28 results about "Genetic Evolution" patented technology

The invention discloses a chip for genome breeding and variety identification of tilapia mossambica. The invention provides a group of SNP (Single Nucleotide Polymorphism) marker combination for tilapia mossambica, which comprises 50000 SNP markers which are respectively SNP1-SNP50000 markers. According to the invention, the SNP marker combination related to economic characters of tilapia mossambica is integrated, representative sites with uniform coverage are selected, a biological probe for site typing is developed, and the site coverage, typing accuracy and GS accuracy of the SNP marker combination are basically consistent with those of re-sequencing; the method can be applied to the aspects of tilapia germplasm resource identification, genetic relationship identification, SNP typing, variety identification, molecular breeding, DNA fingerprint database construction, variety purity detection, germplasm resource genetic analysis, whole genome selective breeding, functional gene positioning, genetic map construction, genetic evolution analysis, whole genome association analysis and the like.

This invention provides a combination of SNP molecular marker primers for the molecular identification of soft-fiber areca nut germplasm resources and their applications, belonging to the field of SNP molecular marker technology. Based on the constructed core areca nut germplasm resources, this invention conducts genetic background association analysis on the phenotypic characteristics of fruit fibers and develops SNP molecular marker primers based on areca nut fiber-specific loci. The development of these SNP molecular marker primers includes four pairs of specific primers. This invention also provides a method for detecting soft-fiber areca nut germplasm resources using SNP molecular marker primers. This method can rapidly, accurately, cost-effectively, and with high throughput detect the genotype of soft-fiber areca nut germplasm resources. The four pairs of specific primers of this invention can be used to identify soft-fiber areca nut germplasm resources, which has important application significance for the scientific protection of areca nut germplasm resource diversity, research on the genetic conservation and evolution of areca nut resources, and areca nut genetic breeding.

The invention belongs to the technical field of breeding planning, and particularly relates to a large model construction method and system for multi-source data collaboration pear precision breeding planning, and the method comprises the steps: obtaining a multi-source collaboration data set, constructing a five-dimensional incidence matrix, and building a unified correlation basis of multi-dimensional data; constructing a constrained knowledge expression structure and training a constraint consistency reasoning model on the basis, analyzing a user breeding instruction in a constraint driving mode, and generating a combined constraint condition set containing a gene feasible region and a multi-phenotype collaborative target; calling germplasm resources under a cross-domain feature alignment and feature-level desensitization framework, executing phenotype-genotype collaborative screening, parent dynamic matching and multi-generation genetic evolution deduction, and generating breeding planning simulation data; and finally, outputting an optimal breeding scheme through a multi-dimensional evaluation system, and continuously updating the model by utilizing verification data. According to the invention, unification of multi-phenotype balanced synergistic improvement and stable gene transfer is realized, and the breeding efficiency and variety adaptability are remarkably improved.

The application discloses a kind of dynamic depth analysis engine construction methods based on genetic evolution algorithm, belong to software analysis technical field, main in solving the problem of low code coverage and malicious behavior trigger rate of existing dynamic analysis technology, main scheme includes step 1: the UI level capture of being tested Android application is carried out to obtain UI component information in the tested Android application, obtain UI level information.Step 2: specified UI event trigger is realized by injecting event function.Step 3: capture software dynamic behavior characteristic data and realize malicious behavior dynamic detection using neural network model.Step 4: event function sequence is generated and screened using genetic evolution algorithm, and the injected event function is changed by feedback regulation.The application finally realizes the dynamic optimization of UI event sequence by combining with feedback regulation while detecting malicious behavior, and realizes the identification of Android malicious software based on dynamic analysis with high trigger rate.

