56 results about "Survival of the fittest" patented technology

A new approach is proposed that contemplates systems and methods to provide harmonious tiling layout for a single heterogeneous data feed with a unique and brief syntax. The approach provides solutions to fit shapes into a container without having any holes by automatically providing the most optimum harmonious layout and tile presentation “win-out” over time, and a survival of the fittest of visual presentation based on configurable metrics. A single user interface combines the action of searching and publishing as a single process whereby search results are formatted with the intention to facilitate publishing the chosen items.

The invention discloses a universal gravitation search-based unmanned plane air route planning method, which comprises the following eight steps: 1, establishing an unmanned plane air route planning mathematical model; 2, setting initialization improved universal gravitation search algorithm parameters and battlefield environmental parameters; 3, randomly initializing N routes and initial positions and accelerated speeds of various particles, and establishing a rotating coordinate system; 4, calculating threat cost of each route according to threat information and the mathematical model; 5, updating inertial mass Mi(t) of the particles according to a weight-based rule; 6, calculating the sum of accelerated speeds of each particle in all directions according to a universal gravitation standard, and updating the speeds of the particles according to a group information speed updating rule; 7, updating the position of each particles according to the updated speed of each particle and the choice of survival of the fittest; and 8, if the number of iterations is greater than the maximum number of iterations, exiting a circulation, otherwise, returning to the step 4 for next iteration. The obtained optimal air route coordinate is subjected to coordinate inverse transformation and a result is output.

The invention discloses a robot path planning method adopting multi-subgroup coevolution particle swarm optimization to perform real-time rolling optimization obstacle avoidance processing, which can enable a robot to realize autonomous navigation in a working condition with stationary obstacles at unknown positions. The method has the following advantages: the method can realize autonomous navigation of the robot in a working condition with stationary obstacle at unknown position; the method introduces group mass center strategy to the multi-subgroup coevolution, so as to increase the search capacity of the population; compared with a conventional path planning method which adopts PSO (Particle Swarm Optimization) and CPSO (Coevolution Particle Swarm Optimization), the method provided by the invention adopts survival of the fittest strategy, thereby being more advantageous in respect to rate and accuracy of evolution convergence; the method provided by the invention can real-timely plan an effective obstacle avoidance path in a complex obstacle environment, and has the advantages of good robustness, high solving efficiency, and the like.

The invention discloses a particle swarm optimization method based on survival of the fittest and step-by-step selection. The method mainly comprises the steps that particles are divided to two sets in the operating process, the first set of particles are superior particles, and the second set of particles are inferior particles. A solution space is searched for in the global scope through a species, and the global searching ability is enhanced; after each time of evolution, m the best particles in the species are maintained, the position spaces of better particles of the m particles are selected as new solution spaces, new particles are selected to replace the position of poor particles in the species in the new solution spaces, in this way, the optimal particles can be approached step by step, and the optimal solution is found out. The searching ability of the particle swarm optimization method is enhanced, the defects that a fundamental particle swarm optimization algorithm easily falls into local extremum or premature convergence or stagnation are overcome, and the optical values of parameters to be optimized can be more accurately and quickly found out.

A new approach is proposed that contemplates systems and methods to provide harmonious tiling layout for a single heterogeneous data feed with a unique and brief syntax. The approach provides solutions to fit shapes into a container without having any holes by automatically providing the most optimum harmonious layout and tile presentation “win-out” over time, and a survival of the fittest of visual presentation based on configurable metrics. A single user interface combines the action of searching and publishing as a single process whereby search results are formatted with the intention to facilitate publishing the chosen items.

