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88 results about "Selection operator" patented technology
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User Interface for Selecting Operators
The present invention relates generally to a method of identifying data delivery parameters relating to delivery of data accessible from a network location via a communications service provider. Embodiments of the invention are particularly well suited to identifying delivery parameters when the delivery of data is metered, such as when data are delivered to terminals connected to mobile networks.
Owner:APPLE INC
Mobile-robot route planning method based on improved genetic algorithm
InactiveCN106843211AImprove environmental adaptabilityStrong optimal path search abilityPosition/course control in two dimensionsGenetic algorithmsProximal pointTournament selection
The invention relates to a mobile-robot route planning method based on an improved genetic algorithm. A raster model is adopted to preprocess a working space of a mobile robot, in a rasterized map, an improved rapid traversing random tree is adopted to generate connections of several clusters between a start point and a target point, portions for the mobile robot to freely walk on in the working space are converted into directed acyclic graphs, and a backtracking method is adopted to generate an initial population which is abundant in diversity and has no infeasible path on the basis of the directed acyclic graphs. Three genetic operators, namely a selection operator, a crossover operator and a mutation operator, are adopted to evolve the population, wherein the selection operator uses a tournament selection strategy, the crossover operator adopts a single-point crossover strategy, and the mutation operator adopts a mutation strategy which displaces an aberrance point with an optimal point in eight-neighbor points of the aberrance point. A quadratic b-spline curve is adopted to smooth an optimal route, and finally, a smooth optimal route is generated. According to the method, the route planning capability of the mobile robot under a complex dynamic environment is effectively improved.
Owner:DONGHUA UNIV
Method and system for optimizing software test case
InactiveCN103810104AReduce participationAvoid situations where test performance is affectedSoftware testing/debuggingMutation operatorSystem under test
The invention discloses a novel method and system for optimizing a software test case. According to the invention, the advantage of analytic hierarchy process on determining weighted values, as well as the technical advancement of the ant colony algorithm and genetic algorithm on determining the simplest and first priority ordering case subset are utilized. The method comprises the following steps: determining the weighted value of each functional requirement of a to-be-tested system by using the single hierarchical arrangement and total ordering of the analytic hierarchy process as well as the quantification of consistency testing; determining a test case subset, with full covering on all functional requirements and minimum operation cost, by combining the ant colony algorithm with the obtained weighted values and through an essential strategy, a redundancy strategy and a greedy strategy; determining a new estimation formula by combining the genetic algorithm with the obtained weighted values and on the basis of obtaining the simplest case subset; determining a test case sequence with highest error detection rate by a selection operator, a crossover operator and a mutation operator.
Owner:中国人民解放军63863部队
Apparatus, method, computer program and mobile terminal for processing information
InactiveUS20080005087A1Increase speedImprove cache hit ratioSubstation equipmentSpecial data processing applicationsTemporal informationDisplay device
An apparatus for processing information, includes a memory storing a plurality of content items different in type and metadata containing time information of the content items, a cache processor for fetching from the memory the content item and the metadata of the content item to be displayed on a display and storing the fetched content item and the metadata thereof on a cache memory, a display controller for displaying on the display the metadata of the content items from the cache memory arranged in accordance with the time information and a selection operator selecting metadata corresponding to a content item desired to be processed, out of the metadata displayed, and a content processor for fetching from the cache memory a content item corresponding to the metadata selected by the selection operator by referencing the cache memory in response to the selected metadata, and for performing a process responsive to the fetched content item.
Owner:SONY MOBILE COMM INC
Short-term traffic flow forecasting method based on road network space relation constraint Lasso
ActiveCN103871246AFast and Accurate PredictionDetection of traffic movementSpecial data processing applicationsSelection operatorRoad networks
A short-term traffic flow forecasting method based on road network space relation constraint Lasso is characterized in that road network constraint is realized by the least absolute shrinkage and selection operator Lasso, road network short-term traffic flow is forecast in three steps of road network analysis, model training and real-time forecasting. The invention provides the short-term traffic flow forecasting method based on the road network space relation constraint Lasso, actually measured expressway traffic flow data are combined, an Lasso algorithm is utilized to forecast the short-term traffic flow, a road network correlation analysis and variable selection method is given, and the expressway short-term traffic flow can be forecast relatively, accurately and rapidly.