The invention discloses a heat dissipation control method and device based on flip-chip bonding. The method comprises the following steps that S1, temperature information in the flip-chip bonding process is collected in real time; s2, pumping a nanofluid coolant through the micro through hole to take away heat generated in the chip bonding process; s3, inputting the collected temperature information into a temperature control regulation module, and adaptively optimizing the flow velocity of the coolant through fuzzy reasoning and a genetic evolution mechanism; s4, continuously receiving temperature feedback of each monitoring point, comparing a preset safety threshold value with the change trend curve in real time, and performing dynamic adaptive adjustment on a temperature control strategy; and S5, after bonding is completed, bottom filling and curing are carried out, and the chip packaging process is completed. According to the method, a high-thermal-conductivity material structure, nanofluid cooling and an intelligent optimization algorithm are fused, efficient heat management and dynamic self-adaptive temperature control in the flip chip packaging process are achieved, and the packaging reliability and the system intelligence level are effectively improved.

The application discloses ginkgo polymorphic EST-SSR molecular marker primers and application thereof, and belongs to the technical field of molecular marker development and application thereof. EST-SSR sites are screened from ginkgo transcriptome data, and 100 pairs of primers are designed and synthesized. Through effectiveness verification and polymorphism screening with 141 ginkgo germplasm genomic DNAs as templates, finally, 20 pairs of specific EST-SSR molecular marker primers with good stability and high polymorphism are obtained. The application further discloses application of the self-developed molecular marker primers in ginkgo genetic diversity analysis and core germplasm construction and the like. The EST-SSR molecular marker primers provided by the application provide theoretical and technical support for ginkgo genetic evolution analysis, kinship identification and good seed selection and the like, and have important value for rational utilization, preservation and protection of ginkgo germplasm resources.

This application relates to a time-varying vehicle delivery route planning method and platform considering traffic flow. The method includes: using the NSGA-II algorithm to perform genetic evolution on multiple initial dual-encoders to generate multiple candidate dual-encoders; decoding and generating delivery planning information associated with each delivery object based on the node codes and delivery codes of all candidate dual-encoders; using the ant colony algorithm to perform time-varying vehicle delivery route planning based on the acquired time-varying travel time and delivery planning information to generate the intended delivery route corresponding to each delivery object; performing corresponding genetic evolution on all candidate dual-encoders based on the delivery fitness corresponding to the intended delivery route; and performing time-varying vehicle delivery route planning based on the delivery planning information and time-varying travel time of the dual-encoders that have completed the genetic evolution operation; and repeating the steps of performing the corresponding genetic evolution operation and performing time-varying vehicle delivery route planning until the target delivery route is generated.

The invention discloses a data cross-region migration method and device, electronic equipment and a storage medium. The technical problems that a current data cross-region migration strategy is single in consideration factor, low in migration efficiency and high in operation cost are solved. The method comprises the steps of obtaining to-be-migrated data and at least one target storage area of data cross-region migration; based on the to-be-migrated data, performing multi-factor analysis on each target storage area to obtain a multi-factor analysis result of each target storage area; on the basis of the multi-factor analysis result of each target storage area, optimal scheduling combining divide-and-conquer and parallel genetic evolution is carried out on the to-be-migrated data, and an optimal data migration scheme is obtained; and migrating the to-be-migrated data to at least one target storage area based on the optimal data migration scheme.

The application discloses a D / Yama2019 genetic evolution lineage influenza D virus reverse genetic manipulation system. Seven pairs of primers are designed to amplify DNA fragments corresponding to full-length genome PB2, PB1, P3, HEF, NP, M and NS segments of D / JY3002, and the DNA fragments are cloned into pHW2000 and pCC1-DualPro vectors to construct a plasmid, and the plasmid is co-transfected into a cell line to obtain artificially rescued D / Yama2019 genetic evolution lineage influenza D virus rD / JY3002. The genome sequence of rD / JY3002 is completely consistent with that of natural isolated strain D / JY3002, and the infection ability is equivalent, and the rD / JY3002 can be stably passaged for at least five generations. A unidirectional expression plasmid pPolI-D / JY3002-PB1-240-GFP-240 is constructed to obtain artificially rescued recombinant influenza D virus rD / JY3002-GFP carrying a green fluorescent reporter gene, and after the rD / JY3002-GFP infects host cells, the GFP expression amount is high and stable. The application establishes a high-efficiency and stable D / Yama2019 genetic evolution lineage influenza D virus reverse genetic manipulation system, and can be used for developing an influenza D virus vector to present an exogenous gene.