The invention belongs to the technical field of identifying synchronous generator parameters, and relates to a method for identifying the synchronous generator parameters by an improved evolution algorithm. Starting from an randomly-generated initial generator parameter group, optimal solution is searched through generation of an initial group, fitness calculation, recombination, mutation and selection, and stopping operation according to operating principles of struggle for existence and survival of the fittest by using actual measurement data in a power management unit (PMU) in a wide area measurement system (WAMS); and an improved evolution strategy algorithm of biomimicry is taken as optimizing theoretical basis, the decoupling of a direct axis and a quadrature axis of the synchronousgenerator and steady state and transient state are processed separately, an initial practicable parameter group is established through design parameters, and a differential equation of a higher orderis calculated by selecting a high-precision improved Euler method, so that the output variable set by the generator is solved, the optimizing process is realized through recombination, mutation and selection of the initial group, and the synchronous generator parameters are identified. The method is simple and has a reliable principle, and the correctness of the parameter identification is high.

The invention relates to a search site with human-aided translation function, which belongs to the technical field of internet. The technical issue to be solved is that a site that a translated foreign web page can be stored in the network space so as to ensure that the translated foreign web page can be downloaded by a search engine conveniently and also can be searched by net friends, an interpreter can add the network space with zero limit and set bilingual material permission (sharing, paying, allies or secrecy), and the reasonable selection with a 'survival of the fittest' mode (trust, observation, mistrust or original state) to the added interpreter can be carried out and the search result ranging lists leaded by the net friends are added is provided.

The invention discloses a genetic algorithm-based pilot allocation method in a large-scaled antenna system. The purpose of improving a sum rate of a user in the system serves as a target, genetic algorithm is adopted, and the optimal pilot allocation scheme is obtained. Firstly, a gene code concept is introduced, different pilot allocation schemes are generated through exchanging the codes, the sum rates of the user in the system in different pilot allocation schemes are further calculated, and a guideline for the survival of the fittest is adopted, a corresponding gene code is kept; secondary, reproduction, crossover and mutation operation are carried out on the kept gene code, and a new gene code is generated; and finally, the above steps are repeated, through multiple turns of survival of the fittest and gene crossover mutation, the pilot allocation scheme with the maximal user sum rate in the system is obtained. The method of the invention adopts the genetic algorithm, limitation of a local optimal solution is broken, pilot pollution influences of the large-scaled antenna system are lessened, and complexity of the pilot allocation strategy is reduced.

The invention provides a method for updating a deteriorated grassland bluegrass lawn at low cost in the north. Weed control, pruning height control, lawn partition area and turf block size determination, rooting hastening with grass blocks soaked in pesticide, determination of the number of turf blocks planted in a community per square meter and planting positions, compacting, watering, sand covering, growth regulator application and other technologies are applied, on the basis of the natural rules of plant interspecific competition and the survival of the fittest, zoysia japonica can easily invade the deteriorated grassland bluegrass lawn due to strong creeping stems and the strong growing vigor and competitiveness, other grass seeds can hardly invade the lawn once the population of the zoysia japonica is formed, and therefore the aim of updating the deteriorated grassland bluegrass lawn at low cost is achieved. The effective method can be applied to the production practice of landscaping in a large area, can solve the problem of a deteriorated cool-season lawn, and can lower updating cost.

The invention discloses a rough set attribute reduction method based on genetic algorithm. The method comprises: (1) obtaining a core of a decision table, and generating an initial population randomly by initialization; (2) controlling the initial population to correspond to the gene position thereof through the attribute core, and calculating a fit value according to fitness function; (3) repairing the population by adopting modification operator; (4) judging whether to satisfy the algorithm terminating condition, if yes, outputting the best individual, and if no, proceeding to (5); (5) performing survival-of-the-fittest operation to individuals in the population by using a selection operator in the genetic algorithm; (6) performing interlace operation to the population with interlace probability by adopting one-point interlace rule; and (7) performing mutation operation to the population according to a heuristic mutation operator with the gene position corresponding to the attribute core not mutated. The technical scheme of the invention is designed to rapidly and efficiently obtain the smallest reduction of attribute in the decision table and efficiently improve information accuracy.