Owner:NANJING UNIV
Polyclone artificial immunity network algorithm for multirobot dynamic path planning
InactiveCN103412490ARealization of dynamic path planningIncrease diversityAdaptive controlPosition/course control in two dimensionsMutation operatorAlgorithm
The invention provides a polyclone artificial immunity network algorithm for multirobot dynamic path planning, and relates to an improved polyclone artificial immunity network algorithm. According to the polyclone artificial immunity network algorithm, a polyclone artificial immunity network is applied to multiple mobile robot dynamic path planning, mutual influence among robots and influence on the robots of mobile barriers are considered, a computational formula of antibody concentration is defined, diversity of antibodies is increased through clonal operators, crossover operators, mutation operators and selection operators, and the problem of premature convergence of a traditional immune network is solved. Specific antibodies corresponding to antigens in a specific environment are stored, initial concentration of the specific antibodies is increased, response time is shortened, and multiple mobile robot dynamic path planning in an unknown environment is effectively achieved.
Owner:SHANDONG UNIV
Method and device for route optimization of logistics delivery vehicle
InactiveCN105046365AImprove fitnessShort delivery distanceForecastingLogisticsLogistics managementDistance matrix
The invention discloses a method and a device for route optimization of logistics delivery vehicle, and belongs to the technical field of logistics. The method comprises the following steps of: initializing a congestion matrix alpha and a distance matrix D, generating a delivery route weight matrix omega=alpha D, and initializing a population module N<ZQ>; selecting a population size N<X>, a maximum number of generations N<G>, a crossing-over rate beta, a mutation rate gamma and a number of generations n=0, generating an initial route r1 through a greedy algorithm, and performing mutation operation on the initial route r1 to generate N<ZQ>-1 new routes; calculating fitness A<n> of each route of a first generation population formed by the initial route and the new routes, selecting N<X> routes with the highest fitness from the current population by adopting selection operators, and performing crossover and mutation operations on the N<X> routes to generate a population of next generation; updating n=n+1, when n=N<G>, calculating the fitness A<n> of all the routes in the latest population, and selecting the delivery route with the highest fitness in the current population as the optimal route. According to the invention, when the logistics delivery vehicle delivers goods, the delivery time can be as less as possible, and the delivery route can be as short as possible.
Owner:余意 +3
Single-instruction-set heterogeneous multi-core system static task scheduling method
InactiveCN102866912AImprove initialization efficiencyAddress serious deficienciesMultiprogramming arrangementsMutation operatorOptimal scheduling
Provided is a single-instruction-set heterogeneous multi-core system static task scheduling method. The method includes five steps: step 1, population initialization; step 2, fitness value calculation; step 3, selection operator operation; step 4, cross operator operation; and step 5 variation operator operation. A local sequence represents an executing sequence of two tasks without depending relations, population initialization efficiency and effective individual are greatly improved, the executing sequence of the tasks is determined through a pre-order-relation matrix, and defects of a traditional height value method are overcome. The method can widen a hunting range of optimal individuals. When the population scale is large enough, a part of optimal solutions missed by the height value method can be found so as to obtain a more optimal scheduling sequence. For the same task set, finishing time of the whole task set is short, power consumption is low, and a purpose of energy conservation and consumption reduction is achieved.
Owner:CAPITAL NORMAL UNIVERSITY
Secondary structure spatial distance constraint-based protein conformation search method
ActiveCN107609342AMake up for inaccuraciesNarrow down the search spaceSpecial data processing applicationsFeature vectorProtein target
The invention discloses a secondary structure spatial distance constraint-based protein conformation search method. According to the method, feature vectors are formed by utilizing a spatial length ofeach secondary structure in a target protein and information of spatial distance between central residues of every two adjacent secondary structures so as to serve as space limitation conditions under a basic framework of a genetic algorithm, so that a solution space is searched in a relatively small conformation space under the condition that an energy function is given; and meanwhile, the spatial distance information is added in a selection operator, so that the inaccuracy of the energy function is made up and then the accuracy of structure modeling is effectively improved. The invention discloses the secondary structure spatial distance constraint-based protein conformation search method which is relatively high in sampling efficiency, relatively high in prediction accuracy and low incalculation cost.
