14 results about "Natural selection" patented technology

The invention provides a method for solving the computing power resource utilization rate based on a genetic algorithm, and relates to the technical field of computing power resource utilization. Comprising the following steps of S1, performing population initialization, randomly generating a group of initial solutions, and representing a computing power resource allocation scheme by each solution; s2, adaptability evaluation: defining a fitness function to calculate the fitness value of each individual; s3, genetic operation: performing selection operation, crossover operation and mutation operation to generate a new offspring; s4, generating a new-generation population, and selecting the most excellent individuals to form the new-generation population; s5, performing iterative computation, iteratively executing the genetic operation and the new generation population generation step, and continuously updating the population until a termination condition is met; and S6, outputting a result, and identifying an optimal solution or a group of excellent solutions from the current population. By simulating natural selection and genetic mechanisms in the biological evolution process, allocation of computing power resources is optimized, so that the resource utilization rate and the system performance are improved.

The invention discloses a multi-modal large model fusion training method and system based on a biological evolutionary algorithm, and relates to a method and system for performing fusion and model selection on a multi-modal large model by using a framework of the biological evolutionary algorithm, selecting characteristic parameters and capabilities to form different models, performing fusion training in a manner similar to biological evolution, and obtaining high-performance AI (artificial intelligence). According to the concept, natural selection, genetic variation and other mechanisms in biological evolution are mainly used for reference and applied to the optimization process of an artificial intelligence model, a self-adaptive training system is formed, and the AI performance is continuously improved in continuous iterative training.

This invention discloses a multi-unit composite stress tiered breeding device and method for juvenile large yellow croaker, belonging to the field of aquaculture breeding technology. The device uses a central control unit as its sole core, forming a fully integrated unidirectional closed-loop drive system. Four independent breeding units are connected through a transparent channel with a centrally located aeration head, forming a physical flow-limiting isolation structure. Each unit independently regulates water temperature, salinity, and dissolved oxygen, creating a multi-factor composite stress gradient. The breeding method employs a three-factor linear equal-gradient synergistic progressive setting, utilizing the juvenile fish's autonomous adaptation and avoidance instincts to achieve cross-unit migration and natural selection. Combined with contour recognition and dynamic tracking algorithms, it monitors the fish population status and mortality rate in real time, and identifies superior offspring with comprehensive stress resistance through secondary verification under extreme stress. This invention offers high screening accuracy and automation, increasing the survival rate of superior individuals by over 40%, reducing labor costs by over 60%, and allowing for flexible adjustment of device parameters. It can be extended to the stress resistance breeding of other marine economic fish species.

The present invention provides a method for user grouping of a millimeter wave massive MIMO system based on a genetic algorithm, which adopts a survival of the fittest genetic mechanism to perform user grouping. From a genetic point of view, dynamically adjusting the user grouping method to ultimately achieve stable grouping is a genetic evolutionary process, in which different user groups constitute different elites in a generation, and the genes (or sub-individuals) of the elites are crossed to produce new offspring, and the parent generation and offspring are simultaneously subjected to preferential treatment to complete the natural selection mechanism, and finally a stable user grouping is obtained. Compared with the early heuristic method, the present invention has a greater advantage in performance; compared with the greedy method, its complexity is significantly reduced while the performance is similar.

This invention discloses a salt-stress-tolerant Bacillus bellis and its applications. It relates to the field of agricultural microbiology. The salt-stress-tolerant Bacillus bellis ZY-2, with accession number CGMCC NO.34345, is described, along with its related applications. The salt-stress-tolerant Bacillus bellis provided by this invention has broad application prospects in resisting saline-alkali environments. Specifically, this strain can be used as the original material to breed strains with better tolerance to saline-alkali environments and more significant effects on promoting wheat growth and development through natural selection, artificial mutation breeding, and genetic engineering breeding, thereby reducing the use of chemical amendments. Furthermore, it exhibits strong tolerance to saline-alkali environments and demonstrates good promotion of wheat growth and development under salt stress.

