tabu search, comprehensive improvement of the algorithm in the aspects of convergence speed, solution diversity and global optimality is realized.

The invention provides a feature selection method based on evolutionary hypergraph learning, electronic equipment and a storage medium, and belongs to the field of artificial intelligence and machine learning. The method comprises the following steps: firstly, introducing a hypergraph structure to model a high-order feature interaction relationship, and comprehensively evaluating feature importance in combination with a genetic algorithm; a feature importance oriented gene pool is constructed based on an evaluation result, effective knowledge migration is realized among different populations through a specially designed cross strategy, and the search efficiency and the feature subset quality are improved. According to the method, experimental verification is carried out on a plurality of data sets with different dimensions, and a result shows that the method can stably select a higher-quality feature subset, and the balance accuracy of the model in a classification task is remarkably improved.

The embodiment of the invention provides a method for annotating a RefGene gene pool based on a distributed SQL (Structured Query Language) query engine. The method comprises the following steps: generating an interval forest differentiated from a positive strand and a negative strand of a chromosome; broadcasting the generated interval forest by using a broadcast mechanism of a distributed SQL query engine; querying the interval forest by using the specified field to be annotated and varied; performing an internal connection operation on the returned query result and the table to be annotated; and outputting the table containing the annotation result. And after the process is executed once, if the returned annotation result is not null, executing the process for the second time for annotating whether the variation belongs to the exon or not. In addition, the embodiment of the invention provides a device for annotating the RefGene gene pool based on the distributed SQL query engine.

The application discloses a method for constructing a digital rock gene library based on massive experimental data, and comprises the following steps: collecting different typical rock samples, carrying out relevant experimental research, obtaining relevant experimental data of the typical rock samples, and processing the relevant experimental data to form rock standardized data; collecting typical geological disaster data occurring in history and processing the geological disaster data to form historical disaster standardized data; collecting real-time dynamic monitoring data of the current geological disaster; and fusing and analyzing the three kinds of heterogeneous data sources and uniformly processing the three kinds of heterogeneous data sources to form the digital rock gene library. The application adopts the three kinds of heterogeneous data sources to construct the digital rock gene library, makes up for defects that data is incomplete and methods are single in the existing rock mechanics field, and leads to different analysis results, has strong broad-spectrum and high accuracy.

The invention belongs to the technical field of data processing, and discloses a sentinel point gene pool data processing method based on clustering analysis, which comprises the following steps: extracting gene expression data of samples in a sentinel point gene pool, and constructing a static feature space and a dynamic time sequence space; performing preliminary clustering on the static feature space to obtain an initial static group; switching to a dynamic time sequence space in each static group, performing secondary clustering on samples in the group based on time sequence similarity, and refining the samples into dynamic evolution subgroups; fitting a dynamic trajectory model of which the gene expression changes along with time for each dynamic evolution subgroup, calculating a deviation degree between a sample and a predicted value of the corresponding dynamic trajectory model in a static feature space, and marking the sample of which the deviation degree exceeds a preset confidence interval as an abnormal sample; and the application scene and value of the sentinel point gene pool in biomedical research are further expanded.

The invention relates to a turbulence model optimization method based on gene expression programming, which comprises the following steps: selecting a numerical simulation method in a CFD solver, and calculating vortex viscosity coefficient distribution; obtaining flow field characteristic variables through an RANS turbulence model; inputting a GEP algorithm by taking a vortex viscosity coefficient as a training truth value and a flow field characteristic variable as an input characteristic, carrying out GEP algorithm training work, and generating an initial population by combining three means of chaotic sequence generation, a gene pool predefined structure and random generation; changing individual crossover and mutation probability in real time to obtain a correction formula of the vortex viscosity coefficient; all coefficients in the vortex viscosity coefficient correction formula are optimized to obtain a vortex viscosity coefficient final expression, and the vortex viscosity coefficient final expression is loaded into a CFD solver; in the loaded CFD solver, calculation is carried out through an RANS turbulence model, and needed flow field information is obtained. The method has the capability of giving an explicit model equation, and the calculation precision of the RANS turbulence model is improved.