Owner:ZHEJIANG UNIV OF TECH
Improved method for extracting Fourier transformation infrared spectrum characteristic variable of multi-component gas by aid of TR (Tikhonov regularization)
ActiveCN102608061AFast analysisHigh accuracy of resultsSpectrum investigationColor/spectral properties measurementsGas analysisSelection operator
The invention discloses an improved method for extracting Fourier transformation infrared spectrum characteristic variable of multi-component gas by aid of TR (Tikhonov regularization). The method includes resolving a characteristic variable extracting model into weight sum of the difference of multiple spectral line values; converting an original TR objective function into an objective function based on the model; then adding a bound term of the difference of spectral line positions in the objective function based on the model; realizing optimal functional solution by means of an LASSO (least absolute shrinkage and selection operator) arithmetic based on an Engl's criterion so as to obtain the optimal value of a regressive vector; and obtaining the characteristic variable capable of overcoming interferences caused by spectrum baseline deviation. The accuracy of online multi-component gas analysis results can be improved by the aid of the improved method. The improved method for extracting Fourier transformation infrared spectrum characteristic variable of multi-component gas by aid of TR can be used for multi-component gas quantitative spectrometric analysis application in the fields of gas logging for petroleum and natural gas exploration, quality control and fault diagnosis of products, hardware, chemical engineering and environmental protection.
Owner:XI AN JIAOTONG UNIV
Method for automatically managing and controlling virtual GPU (Graphics Processing Unit) resource in cloud gaming
ActiveCN104216783AAutomate managementReliable cloud gaming serviceResource allocationSoftware simulation/interpretation/emulationComputer moduleSelection operator
The invention provides a method for automatically managing and controlling a virtual (Graphics Processing Unit) resource in cloud gaming. The method comprises the steps of establishing an Auto-vGPU framework; selecting key index data as system input by using an LASSO (Least Absolute Shrinkage and Selection Operator)-based dimensionality reduction algorithm for supporting an input and output model, which fits the low dimension, of the Auto-vGPU framework; automatically controlling the parameter configuration in a vGASA module in the Auto-vGPU framework by utilizing a parameter automatic configuration algorithm of a PI (proportional-Integral) controller, reducing the manual operation, and supporting the Auto-vGPU framework to keep good performance in a dynamic and complicated cloud environment. According to the method provided by the invention, the automatic management on the virtual GPU resource is realized, an LASSO / LARS (Least Angle Regression) dimensionality reduction technology is used, the input capacity of each game in a virtual machine is automatically reduced, and an online controller is also designed through adopting a method for automatically configuring PI parameters according to expected performance.
Owner:SHANGHAI JIAO TONG UNIV
Method for predicting ship fuel consumption according to sea conditions and manipulating conditions
InactiveCN106779137AAchieve sparseSolving Multicollinearity ProblemsForecastingData setSelection operator
The invention discloses a method for predicting ship fuel consumption according to sea conditions and manipulating conditions. The method for predicting the ship oil consumption comprises the steps of firstly acquiring a sample data set through data screening, data integration and normalized processing, then building a multivariate linear regression prediction model, defining a cost function by adopting a least shrinkage and selection operator (LASSO algorithm) based on the sample data set, performing variable shrinkage and parameter selection by combining cross validation and a least angle regression (LARS) algorithm, finally solving LASSO estimation by adopting an Osborne dual algorithm, and calculating to acquire the ship fuel consumption. The method provided by the invention for predicting the ship fuel consumption according to sea conditions and manipulating conditions can establish a function relation between the ship fuel consumption amount and each influence factor, solves a problem of multicollinearity in fuel consumption calculation, improves the ship fuel consumption calculation accuracy and has importance significance for energy conservation and emission reduction of traffic on the sea.