The invention relates to an unmanned aerial vehicle path planning method and specifically relates to an unmanned aerial vehicle three-dimensional path planning method based on multi-strategy improvedparticle swarm optimization algorithm. Simulation modeling is carried out for two real terrains: a hilly terrain and a mountain terrain, inertia weight based on linear decreasing and a Logistic mapping function in a chaos strategy are imported into the particle swarm optimization algorithm, and survival of the fittest strategy is employed for individuals with low adaptive values in an optimizationprocess, thereby providing a new improved IPSO algorithm. An experiment result shows that under the hilly terrain, planned path length of the provided IPSO algorithm is reduced by 5.2% relative to that of AWPIO, and the planned path length of the IPSO algorithm is reduced by 5.9% relative to that of PSO; time consumption of the IPSO algorithm is reduced by 5.25% relative to that of the AWPIO, andthe time consumption of the IPSO algorithm is reduced by 4.15% relative to that of the PSO; under the mountain terrain, the planned path length of the provided IPSO algorithm is reduced by 1.3% relative to that of the AWPIO, the planned path length of the IPSO algorithm is reduced by 2.69% relative to that of the PSO; and the time consumption of the IPSO algorithm is reduced by 24.3% relative tothat of the AWPIO, and the time consumption of the IPSO algorithm is reduced by 26.3% relative to that of the PSO. The IPSO is a smart algorithm relatively applicable to path planning.

The invention discloses a method for planning route of an unmanned surface vehicle based on universal gravitation search. The method comprises the following steps: firstly, establishing a mathematical model of the surface unmanned vehicle, and initializing parameters of the method; secondly, randomizing a plurality of paths and an initial position and an accelerated speed of each particle, and establishing a rotating coordinate system; thirdly, updating inertia mass of each particle according to a rule of dynamic inertia weight, and updating the speed of each particle according to an improved universal gravitation method; finally, updating the position of each particle according to an updated speed of the particle and a selection principle of survival of the fittest; if the number of iterations is greater than the maximum number of iterations, exiting a loop; otherwise, returning to the previous step for entering into the next iteration; performing coordinate inverse-transformation on the obtained optical path coordinate, and outputting results.

The invention discloses a crowd-sourcing cooperative sensing motivation method based on evolutionary game. The method comprises the following steps: taking a smart phone and wearable equipment as participants in a crowd-sourcing sensing system, thereby collecting data from the activity surrounding environment of the people, and uploading the data to an application service platform through an available network, wherein the service platform processes the data of the participants and extracts the query required information. The basic rule: survival of the fittest (replicate dynamic rule) in the evolutionary game is applied to the crowd-sourcing sensing, the fitness in the evolutionary game is the earnings of the user; since the evolutionary aim is to produce the individual with high fitness in the next generation of evolutionary competition and eliminate the individual with low fitness, the user participant is encouraged to perform cooperation and information exchange, and the user totalearning is maximized and finally achieves the balance.

The invention belongs to the technical field of image processing, and particularly discloses a graphic image sorting method based on a genetic programming algorithm. The method comprises the steps that (1) image feature sets and training feature sets are constructed; (2) first-stage relevant parameters are set; (3) the image features are extracted; (4) species are initialized and fitness is estimated; (5) individuals are subjected to the survival of the fittest, superior individuals are subjected to crossover and variation, and the fitness is estimated; (6) the individuals are subjected to partial searching; (7) the species are estimated, and if the crossover and variation operation is completed is judged; (8) the good species are selected, and if evolution is over is judged; (9) the species are again initialized according the new features; (10) the better species are selected for crossover and variation; (11) an image matching model is output according to the optimal individual, and an individual tree is decoded to obtain new image features. The training model generated through the method can effectively improve image sorting precision.