The invention discloses an lncRNA m5C methylation site prediction method based on deep learning, and relates to the technical field of m5C site prediction. The invention aims to solve the problem of low prediction accuracy of the existing lncRNA m5C methylation site method. The method comprises the following steps: acquiring an lncRNA sequence fragment corresponding to a methylated data file in a human gene pool, and constructing a training set by using the lncRNA sequence fragment; performing sequence coding on data in the training set to obtain an original feature vector of the lncRNA, and obtaining a coded training set; and training an lncRNA m5C methylation site prediction model by using the encoded training set to obtain a trained lncRNA m5C methylation site prediction model. Obtaining the original characteristics of the lncRNA sequence to be detected; and inputting the original characteristics of the lncRNA sequence to be detected into the trained lncRNA m5C methylation site prediction model to obtain an m5C site prediction result. The method disclosed by the invention is used for predicting the m5C methylation site of the lncRNA.

The invention relates to the technical field of data analysis, in particular to an integrated analysis method and system for multi-source single cell transcriptome data. The method comprises the following steps: converting all gene names of single cell transcriptome data from different sources into a unified version, and filtering source specific genes; a specific background gene pool is constructed, pollution genes are identified, and background RNA pollution is eliminated; calculating the average sequencing depth of each sample cell, and performing sequencing depth correction on each sample cell; based on transcriptome data of single cells from different sources, cell types are identified through cell grouping and characteristic gene expression quantity analysis, and each cell type is obtained; and constructing anchor point cells for each cell type, and correcting the deep equilibrium cell expression profile of the same cell type to obtain an integrated cell expression profile. The accuracy of data integration analysis of the single cell transcriptome is improved, and the influence of batch effect caused by multiple sources on other subsequent analysis is reduced.

The invention discloses a malicious software detection method and device, computer equipment and a readable storage medium, relates to the technical field of computer security and malicious code detection, combines a gene coding technology and a frequency domain data analysis method, and improves the detection efficiency and accuracy. The method comprises the following steps: running to-be-detected software, and continuously simulating user behaviors; collecting an interface calling sequence, and coding the interface calling sequence based on a time sequence gene coding technology to obtain a software gene sequence; matching the software gene sequence with a sample gene sequence included in a malicious software gene pool, and acquiring software frequency domain data under the condition that the matching determines that the sample gene sequence similar to the software gene sequence does not exist; matching the software frequency domain data with sample frequency domain data included in the malicious sample frequency domain database, and determining the to-be-detected software as malicious software under the condition of determining that the sample frequency domain data similar to the software frequency domain data exists through matching.

The application discloses a kind of control parameter adjustment method and system of magnetic levitation air supply machine, it is related to high-precision control technical field, including, construct information fusion model, the electromechanical thermal coupling characteristic input information fusion model of acquisition, generate electromechanical thermal characteristic vector;With vector decoupling operator, electromechanical thermal characteristic vector is separated into electromechanical thermal characteristic component, and energy stable scalar value is generated in combination with real-time magnetic levitation air supply machine operation data;Distributed digital gene library is constructed, energy stable scalar value is mapped into discrete working condition label, discrete working condition label and gene fragment in distributed digital gene library are matched, and optimal gene fragment is output;Analysis optimal gene fragment generates control parameter set, and generates multiple parameter change trajectory by smoothing operation function group.The application is by constructing distributed digital gene library, so that control parameter self-adapting adaptation continuous change operating condition and equipment aging Slow time-varying factor, significantly improve system robustness.