Owner:SHANGHAI MARITIME UNIVERSITY
Wind farm multi-model draught fan optimized arrangement method based on genetic algorithm
InactiveCN103793566ACoding is intuitiveIntuitive and accurate position relationshipSpecial data processing applicationsAlgorithmSquare mesh
Owner:TONGJI UNIV
Satellite remote sensing image fusion method
ActiveCN103942769AIncrease redundancyIncrease independenceImage enhancementImage analysisWave bandSelection operator
The invention discloses a satellite remote sensing image fusion method comprising that: natural color waveband combined intensity I, a ratio R of near-infrared waveband intensity to the natural color waveband combined intensity I, and a normalized difference vegetation index NDVI are respectively calculated with regard to a multispectral remote sensing image with a near-infrared waveband, a red light waveband, a green light waveband and a blue light waveband, and then a basic enhancement operator k1 is established according to the ratio R. A characteristic selection operator k2 and a characteristic smooth operator k3 are established according to the NDVI. A spectrum integrated compensation coefficient S is formed by the production of k1, k2 and k3, and then each waveband value in the image is multiplied by (1+S) so that the obtained result is the result after fusion of all the wavebands. The near-infrared waveband acts as a data source for enhancement processing, and the enhancement operator with clear physical meaning is designed to perform selective characteristic fusion enhancement on the remote sensing image so that the method is simple, operation is rapid, and the method is applicable to multiband satellite images with near-infrared, red, green, and blue spectral data.
Owner:PEARL RIVER HYDRAULIC RES INST OF PEARL RIVER WATER RESOURCES COMMISSION
Multi-intelligent robot task distribution method facing dynamic task
ActiveCN108416488AAvoid deadlockSolve multitasking problemsResourcesDNA computersTask completionLocal optimum
The present invention provides a multi-intelligent robot task distribution method facing a dynamic task which mainly solves the multi-task distribution problem of a task state quantity with time-variant characteristics. The method comprises the steps of: obtaining dynamic task feature parameters, combining intelligent robot ability parameters, and establishing a feature equation of a task point state quantity; according to the feature equation, designing an intelligent robot revenue function; according to the revenue function, designing a genetic algorithm fitness function; further designing agenetic algorithm difference selection operator and a local mutation operator, and providing an algorithm repair strategy; and finally, employing the genetic algorithm to generate an intelligent robot task distribution scheme to complete multi-task distribution. The multi-intelligent robot task distribution method takes obtaining of system maximum return as a target to achieve dynamic multi-taskrapid distribution, solve the algorithm chromosome deadlock problem and avoid that search falls into local optimum, and through a multi-stage distribution strategy, the method can fully deploy intelligent robots in the system to participate in task completion so as to improve the whole efficiency of the system.
Owner:CENT SOUTH UNIV
Data balance method based on genetic algorithm in MapReduce calculation module
InactiveCN103106253AEasy to useReduce processing timeGenetic modelsSpecial data processing applicationsMetadataComputational resource
Provided is a data balance method based on genetic algorithm in a MapReduce calculation module. The data balance method based on the genetic algorithm in the MapReduce calculation module includes: obtaining global Map output information, utilizing the genetic algorithm to conduct combination optimization, collecting and coding metadata, conducting multiple random partition on population, forming a genome through each partition, calculating fitness function values of all subsets in each gene, applying a selection operator to a genome on the basis of evaluating fitness of each gene, utilizing a roulette algorithm to choose a plurality of high quality genes in the genome at random, conducting cross operation on the chosen genes, conducting mutation operation, choosing retained genes according to an elitism strategy after multiple evolutions, decoding the genes to obtain a optical combination of the metadata and guaranteeing that each data quantity which is processed by the reducer is approximate equal. The data balance method based on genetic algorithm in the MapReduce calculation module solves the problem of unbalance input data in the reduce phrase, saves calculation resource and reduces calculation cost.
Owner:XI AN JIAOTONG UNIV
Multi-defect positioning method based on search algorithm
InactiveCN105760295AGood effectEfficiency is feasibleSoftware testing/debuggingMutation operatorGreedy algorithm
The invention discloses a multi-defect positioning method based on a search algorithm. The method includes the steps that 1, the search algorithm at a first stage is executed, wherein the following processing that firstly, a population with multi-defect distribution is initialized through a greedy algorithm, then a selection operator, a crossover operator and a mutation operator are executed to generate a new individual, the new individual is re-inserted into the original population, a next-generation population is formed, and when a terminal condition of the search algorithm is met, a second stage is executed is specially included; 2, multi-defect positioning at a second stage is executed, wherein a final defect distribution combined population is obtained, an executable entity rank is obtained according to candidate defect distribution populations, the executable entity sequence is mapped to a real position of a program, a rank of equivocation coefficients of corresponding program entities is obtained according to multi-defect distribution in the optimal candidate defect distribution population, and the algorithm is completed. The effect of an adopted GAMFal algorithm on the multi (single) defect positioning problem is superior to that of an existing SFL method; only little artificial participation is needed; the efficiency of the algorithm is feasible.