The invention discloses a target ship direction estimation method based on a differential evolution mechanism. The method includes the following steps that firstly, a multi-variation strategy is blended in a differential evolution optimization algorithm, so that the improved differential evolution mechanism is formed, wherein the multi-variation strategy comprises three processes of variation, hybridization and selection; secondly, the improved differential evolution mechanism acquired in the first step and a likelihood function are combined and used for estimating the DOA direction of a target ship. According to the method, the multi-variation strategy and a survival of the fittest mechanism are firstly blended in the differential evolution optimization algorithm and then the improved differential evolution mechanism and the likelihood function are combined and used for estimating the DOA direction of the target ship. Tests show that the reasonability of an improved differential evolution scheme is shown through the method and the method has better optimization performance than other algorithms; in addition, the improved differential evolution scheme is applied to the target ship direction estimation method, effectiveness is achieved, and the robustness of the method is better than that of other traditional methods.

This invention discloses a method and an apparatus for automatic regulating core with waveguide optical fiber based on genetic algorism, which is characterized by forming mapping between regulating-core physical parameter and genetic gene model, describing a certain relative place between waveguide optical axis and fibre-optical optical axis when regulating core by individual concept, taking coupling efficiency as adapting function to judge and adjusting constantly the related place between waveguide and optical fiber through generations of genetic manipulation such as selecting regeneration, cross-over, variation according to genetic principle about survival of the fittest until astringing in the optimal coupling place, and adopting up-rush method adjusting four-axis in little neighborhood when realizing the iliofemoral ligament of waveguide and optical fiber is lower than 2dB to find the optimum place between waveguide and optical fiber and finish the process

The invention discloses a global optimization, searching and machine learning method based on a Lamarck's principle of inheritance of acquired characters. The global optimization, searching and machine learning method comprises the steps of: step 1, constructing an objective function f(x) according to a problem object; step 2, encoding the problem object into a chromosome of a genetic algorithm, automatically calculating or inputting operation parameters, and performing initialization; step 3, performing iterative optimization on a current (kth generation) population Gk={Pk<1>, Pk<2>,..., Pk<S>} by adopting a Lamarck's ''operator of inheritance of acquired characters'' and a ''use and disuse operator'' according to evaluation of the objective function f(x); step 4, and outputting an optimal solution set of the problem object. The global optimization, searching and machine learning method integrates the ''inheritance of acquired characters'' and ''use and disuse'' natural laws of Lamarck's evolution theory with the modern ''epigenetics'' and the ''survival of the fittest'' natural law of Darwin's evolution theory, simplifies the structure of the genetic algorithm, overcomes the multiple technical defects of the existing algorithm, and improves the efficiency, global optimality and sustainability of late evolution of the algorithm, so that more global optimization, searching and machine learning problems can be better solved.

The invention discloses an interplanting method for maize and sunflowers and relates to the technical field of agricultural product planting. The method comprises the following steps: (1) land selection; (2) land preparation; (3) maize seedling raising; (4) sunflower seedling raising; (5) transplanting and field planting; (6) field management; and (7) harvesting. According to the method, survival of the fittest is achieved by adopting an interplanting mode, and meanwhile, the yield and quality of the maize and the sunflowers are improved; and the planting method is scientific and reasonable, so that the cost can be effectively reduced, and the economic benefit can be improved.

The invention discloses a method for detecting outlier data from large-scale high dimensional data based on a genetic algorithm, and belongs to the technical field of outlier data mining. The method comprises the steps of (1) sample discretization and encoding, namely encoding the high dimensional data and enabling each individual to correspond to one character string, selecting a sparse coefficient as a fitness function and taking the coefficient as a criterion for judging whether the individuals are good or bad, (2) loop iteration, namely maintaining a group which comprises a plurality of individuals and updating the group continuously by use of crossing, mutation and selection according to the principle of survival of the fittest, and (3) decoding to obtain the outlier data, namely decoding the group obtained at last by corresponding to the corresponding sample data and then finding the hidden outlier data in the sample data. The method for detecting the outlier data from the large-scale high dimensional data based on the genetic algorithm is capable of effectively and quickly finding out the hidden outlier data from the large-scale high dimensional data.