This invention discloses a prognostic model and construction method for cervical squamous cell carcinoma, belonging to the fields of bioinformatics and oncology. The construction method is based on a set of genes related to programmed cell death, integrating multi-omics data of cervical squamous cell carcinoma patients from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and the Cancer Genome Characterization Project (CGCI). After standardized preprocessing, differential expression analysis, bootstrap resampling combined with univariate Cox regression for initial screening, consensus screening using multiple machine learning algorithms, and finally, multivariate Cox proportional hazards regression analysis to identify three core independent prognostic genes and construct a risk scoring model. This model has undergone multi-dimensional validation and optimization, demonstrating robust predictive performance. The method of this invention is standardized and highly reproducible, and the constructed model has high accuracy and strong generalization ability, providing a reliable tool for individualized prognostic assessment and clinical decision-making for cervical squamous cell carcinoma patients.

A method and an apparatus for updating a cloud platform are provided. The method may include: in response to receiving a cloud platform update request, acquiring to-be-used updating cluster gene information corresponding to the cloud platform update request, wherein the to-be-used updating cluster gene information is structured information that completely represents information of components in a cloud platform container cluster; updating a standard cloud platform gene library according to a comparison result between the to-be-used updating cluster gene information and cluster gene information of a current standard cloud platform, wherein the standard cloud platform is a unified cloud platform on which a customer-specific cloud platform is deployed; and determining, according to an updated standard cloud platform gene library, a hardware resource of a final standard cloud platform and a software resource of the final standard cloud platform.

The invention discloses an intelligent manufacturing system and method for a text travel digital cultural product based on a large model, and relates to the technical field of text travel digitization, and the system comprises a data graph module which receives and processes multi-source data, and constructs a text travel knowledge graph; the semantic extraction module is used for finely tuning the model to extract semantic tags, and calculating and verifying the tag reliability; the gene pool matching module is used for retrieving a gene pool and matching visual features with cultural relic parameters; the double-drive dynamic generation module is used for generating a static model and simulating dynamic evolution in combination with semantic vision; the achievement verification output module is used for converting the data into multimedia, verifying the similarity and judging the achievement; according to the invention, through semantic-vision dual-drive dynamic generation and multi-dimensional verification of a closed loop, it is ensured that digital products fit historical logic of cultural relics; meanwhile, through multi-source data integration, semantic optimization and gene pool accurate matching, full-process data and semantic optimization is achieved, and the problems of semantic vision disjunction, data fragmentation and the like in traditional text travel digitization are solved.

This invention provides a species gene classification system, method, apparatus, electronic device, and storage medium, belonging to the field of integrated circuit technology. It includes: a preprocessing module for converting a first serial current signal corresponding to a gene of a species to be tested into a hash vector representing that gene; a content-addressable memory (MAP) for performing vector-matrix multiplication on the hash vectors to obtain multiple first cumulative currents; the MAP is an RRAM array structure, and its conductance is positively correlated with a reference hash vector, where each reference hash vector represents a gene from a species gene pool; and a first comparison module for comparing the various first cumulative currents to determine the species to which the gene belongs. This invention achieves species gene classification through in-memory computation, reducing data movement and eliminating the need for complex algorithms to correct noise, thereby accelerating system operation, reducing sequencing time, and lowering system energy consumption.

The invention provides a Qiang product generation method and system, computer equipment and a storage medium, and belongs to the field of digital protection and innovative design of intangible cultural heritage, and the method comprises the steps: collecting sheep totem literature records and artificial Qiang handicraft real objects, and extracting a vectorization feature curve and process visual features by using an improved Mask R-CNN model; performing three-level coding on the basis of a rooting theory, and constructing a Qiang culture gene bank containing visual features, semantic features and translation rules; converting the gene bank into a cue word matrix in combination with a shape grammar rule, designing an intention graph and a creative sketch, and inputting the intention graph and the creative sketch into an AIGC model to generate a candidate scheme set; and dynamically adjusting AIGC model parameters through a multi-strategy enhanced escape algorithm, and finally outputting an optimal design element and generating a Qiang product. Accurate extraction and intelligent translation of Qiang culture genes are achieved, culture inheritance accuracy and design innovation efficiency are both considered, and intelligent transformation from protection to innovation of the Qiang culture genes is promoted.