Owner:TIANJIN UNIV
Adaptive genetic algorithm based on population evolution process
InactiveCN106934459AIncrease diversityFast global search capabilityGenetic algorithmsAlgorithmSelection operator
The invention discloses a self-adaptive genetic algorithm based on the population evolution process, including the first step, setting the parameters of the BAGA algorithm, setting the number of iterations of the algorithm, the number of populations in each generation, the discrete precision of the independent variable, and the total number of shooting times , a constant; the second step is to use binary code to generate the initial population; the third step is to judge whether the maximum number of iterations is satisfied, and if so, output the optimal individual of the last generation, which is the optimal value found, otherwise turn to the fourth step; The fourth step is to establish the relationship between the objective function and the fitness function, and then calculate the fitness of each individual and the average fitness of contemporary individuals, save the individual with the largest contemporary fitness, and calculate the evolutionary degree of the contemporary population, the degree of population aggregation, and Balance factor, crossover probability and mutation probability; the fifth step, selection, crossover and mutation operations to generate new populations, the selection operator uses roulette technology, the crossover operation uses univariate crossover, and the mutation operation uses basic bit mutation; the sixth step, Find the best individual in the contemporary population, keep it, and then go to the second step.
Owner:NORTHWESTERN POLYTECHNICAL UNIV
Formula input method and system for interactive formula typesetting software
InactiveCN101436308AImprove efficiencyReduce learning difficultyNatural language data processingSpecial data processing applicationsSelection operatorSoftware
The invention discloses a formula inputting method for interactive formula typesetting software and belongs to the field of printing and typesetting technology. In the interactive formula typesetting software, the efficiency of formula inputting is low. The method classifies and nominates an operator or a sign, establishes a mapping relation form between the name of the operator or sign and the operator or sign and inputs the name of the operator or sign in a character inputting region of a formula inputting method interface; according to the mapping relation, the operator or sign matched with the input name is displayed in a formula display region of the formula inputting method interface; and the operator or sign is selected and inserted into a type face. The method can rapidly input a formula and improve the efficiency of formula typesetting.
Owner:PEKING UNIV FOUNDER GRP CO LTD +1
Resource scheduling optimization method based on binary space partitioning tree
InactiveCN103886375AAvoid problemsChanging the properties of random searchGenetic modelsSpecial data processing applicationsBinary space partitioningNeighborhood search
The embodiment of the invention provides a resource scheduling optimization method based on a binary space partitioning tree. The binary space partitioning tree drives search, when overlapping individuals occur under the action of a selection operator, self-variation drive of a genetic algorithm that local search, neighborhood search and cross-domain search are carried out in a search space with directivity is achieved, and therefore the overlapping individuals are effectively prevented from occurring, population diversity is kept, and random search of the genetic algorithm is changed.
Owner:张黎明
Video server location selection method based on genetic ant colony hybrid algorithm
ActiveCN108573326ALow costSolve the problem of being stuck in a local optimumForecastingArtificial lifeLocal optimumSelection operator
The invention relates to a video server location selection method based on a multi-constraint priority genetic ant colony hybrid algorithm. The hybrid algorithm carries out multiple times of combination on an improved genetic algorithm and an ant colony optimization algorithm, the improved genetic algorithm is executed firstly, a group of problem near-optimum solutions generated by the improved genetic algorithm is converted to initial pheromone distribution of the ant colony algorithm; and then, a genetic ant colony hybrid algorithm based on a multi-constraint priority distribution strategy is executed. The shortcoming that the single-constraint priority distribution strategy in the traditional genetic algorithm can not find out the problem optimum solution is overcome, and the problems that the traditional genetic algorithm adopts a roulette wheel selection operator, the colony diversity is reduced, and falling into local optimum easily happens can be solved.