The invention provides a method for measuring the mutation rate of a sexual reproduction animal whole genome level nucleotide germline. The method comprises the following steps: (1) performing genome sequencing on a to-be-detected species to obtain sequences of all coding proteins of the to-be-detected species; (2) constructing a phylogenetic tree of a to-be-tested species; (3) obtaining the divergence time Tdivergence between the species to be detected and the sibling species; (4) optimizing the phylogenetic tree of the species to be tested; and (5) obtaining the annual germline mutation rate [mu] year of the species to be detected. The principle of the method is as follows: neutral regions or neutral sites are widely distributed in a genome, and mutations generated at the positions are generally not influenced by natural selection; the mutation rate of the germline can be calculated by analyzing the change of the variation frequency of the sites along with time. The method provided by the invention not only is widely applicable to sexual reproduction animal species with obtained genome or transcriptome data, but also is accurate and efficient, fills up the blank of the prior art, and has great significance in theoretical research and practical application of biomedical engineering.

The present invention provides a process logistics scheduling method and system, including: using a multi-objective group intelligent algorithm based on trend neighborhood search for scheduling optimization, including: population initialization step: constructing the chromosome construction of individuals in the population, and performing initialization operations on all individuals in the population; mutation operation step: generating new individuals by randomly changing certain genes on the chromosome to form a progeny population, increasing the diversity of the entire population, and expanding the search space, including exchange mutation or reverse mutation; selection operation step: simulating the characteristics of survival of the fittest in natural selection, by calculating the objective function value of each individual in the solution population, obtaining the fitness value of the individual, and allowing individuals with good fitness to survive in iterations, while keeping the size of the population constant. The present invention can ensure the consistency of chromosome design with the process, and at the same time ensure the effectiveness of population evolution, simple coding, simple rules, and easy operation.

The invention discloses a communication equipment repair spare part topological layout optimization method based on an SAGA, and the method employs a genetic algorithm to simulate the natural selection and genetic process, carries out the effective search in a large-scale solution space, improves the search breadth and quality of a solution, and deals with the challenge that the solution space is large and complex. The calculation bottleneck of an accurate solution method in a large-scale complex problem can be avoided, the quality of the solution can be continuously optimized through multi-generation iteration, and the solution requirement of the complex problem is met. In order to cope with the challenge that a plurality of locally optimal solutions may exist, a physical annealing process is simulated by using a simulated annealing-genetic algorithm, a poorer solution is allowed to be accepted at the initial stage, and the algorithm is gradually concentrated on a better solution as the temperature is gradually reduced, so that the trouble of the locally optimal solutions is effectively avoided; the bottleneck of a traditional accurate solution method in large-scale complex problems can be overcome, the search flexibility and robustness can be improved, and it is ensured that a solution close to global optimum is obtained.

The invention belongs to the technical field of biology, and discloses a breeding method and application of an aroma generating strain with high ethanol tolerance. According to the breeding method provided by the invention, automatic and high-throughput adaptive evolution treatment is realized by utilizing a microbial micro-droplet culture system, and the adaptive evolution treatment is organically combined with a mutation breeding technology, so that the advantages of a high-ethanol-tolerance strain obtained by random mutation in the mutation breeding process are directionally enhanced; therefore, the directionality of the breeding process is improved; meanwhile, the mutation breeding technology can accelerate the natural selection process to a certain extent and shorten and simplify the adaptive evolution treatment period by providing abundant random mutations; through the organic synergistic effect of the adaptive evolution treatment and the mutation breeding technology, the precise and efficient breeding of the aroma generating strain with high ethanol tolerance is realized, and the method has a good application value for improving the production quality of white spirit.

