15 results about "Genetic Evolution" patented technology

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 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 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 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 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 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.