Owner:WUHAN UNIV OF TECH
Prediction method for shearing parameters of Martian soil based on GA-BP neural network
InactiveCN108460461AAccurate estimateImproved selection operatorNeural learning methodsMartian soilSelection operator
The invention discloses a prediction method for shearing parameters of Martian soil based on a GA-BP neural network, and the method comprises the steps: S1, determining a BP network weight and threshold, and using an improved genetic algorithm (GA) to optimize the BP neural network weight and thresholds: firstly coding the BP neural network weight and threshold, carrying out the selection, crossing and mutation operations of the weight and threshold according to a fitness function to obtain a new weight and a threshold until a training error reaches 0.001, otherwise continuing the optimizationto obtain the weight and threshold; S2, establishing a BP prediction model; S3, training the BP model to predict shearing parameters of Martian soil. The method improves a selection operator of the GA, maintains the diversity of populations while effectively selecting a better individual in the populations, thereby optimizing the weight and threshold of the BP neural network model and enabling the BP network to accurately estimate the shearing parameters of the Martian soil.
Owner:JILIN UNIV
Simulation resource dispatching method based on improved genetic algorithm
InactiveCN107329831AStrong global search capabilityFast convergenceResource allocationDigital output to print unitsSelection operatorSelf adaptive
Owner:BEIJING SIMULATION CENT
Multi-population genetic algorithm-based power distribution network fault section location algorithm
The invention discloses a multi-population genetic algorithm-based power distribution network fault section location algorithm. The algorithm includes the following steps that: 1) the fault current ofa power distribution network containing distributed power sources is coded with binary codes; 2) on the basis of satisfying the requirements of the multi-power source network, a distributed power source switching coefficient is introduced to represent power source switching, the application of the algorithm to a complex power distribution network is considered, a corresponding switching functionis established; 3) the construction of a fitness function is completed for the fault section location problem of the power distribution network according to a fault current code and the switching function of the power distribution network containing the distributed power sources; and 4) a multi-population genetic algorithm (MPGA) is implemented, so that population initialization, control parametersetting, immigration operator, manual selection operator and convergence condition determination are completed. With the algorithm of the invention adopted, the fault section of the power distribution network can be located accurately. The algorithm is suitable for a complex power distribution network containing distributed power sources, and has certain effectiveness and fault tolerance.
Owner:NANJING UNIV OF SCI & TECH
WAMS-based genetic algorithm-improved power grid reactive capacity optimization configuration method
InactiveCN104112237AAvoid crossing the limitImprove computing efficiencyData processing applicationsGenetic modelsTime informationWide area
The invention relates to a genetic algorithm-improved power grid reactive capacity optimization configuration method based on real-time information of a Wide Area Measurement System (WAMS) and an Energy Management System (EMS) of a power grid. The method includes: step S1. obtaining power grid measurement information from the power grid WAMS in real time; step S2. obtaining from the EMS the power grid structure, parameters and running section information in the EMS of a current time section, and forming an admittance matrix of a whole network containing all load node equivalent admittance; step S3. performing hybrid coding on a control variable of power grid reactive optimization; step S4. establishing a fitness function; step S5. executing a selection operator; step S6. executing a cross and mutation operator; and step S7. determining the rate of convergence and convergence termination criteria. The method in the invention makes improvements on the basis of a traditional genetic algorithm, makes improvements in multiple aspects to improve defects of the traditional genetic algorithm in reactive optimization, improves the rate of convergence and quality of a solution, and prevents the problem of occurrence of a local optimal solution.
Owner:STATE GRID CORP OF CHINA +1
Rough set attribute reduction method based on genetic algorithm
InactiveCN101763529AFast convergenceSimple codingGenetic modelsKnowledge based modelsGene PositionMutation operator
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.
Owner:SUN YAT SEN UNIV
Method for accurately identifying parameters of thermal process state-space model by adopting improved genetic optimization algorithm
ActiveCN106650934AGood estimateAvoid Random Search PhenomenaGenetic algorithmsModel parametersGlobal optimization
The invention discloses a method for accurately identifying parameters of a thermal process state-space model by adopting an improved genetic optimization algorithm. The method mainly comprises the steps of determining structure and identification parameters of the model, determining structural parameters of the optimization algorithm, solving a fitness value, encoding, transforming a decimal system into a binary system, performing optimal chromosome high-frequency mutation, implementing an optimal chromosome preservation mechanism, a selection operator, a crossover and mutation operators, decoding, transforming the binary system into a decimal system, and performing adaptive spatial mutation. According to the invention, the optimal chromosome preservation mechanism is introduced, so that random search of the algorithm in a later period can be avoided; the global optimization ability of the algorithm can be enhanced through optimal chromosome high-frequency mutation; and a certain range of real number spatial mutation is performed on a global optimal solution through adaptive spatial mutation, the range of spatial mutation increase along with increase in algebras trapping in local optimum until a local optimal solution jumps out, and the local optimization ability of the algorithm can be enhanced.