The invention discloses a voxel robot structure optimization design method based on morphological statistical modeling, and the method comprises the steps: constructing and training a depth probability generation model which is based on a multi-level representation mode and comprises a task embedding layer, a morphological latent variable generation layer and a voxel distribution generation layer; performing morphological design on the target task by using the generative model, including inputting a task code, generating a morphological latent variable, and generating a voxel robot form based on the morphological latent variable; in the generation process, the morphological pool is used for storing morphological samples of intergenerational sampling and the fitness of the morphological samples, the morphological samples are screened and optimized based on the continuous natural selection sampling technology, and the optimization result is fed back to the generation model; for different task targets, a model and a sample selection strategy are generated through iterative optimization, and multi-task adaptability design is achieved. According to the method, the morphological samples are generated through the generative model, the morphological pool is introduced to store the samples and the fitness thereof, the wide applicability of description is kept, and the sample utilization rate is effectively improved.

The invention discloses a salt stress resistant bacillus velezensis strain and application thereof. Relates to the technical field of agricultural microorganisms. The invention relates to salt stress resistant bacillus velezensis ZY-2 with the preservation number of CGMCC (China General Microbiological Culture Collection Center) NO.34345, and provides related application. The salt stress resistant bacillus velezensis provided by the invention has a wide application prospect in a salt and alkali resistant environment. Specifically, the strain can be used as an original material to breed the strain which is better in salt and alkali environment tolerance and more remarkable in wheat growth and development promotion effect through natural breeding, artificial mutation breeding, genetic engineering breeding and other methods, so that the use of chemical modifiers and the like can be reduced. In addition, the strain has a strong tolerance effect on a salt-alkali environment, and has a good promotion effect on growth and development of wheat under salt stress.

The application provides a water transportation science data standard system construction method, which comprises the following steps: constructing a water transportation science ontology, generating a standard gene sequence for multi-source heterogeneous water transportation data (such as AIS message, hydrological data and the like) and embedding the data unit to form a data set carrying the standard gene. Syntax, semantics and behavior verification are performed through a three-layer verification model, and based on the result, the fitness of the gene variants is evaluated and evolved by using a natural selection mechanism. Then, version control and conflict arbitration are performed through a three-branch government framework to generate standard government decisions, and finally, the water transportation science data standard system is output by using a digital twin simulation system for closed-loop verification. The application realizes the embedding of the standard in the data, the data-driven evolution and the prior verification, and solves the problem of the disconnection between the standard and the data.

The application provides a method for measuring the whole genome level nucleotide germline mutation rate of an animal of sexual reproduction. The method comprises the following steps: (1) performing genome sequencing on a to-be-tested species to obtain the sequences of all protein-coding genes of the to-be-tested species; (2) constructing a phylogenetic tree of the to-be-tested species; (3) obtaining the divergence time T between the to-be-tested species and a close relative species divergence ; (4) optimizing the phylogenetic tree of the to-be-tested species; (5) obtaining the annual germline mutation rate mu of the to-be-tested species year . The principle of the method is that neutral regions or neutral sites are widely distributed in the genome, and mutations at these positions are usually not affected by natural selection; by analyzing the variation frequency of these sites over time, the germline mutation rate can be calculated. The method described in the application is not only widely applicable to animal species of sexual reproduction that have obtained genome or transcriptome data, but also accurate and efficient, fills the gap in the prior art, and has important significance for theoretical research and practical application of biomedical engineering.

A five-axis cutter feeding and retracting method based on a genetic algorithm belongs to the technical field of numerical control machining and comprises the following steps: step 1, discretizing a workpiece space; defining a cutter as a cylinder, and segmenting a cutter path by using a linear sampling method; 2, gene coding processing, wherein the chromosome of each individual is coded into a path point sequence; 3, performing population initialization processing, randomly generating Group Size individuals, and calculating and selecting the Group Size individuals with relatively high fitness to form an initial population; 4, performing gene recombination treatment based on individual fitness; 5, performing gene mutation, namely performing mutation on individual genes according to a mutation probability; 6, natural selection is conducted, population individual fitness is ranked, and a population is reformed; and carrying out iterative solution on the step 4, the step 5 and the step 6. According to the scheme, tool retracting can be achieved at any position, the optimal tool retracting track is automatically selected, collision is prevented in the tool retracting process, and the tool retracting efficiency can be improved.