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5188 results about "Genetics algorithms" patented technology
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Genetic Algorithms. Genetic Algorithms(GAs) are adaptive heuristic search algorithms that belong to the larger part of evolutionary algorithms. Genetic algorithms are based on the ideas of natural selection and genetics.
Wind power forecasting method based on genetic algorithm optimization BP neural network
InactiveCN101706335AImprove forecast accuracyReduce computing timeGenetic modelsWork measurementAlgorithmPredictive methods
The invention discloses a wind power forecasting method based on a genetic algorithm optimization BP neural network, comprising the steps: acquiring forecasting reference data from a data processing module of a wind power forecasting system; establishing a forecasting model of the BP neural network to the reference data, adopting a plurality of population codes corresponding to different structures of the BP neural network, encoding the weight number and threshold of the neural network by every population to generate individuals with different lengths, evolving and optimizing every population by using selection, intersection and variation operations of the genetic algorithm, and finally judging convergence conditions and selecting optimal individual; then initiating the neural network, further training the network by using momentum BP algorithm with variable learning rate till up to convergence, forecasting wind power by using the network; and finally, repeatedly using a forecasted valve to carry out a plurality of times of forecasting in a circle of forecast for realizing multi-step forecasting with spacing time interval. In the invention, the forecasting precision is improved, the calculation time is decreased, and the stability is enhanced.
Owner:SOUTH CHINA UNIV OF TECH +1
Multi-Objective Radiation Therapy Optimization Method
InactiveUS20130197878A1Mapping structureLarge sampleMechanical/radiation/invasive therapiesComputation using non-denominational number representationGenetics algorithmsEngineering
A novel and powerful fluence and beam orientation optimization package for radiotherapy optimization, called PARETO (Pareto-Aware Radiotherapy Evolutionary Treatment Optimization), makes use of a multi-objective genetic algorithm capable of optimizing several objective functions simultaneously and mapping the structure of their trade-off surface efficiently and in detail. PARETO generates a database of Pareto non-dominated solutions and allows the graphical exploration of trade-offs between multiple planning objectives during IMRT treatment planning PARETO offers automated and truly multi-objective treatment plan optimization, which does not require any objective weights to be chosen, and therefore finds a large sample of optimized solutions defining a trade-off surface, which represents the range of compromises that are possible.
Owner:FIEGE JASON +5
Method for imaging multiphase flow using electrical capacitance tomography
InactiveUS20070133746A1Electric/magnetic detection for well-loggingMaterial analysis by electric/magnetic meansGenetics algorithmsEngineering
The invention relates to a novel image-reconstruction technique which is used to view multiphase flows using electrical capacitance tomography (ECT), which is based on non-linear heuristic global optimization methods involving simulated annealing and genetic algorithms. The inventive method consists in obtaining electrical capacitance data which are measured between electrodes positioned on the outer surface of pipeline, well or tank (electrically-insulating) containing fluids. The aforementioned data are dependent on the distribution of the fluids inside the pipeline, well or tank. Moreover, the data are processed in order to reconstruct an image of the spatial distribution of the relative electrical permittivity (also known as the dielectric constant) inside the tube, well or tank, which reflects the distribution of the different phases present in the flow.
Owner:INST MEXICANO DEL GASOLINEEO
Method and system for optimal scheduling on joint flood control for cascade reservoir groups
InactiveCN102817335AProtection securityImprove decision-making efficiencyClimate change adaptationForecastingTraffic volumeFlood control
The invention discloses a method and a system for optimal scheduling on joint flood control for cascade reservoir groups. The method includes the steps of firstly, determining flood type according to real-time reservoir level and the process of forecasting runoff in case of flood; secondly, deciding a primary protection object according to the flood type and downstream control-point flood control standards; thirdly, automatically selecting flood control optimization objectives and corresponding optimization scheduling models in a system model base; and fourthly, solving and optimizing the optimization scheduling model by modified genetic algorithm. The method and the system dynamically judge the level of flood and finish hierarchical scheduling based on the level of flood. In addition, projection of downstream protection objects, dam safety and flood recycling are achieved by selecting proper optimization scheduling objectives according to comprehensive information of the reservoirs, such as regulation performance, scheduling period and reliability in forecast flood during hierarchical scheduling, efficiency in decisions for the reservoir groups is improved, and mass data statistics show that the decision efficiency is improved by about 30% by the method and the system.