The invention discloses an SNP molecular marker combination for identifying taro germplasm resources and application, and belongs to the technical field of molecular biology. According to the invention, 252 SNP loci are screened out and used for developing the PARMS-SNP marker, and 27 original PARMS-SNP markers are successfully obtained. 27 SNP markers are utilized to carry out genetic typing on 72 taro resources, and population structure analysis, PCA principal component analysis and genetic evolution analysis are further carried out. The taro germplasm resources can be well distinguished, and reference is provided for evaluation and identification of the taro germplasm resources and breeding of new germplasm.

The invention discloses a flow type blood sample pretreatment method and system based on a mechanical arm, and relates to the technical field of flow cytometry, the method comprises the following steps: obtaining operation information and layout information of a to-be-treated sample, and coding based on the operation information and the layout information to obtain sample features; generating an initial chromosome population based on the sample features; performing genetic variation treatment on the initial chromosome population to obtain a target optimized population, and selecting a target chromosome meeting a preset fitness condition from the target optimized population; and determining the trajectory planning scheme corresponding to the target chromosome as a target trajectory scheme, and controlling the mechanical arm to execute sample pretreatment operation on the to-be-treated sample according to the target trajectory scheme. According to the method, the sample information is obtained and feature coding is performed, so that trajectory optimization is performed by adopting the genetic evolutionary algorithm based on the sample features, the moving trajectory scheme of the mechanical arm can fully consider the features and layout of the samples, and the synchronism and the overall efficiency of sample processing are improved.

The application relates to a process mapping optimization method and device based on a genetic algorithm and a storage medium. The method comprises the following steps: obtaining communication data corresponding to a plurality of sub-processes of a target computing program, wherein the communication data comprises process communication volume and process communication time delay; performing real number coding on the process communication volume and the process communication time delay to generate a first process mapping coding array, wherein the first process mapping coding array comprises a plurality of first codes, and the first codes are used for representing the corresponding relationship between a first process core for executing a sub-process and the sub-process; performing genetic evolution operation on the first codes based on the genetic algorithm, performing redundancy scheduling processing on the first codes after the genetic evolution operation, and generating a second process mapping coding array with a plurality of second codes; determining the fitness of the second codes, and performing genetic evolution operation updating on the second codes in the second process mapping coding array according to the fitness to generate a target process mapping coding array, so that a process mapping optimization result is obtained.

The application discloses a SNP molecular marker combination for identifying taro germplasm resources and application, and belongs to the technical field of molecular biology. 252 SNP sites are screened for the development of PARMS-SNP markers, and 27 original PARMS-SNP markers are successfully obtained. 72 taro resources are subjected to genetic typing by using the 27 SNP markers, and population structure analysis, PCA principal component analysis and genetic evolution analysis are further carried out. The taro germplasm resources can be better distinguished, and reference is provided for the evaluation and identification of taro germplasm resources and the breeding of new germplasm.

The application discloses a power system gene attack modeling method and system based on autonomous evolution game, relates to the technical field of power system attack and defense simulation, and comprises the following steps: performing evolution processing on a plurality of first power attack genes by using a power attack gene regulation coding model, obtaining second power attack genes corresponding to each first power attack gene and performing genetic evolution, simulating a dynamic confrontation process between an attack behavior and a defense mechanism based on an immune response model by using all third-generation power attack genes; constructing an attack and defense game optimization objective function, taking the attack and defense game optimization objective function as an optimization criterion, and making attack strategies and defense strategies interactively evolve through autonomous evolution game until the attack and defense game converges to Nash equilibrium. The first power attack genes are subjected to evolution processing by using the power attack gene regulation coding model, so that the attack logic can be self-organized and cooperatively evolved like biological genes.