Owner:SOUTHEAST UNIV
A controlled source audio-frequency magnetotellurics one-dimensional inversion method using an improved genetic algorithm
InactiveCN106021859AImprove robustnessImprove performanceInformaticsSpecial data processing applicationsProbitInversion methods
The invention provides a controlled source audio-frequency magnetotellurics one-dimensional inversion method using an improved genetic algorithm. By applying the genetic algorithm to CSAMT one-dimensional data inversion, a target function based on the combination of frequency weighting and phase weighting is proposed, a selection operator based on the combination of fitness value ranking selection and the simulated annealing method is proposed, segmented crossover probability upper and lower limits are proposed, and a crossover operator based on the combination of the self-adaptive crossover probability based on fitness values and a mutation operator based on the combination of fitness and gene weighting are proposed; by using the probability-based optimal individual preservation strategy, the individual with the smallest fitness value is replaced by the individual with the largest fitness value with a certain probability. Compared with the conventional CSAMT data inversion method, the method prevents inversion failure caused by the emergence of ill-conditioned matrixes, can avoid the problems of prematurity and the condition of being liable to be caught in a local extremum in the standard genetic algorithm, and enables chromosomes to move in the optimal solution direction rapidly to find the optimal solution.
Owner:JILIN UNIV
Construction project multi-objective optimization method
InactiveCN111062119AResolve ambiguityImprove engineering applicabilityDesign optimisation/simulationMulti-objective optimisationMulti objective optimization algorithmAlgorithm
The invention provides a construction project multi-objective optimization method. The construction project multi-objective optimization method comprises the following steps: determining a mathematical model and genetic algorithm parameters of multi-objective optimization; establishing a population with feasible constraints and a population target function matrix; calculating an objective weight of the target function by adopting an entropy weight method according to the target function matrix, and synthesizing a hybrid dynamic weight of the target function; sorting the population by adoptinga method based on dynamic weight to obtain a Pareto temporary solution set; attaching virtual fitness values to individuals according to population individual sorting, and selecting a filial generation population by adopting a proportional selection operator and a roulette method; performing crossover operation on the filial generation population; performing mutation operation on the filial generation population after the crossover operation; combining the Pareto temporary solution set with the filial generation population after mutation operation to generate a new population; and if the algorithm termination condition is met, terminating the algorithm, otherwise, returning. According to the method, the problem of ambiguity between an original multi-objective optimization algorithm and engineering application is well solved, and the method has better engineering applicability.
Owner:SHENZHEN UNIV +2
Cross-region power system protection communication network planning method
ActiveCN108880886ASatisfy latency requirementsReduce riskData switching networksGenetic algorithmsFirst generationVariable length
The invention relates to a cross-region power system protection communication network planning method, comprising the steps of initializing a first generation of populations through adoption of a variable-length chromosome coding method; setting a fitness function, and evaluating fitness of chromosomes according to features of target populations; selecting parental chromosomes according to the fitness function, specifically, selecting the parental chromosomes through adoption of a selection operator, thereby enabling the parental chromosomes to be inherited by a next generation; carrying out cross processing on the parental chromosomes, and generating new chromosomes, thereby improving diversity of species; carrying out variation processing on the parental chromosomes after the cross processing, thereby improving searching capability of the populations; and combining the parental chromosomes and the newly generated chromosomes, as descendants of a current generation of populations, carrying out a next round of evolution until the preset generation number is realized, exiting a loop, and obtaining a final planning scheme, namely the chromosomes with the highest fitness in the last generation of populations. According to the method, a demand of line protection business for delay can be satisfied.
Owner:STATE GRID INFORMATION & TELECOMM BRANCH +3
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