The invention discloses a preparation and application methods of an efficient diluent for giant salamander sperm and relates to the technical field of giant salamander cultivation methods. The efficient diluent is prepared by medical 0.9% sodium chloride injection, double distilled water, glycerin, glucose, sodium citrate and mycillin. During use, the diluent is used to dilute the sperm, the diluted sperm is used to perform insemination on eggs, and the eggs are submerged by the diluted sperm in a way that the diluted sperm is 1cm higher than the eggs during the insemination. The preparation and application methods have the advantages that the giant salamander sperm is diluted by the combined diluent, the swimming range of sperms in a bath solution is expanded, the bonding surfaces of the sperms and the eggs is enhanced greatly, the user amount of pure sperm in each insemination is reduced, the sperms with low activity cannot swim into egg envelopes to inseminate the eggs, malformed or weak residual bodies are reduced greatly, survival of the fittest is achieved before the insemination, and the quality of the insemination is increased effectively.

A method is provided for deriving a near-optimal fuzzy automaton for a given separation problem. The method includes the steps of: forming a first generation population (24) of fuzzy automata, where the first generation population of fuzzy automata includes a plurality of fuzzy automata; performing a mutation operation (28) on each fuzzy automaton in the first generation population of fuzzy automata; reproducing the first generation population of fuzzy automata using a survival of the fittest operation (30, 32, 34); and applying a cross-over operator (36) to the reproduced first generation population of fuzzy automata, thereby yielding a next-generation population of fuzzy automata. A near-optimal fuzzy automaton is identified by evaluating the performance (38) of each fuzzy automaton in the next-generation population; otherwise the methodology is repeated until a near-optimal fuzzy automaton is derived for the given separation problem.

A network product display method, apparatus, system, server and terminal are disclosed in the present invention, and belong to the field of computer technology. The method includes: collecting behavior events transmitted by at least one terminal, and the behavior events are generated according to operations on the displayed network product; adjusting the lifetime of the network product according to the behavior events, and the lifetime is the remaining display time of the network product. The present invention, by collecting the behavior events generated according to the operations on the network product and adjusting the lifetime of the network product according to the collected behavior events, solves the problem that lots of server resources are occupied when more network products are released by the server, and achieves the effect that the server resources occupation is reduced and the survival of the fittest of the network products is realized.

The invention relates to a method for cultivating a mother strain of nodule bacteria. The method comprises a strain domesticating and culturing step: carrying out inferior elimination and superior selection by virtue of methods of environmental screening, antagonism competition and survival of the fittest in a simulated target environment, so as to find and cultivate the strain matched with the target environment and the variety. By virtue of the method, the problems that the nodule bacteria are poor in adaptability and the inoculating scaffolding rates of leguminous plants are low are well solved, the action of the nodule bacteria is fully exerted, and a product meets the requirements of organic agricultural products and is low in cost, high in yield and good in benefit.

The invention relates to a pilot distribution method based on an artificial fish swarm algorithm. The concept of artificial fish is introduced at first, each artificial fish corresponds to a pilot distribution scheme of a cell in a large-scale antenna system, different pilot distribution schemes are generated by exchanging codes, in order to calculate a user sum rate in the system under the different pilot distribution schemes, and meanwhile, a criterion of survival of the fittest is adopted to retain a pilot distribution sequence with a relatively large system sum rate; tailgating and clustering operations are carried out on the retained pilot distribution sequence, the system sum rate is evaluated after the corresponding operations, and the pilot distribution sequence with the relatively large rate is sent to a bulletin board; and finally, the steps are repeated, the survival of the fittest and the artificial fish tailgating and clustering behaviors are carried out for multiple turns to obtain the pilot distribution scheme with the largest user sum rate in the system. The pilot distribution method provided by the invention breaks the limitation of the local optimal solution, the user sum rate is maximized, and the pilot pollution influence and the complexity of the pilot distribution policy of the large-scale antenna system can be reduced.