The invention relates to a GA-ALNS-based goods purchasing and cyclic goods taking decision-making method and service platform, and the method comprises the steps: obtaining the demand information of a plurality of to-be-received target products of a central warehouse in a plurality of execution periods, and the demand information at least comprises the demand quantity of each to-be-received target product; generating an initial two-dimensional coding body comprising a goods taking decision coding sub-according to the execution cycle, the target product and the demand quantity code, planning a target transportation path of the initial two-dimensional coding body and determining the fitness corresponding to the initial two-dimensional coding body based on the goods taking decision coding sub-and an adaptive large neighborhood search algorithm, and determining the target transportation path of the target two-dimensional coding body based on the fitness and a genetic algorithm. Carrying out genetic evolution operation on the initial two-dimensional code body, and repeatedly executing the steps of planning and generating a target transportation path and carrying out genetic evolution operation by utilizing a self-adaptive large neighborhood search algorithm until a target two-dimensional code body of which the fitness is greater than a fitness threshold value is generated, the decision result comprises a goods taking decision corresponding to the target two-dimensional coding body and a target transportation path.

This application discloses a flow cytometry blood sample preprocessing method and system based on a robotic arm, relating to the field of flow cytometry technology. The method includes: acquiring operational and layout information of the sample to be processed, and encoding this information to obtain sample features; generating an initial chromosome population based on the sample features; performing genetic mutation processing on the initial chromosome population to obtain a target optimized population, and selecting target chromosomes that meet preset fitness conditions from the target optimized population; determining the trajectory planning scheme corresponding to the target chromosome as the target trajectory scheme, and controlling the robotic arm to perform sample preprocessing operations according to the target trajectory scheme. This application acquires sample information and performs feature encoding, thereby optimizing the trajectory using a genetic evolution algorithm based on the sample features. This allows the robotic arm's trajectory scheme to fully consider the characteristics and layout of the sample, improving the synchronization and overall efficiency of sample processing.

The invention relates to a parameter optimization method and device for a power transmission system, electronic equipment and a medium, and the method comprises the steps: constructing a torsional vibration dynamics model of a vehicle based on a multi-body dynamics theory; performing simulation analysis on the torsional vibration dynamic model to obtain simulation data, constructing a sample data set and a verification data set by using the simulation data, and training an agent model meeting a preset risk resonance condition by using the sample data set and the verification data set; and performing iterative calculation on the proxy model to obtain a calculation result, screening a solution set meeting a preset constraint condition from the calculation result through a genetic evolution mechanism, and optimizing parameters of the power transmission system of the vehicle by using the solution set. Therefore, the technical problems that a large amount of energy loss which cannot be effectively identified is caused by a split optimization normal form and the overall efficiency is difficult to break through a theoretical peak value in the related technology are solved.

The invention discloses an intrusion prediction and defense method based on genetic evolution and two-stage stochastic programming. The method comprises the following steps: constructing an attack path prediction model based on a genetic algorithm, and outputting an elite set of a high threat attack path; establishing a two-stage stochastic programming model based on the elite set, taking the total expected cost as a target function, introducing attack logic constraints and resource constraints, and outputting an optimal defense strategy and a resource allocation scheme; and deploying defense measures according to the optimal defense strategy and the resource allocation scheme, and implementing active defense. According to the method, the defect that a traditional network security defense technology lags behind is overcome, active prediction and accurate defense of attack behaviors are achieved, and by intelligently generating a security protection strategy, the utilization efficiency of security resources is improved, the operation and maintenance cost and false alarm interference are reduced, and therefore the initiative and effectiveness of security protection are improved.

The invention discloses a primer for detecting pigeon type I paramyxovirus and a kit thereof, the primer capable of amplifying the pigeon type I paramyxovirus is developed, and on the basis of the primer, the pigeon type I paramyxovirus can be quickly and efficiently diagnosed through an RT-PCR (Reverse Transcription-Polymerase Chain Reaction) method; moreover, the method is wide in application range, can be used for detecting not only serum, but also samples such as cloaca secretions or saliva or tissue fluid and the like, and has universality. Compared with other detection methods, the one-step RT-PCR method is low in cost and simple to operate, and a new direction can be provided for epidemic disease diagnosis and pathogen genetic evolution analysis.