A new approach is proposed that contemplates systems and methods to provide harmonious tiling layout for a single heterogeneous data feed with a unique and brief syntax. The approach provides solutions to fit shapes into a container without having any holes by automatically providing the most optimum harmonious layout and tile presentation “win-out” over time, and a survival of the fittest of visual presentation based on configurable metrics. A single user interface combines the action of searching and publishing as a single process whereby search results are formatted with the intention to facilitate publishing the chosen items.

The invention provides a speech input method of a mobile terminal. Meanwhile, a voice message inputted by a user is recognized on the basis of two kinds of different input methods. Two recognition results are compared. According to a comparison result, the recognition results are displayed to the user. Accuracy of speech recognition is improved by adoption of multiple input methods for recognitionand matching. In addition, two input methods are scored cumulatively on the basis of selections made by the user to the recognition results. After the scores reach the threshold value, a speech recognition module of an input method with a low credit is eliminated. Therefore, a signal module is kept and deleted on the basis of an input method. The input method is configured in a more flexible manner. User experience is improved. Meanwhile, utilization rate of storage space of the terminal is increased. Finally, a novel input method or a novel speech input module replaces an eliminated input method or an eliminated speech input module, which reflects survival of the fittest in speech recognition. Therefore, accuracy of speech recognition is improved so that user experience is improved.

A system and method provide advertising power to any person wishing to express an opinion, by distributing that message broadly to the public, regardless of the form of media or demographic groups, and provide a mechanism for supporting viewers to push it forward, and measures its success compared to competing messages. The invention provides access to advertising and dissemination of ideas to the masses of people, regardless of their membership in a social media or party or demography or geography or financial position. After the message is initiated, the invention allows for the public to support it by paying for additional views or clicks or advertisements which themselves allow for further support and so on. From that point forward, the message is propagated by the principle of survival of the fittest, where all messages are heard, but only the most widely accepted survive and grow.

The invention discloses a multipurpose culture vessel for assisting a reproduction test. The multipurpose culture vessel comprises a culture vessel and a vessel cover, wherein the culture vessel comprises a vessel main body, an ova placing cup, a plurality of sperm placing cups and a plurality of sperm channels; a columnar supporting platform is arranged in the middle of the vessel main body; theova placing cup is fixed on the columnar supporting platform; the sperm placing cups are all arranged in the vessel main body in a manner of surrounding the ova placing cup; the height of the rims ofthe sperm placing cups is slightly lower than that of the bottom of the ova placing cup; a sperm guide-out hole is formed in the outer wall of each of the sperm placing cups near the rim; a sperm guide-in hole is formed in the outer wall of each of the sperm placing cups near the bottom; each of the sperm channels is correspondingly fixedly between each of the sperm guide-out holes and each of thesperm guide-in holes that are opposite. The multipurpose culture vessel has the beneficial effects that the sperm channels are slantingly arranged, so that the survival of the fittest in moving of sperm can be reflected, and the sperm with best activity can only pass the sperm channels and move to the ova placing cup to be combined with high-quality ova, therefore, the multipurpose culture vesselis strong in practicability and good in using effect.

The invention provides a WLAN antenna combination method and system. The method includes the steps that on-off states of all antennas are endowed with antenna weights respectively, antenna weight sequences are formed according to selection of the antennas, and multiple antenna weight sequences are selected to constitute a contemporary antenna weight set suitable for genetic algorithm operation; pairing, crossover and variation are carried out on the antenna weight sequences to obtain a variation antenna weight set; if a variation result does not meet the requirement, selection, crossover and variation steps continue to be conducted on the mutation result till the antenna weight sequence with an adaptive value f larger than a threshold set by the system is found. A genetic algorithm is used for searching for antenna combinations meeting communication quality requirements, each crossover and variation result adaptive value can be superior to the previous crossover and variation result adaptive value by effectively using criteria of survival of the fittest and crossover-and-variation in the genetic algorithm, the antenna combinations meeting the communication quality requirements can be found rapidly, the number of times of section of the antenna combinations is reduced, system expenses are lowered, and the communication effect is improved.