The mycobacterium tuberculosis can be divided into pedigree 1 to pedigree 9 (line 1-9, L1-L9) with genetic evolution relationship, and the pedigree 3 (line 3, L3) can be further divided into L3.1. 1, L3.1. 2, L3.2. 1 and L3.2. 2. The mycobacterium tuberculosis can be used for preparing a mycobacterium tuberculosis pedigree, a mycobacterium tuberculosis pedigree, a mycobacterium tuberculosis pedigree and a mycobacterium tuberculosis pedigree. However, a large number of L3 strains still cannot be typed. The invention relates to an SNP (Single Nucleotide Polymorphism) site for identifying six new subbranch genotypes of mycobacterium tuberculosis L3.1. 1 except for two subbranches of L3.1. 1. I1 and L3.1. 1. I2. Specifically, the invention provides a method for deeply typing and identifying six new sub-branches of mycobacterium tuberculosis L3.1. 1 except for two existing sub-branches of L3.1. 1. I1 and L3.1. 1. I2, so as to provide theoretical support for pathogenicity fundamental research and accurate prevention and control of tuberculosis. The method relates to a set comprising 37 SNP sites, and identification and genetic evolution analysis of 6 new sub-branches of the mycobacterium tuberculosis L3.1. 1 can be realized through the SNP set, so that support is provided for identification and accurate prevention and control of sub-branches with stronger propagation of the mycobacterium tuberculosis pedigree 3.

The present application belongs to the technical field of breeding planning, and particularly relates to a method and system for constructing a large model for precise pear breeding planning based on multi-source data collaboration, which obtains a multi-source collaborative data set and constructs a five-dimensional correlation matrix to establish a unified correlation basis for multi-dimensional data; based on this, a constraint type knowledge expression structure is constructed and a constraint consistency reasoning model is trained to analyze user breeding instructions in a constraint driven manner, generating a joint constraint condition set containing a gene feasible region and a multi-phenotype collaborative target; under a cross-domain feature alignment and feature-level desensitization framework, germplasm resources are called to perform phenotype-genotype collaborative screening, parent dynamic matching and multi-generation genetic evolution deduction to generate breeding planning simulation data; finally, the optimal breeding scheme is output through a multi-dimensional evaluation system, and the model is continuously updated using verification data. The present application realizes the unity of multi-phenotype balanced collaborative improvement and gene stable transmission, significantly improving breeding efficiency and variety adaptability.

The present application belongs to the technical field of molecular biology, and particularly relates to a SNP molecular marker combination for identifying or distinguishing grouper germplasm resources and application thereof. Genomic DNA of golden money grouper, tiger grouper and golden tiger hybrid grouper is extracted, and 177 common SNP sites are obtained after detection, and specific position information is shown in Table 1 of the specification. The SNP molecular marker combination screened by the present application can be developed into primers, probes or gene chips, and through simple phylogenetic tree analysis, golden money grouper, tiger grouper and golden tiger hybrid grouper can be quickly and accurately distinguished, and unknown detection samples can also be subjected to genetic phylogenetic tree analysis with known golden money grouper, tiger grouper and golden tiger hybrid grouper, so that it can be quickly and accurately identified which kind of grouper the unknown detection sample belongs to, and the present application has the characteristics of simple operation, high efficiency, high accuracy and the like, and has important significance in grouper germplasm resource protection and utilization and grouper genetic breeding work.

The invention discloses an HPM source optimization method and system based on Bayesian optimization and multi-small population evolution, and the method comprises the steps: obtaining a data set describing the structure parameters and performance parameters of a to-be-optimized HPM source device, initializing a global population library, and carrying out the partitioning of the global population library; bayesian optimization model parameters are initialized, and a plurality of small populations are constructed based on the combination of Bayesian optimization model recommendation and random sampling; performing parallel genetic evolution on each small population, predicting device performance parameters by using a PIC numerical simulation method, and realizing individual fitness evaluation by using an FSAWS method until convergence and collection of niche elite individuals; updating a global Pareto solution set and a global population library by using niche elite individuals, and updating a Bayesian optimization model according to a preset strategy; elite individuals are found in an iteration mode, and structural optimization of the HPM source device is achieved.

The network defense method, device and equipment provided by the present disclosure relate to computer network security technology, and include: obtaining a configuration file in a switch of a business server monitored by a honeypot server according to obtained honeypot deployment instructions, the configuration file including a live Internet Protocol address; determining a non-live Internet Protocol address according to the live Internet Protocol address; determining a target service set according to a preset genetic evolution algorithm, a preset initial port set and a preset first port set; and deploying a honeypot service to achieve network defense according to the target service set and the non-live Internet Protocol address. According to the present scheme, the honeypot service to be deployed is determined through the non-live Internet Protocol address, the preset port set and the first port set with higher attacker benefits, the deployed honeypot service can improve the trapping capability to a certain extent, and the genetic evolution algorithm is used to accelerate the deployment efficiency.

The invention belongs to the technical field of molecular biology, and particularly relates to an SNP molecular marker combination for identifying or distinguishing grouper germplasm resources and application of the SNP molecular marker combination. Genomic DNA of hybrid spots of christina plaque, tiger plaque and golden tiger plaque is extracted, 177 common SNPs sites are obtained after detection, and specific position information is shown in a table 1 in the specification. The SNP molecular marker combination screened by the invention can be developed into a primer, a probe or a gene chip, and through simple phylogenetic tree analysis, the three types of groupers, i.e., christina plaque, tiger plaque and golden tiger hybrid plaque, can be quickly and accurately distinguished; genetic evolutionary tree analysis can be carried out on unknown detection samples and known christina plaque, tiger plaque and golden tiger hybrid plaque, the unknown detection samples can be quickly and accurately identified which of the three groupers belongs to, and the method has the characteristics of simplicity and convenience in operation, high efficiency, high accuracy and the like, and has a wide application prospect in grouper germplasm resource protection and utilization. The method has important significance in grouper genetic breeding work.

The invention relates to a time-varying vehicle distribution path planning method and planning platform considering traffic flow, and the method comprises the steps: carrying out the genetic evolution operation of a plurality of initial double-coding bodies through employing an NSGA-II algorithm, and generating a plurality of candidate double-coding bodies; according to the node codes and the distribution codes of all the candidate double-code bodies, performing decoding to generate distribution planning information associated with each distribution object, performing time-varying vehicle distribution path planning by using an ant colony algorithm based on the acquired time-varying travel time and the distribution planning information, and generating an intentional distribution path corresponding to each distribution object; according to the distribution fitness corresponding to the intentional distribution path, performing corresponding genetic evolution operation on all candidate double-coding bodies, and according to the distribution planning information and the time-varying travel time corresponding to the double-coding bodies completing the genetic evolution operation, performing time-varying vehicle distribution path planning; and repeatedly executing the steps of performing the corresponding genetic evolution operation and performing the time-varying vehicle distribution path planning until a target distribution path is generated.

The present application relates to the technical field of molecular biology and plant molecular breeding, and particularly relates to a chromosome inversion co-segregated with plum flower purple leaf character and application thereof. A chromosome inversion molecular marker co-segregated with the plum flower purple leaf character of 'Meiren' plum is developed by using nucleotide sequences on both sides of the chromosome inversion breakpoint to design primers, and the marker primer sequences are shown as SEQ ID NO. 5-10. The present application explains the evolutionary relationship and source of the chromosome inversion from the genomic level, and clearly defines the genetic evolutionary relationship of the purple leaf character of 'Meiren' plum. The molecular marker provided by the present application can efficiently and accurately predict the plum flower purple leaf character, has high accuracy and remarkable effect, has high application prospect in molecular assisted breeding, and can accurately identify the purple leaf character genotype of plum flower or Prunus germplasm resources due to distant hybridization.

The present invention discloses the use of donkey-derived biological components in analyzing human HBV or its satellite virus infection. Through genetic phylogenetic tree analysis, the present invention screened and identified donkey sodium ion / taurocholic acid co-transporting peptides that are similar to human ones. Furthermore, experimental confirmation confirmed that the donkey sodium ion / taurocholic acid co-transporting peptides can support human HBV and / or its satellite virus infection, and that primary donkey hepatocytes can support human HBV and / or its satellite virus infection. This invention enables the construction of an economical and efficient animal model for HBV infection, which is of great significance for antiviral research and drug development against HBV and / or its satellite viruses.