Owner:GUIZHOU WUJIANG HYDROPOWER DEV
Plan method for rapid coverage track search coordinated by multiple UAVs (Unmanned Aerial Vehicles)
ActiveCN106406346ASolving the Track Planning Problem of Cooperative Coverage SearchNarrow down your area searchPosition/course control in three dimensionsSimulationGenetics algorithms
The invention discloses a plan method for rapid coverage track search coordinated by multiple UAVs, and belongs to the field of UAV track planning. Key searching objects, namely points, lines and surfaces, are extracted from a gray area according to prior information of a battlefield environment and geometric characteristics of an object existing area; the access sequence of the key searching objects is determined via an integer-dual-coded genetic algorithm; according to the key searching objects and the distribution sequence of the UAVs, a local shortest connection track from the end point of a present object coverage search track to the start point of a next object coverage search track is obtained via a Dubins path and a greedy strategy, the coverage search track of the next search object is obtained, and the UAV coordinated coverage search track is obtained. The coordinated rapid coverage search track of multiple UAVs in the special gray area can be planned, the coverage time is short, the robustness of the algorithm is high, and a regional full-coverage search track can be replaced effectively.
Owner:BEIJING INSTITUTE OF TECHNOLOGYGY
Path planning method based on genetic algorithm
A path planning method based on the genetic algorithm includes the following steps: (1) establishing a path optimization mathematical model with a method, wherein the method specifically includes the steps of supposing that G is a path from the starting point 1 to the terminal point n, the path G does not include a repeated route or a round route, and the consumption of one route is the sum of weights on the route; (2) performing a path search process which specifically includes the following steps of starting from the starting point, searching for an optimized path within the range of the search radius with the genetic algorithm, moving along with a vehicle to the next node of a path obtained through the last search, taking the node as the starting point of the current search, searching out a path again on the basis of the node within the range of the search radius, and continuing to apply the method until the destination site is searched out. The path planning method based on the genetic algorithm is good in rapidity and stability and strong in applicability.
Owner:ENJOYOR COMPANY LIMITED
Brain glioma molecular marker nondestructive prediction method and prediction system based on radiomics
The invention belongs to the technical field of computer-aided diagnosis, and specifically relates to a brain glioma molecular marker nondestructive prediction method and a prediction system based on radiomics. The method comprises the following steps: adopting a three-dimensional magnetic resonance image automatic segmentation method based on a convolution neural network; registering a tumor obtained from segmentation to a standard brain atlas, and acquiring 116 position features of tumor distribution; getting 21 gray features, 15 shape features and 39 texture features through calculation; carrying out three-dimensional wavelet decomposition on the gray features and the texture features to get 480 wavelet features of eight sub-bands; acquiring 671 high-throughput features from the three-dimensional T2-Flair magnetic resonance image of each case; using a feature screening strategy combining p-value screening and a genetic algorithm to get 110 features highly associated with IDH1; and using a support vector machine and an AdaBoost classifier to get a classification of which the IDH1 prediction accuracy is 80%. As a novel method of radiomics, the method provides a nondestructive prediction scheme of important molecular markers for clinical diagnosis of gliomas.
Owner:FUDAN UNIV
Multi-objective optimization method for collaborative allocation of time slots of multi-runway approaching-departing flights
The invention relates to a multi-objective optimization method for collaborative allocation of time slots of multi-runway approaching-departing flights, belonging to the technical field of civil aviation. The multi-objective optimization method is mainly based on a collaborative decision-making idea and comprises the following steps of: firstly, dividing a time interval into a plurality of time slots, determining the approaching-departing capacity of an airport and dynamically creating time slots; secondly, establishing a multi-objective optimization model with minimum total delay cost, fair delay loss of each aviation company and balanced use frequency of each runway as objectives and with the effectiveness and the approaching-departing capacity of the airport as constraining conditions; and finally, solving by using a genetic algorithm to obtain an optimal flight time slot allocation scheme. The multi-objective optimization method disclosed by the invention is suitable for solving the time slot allocation problem of the approaching-departing flights of each airport.
Owner:NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
Systems, methods and apparatus for just-in time scheduling and planning
ActiveUS20110173042A1Optimizes supply planMaximize availabilityGenetic modelsDigital computer detailsProgram planningConstructive heuristic
The disclosure relates generally to methods and apparatus to optimize a supply plan through a hybrid meta-heuristic approach based on genetic algorithms to optimize inventory and generate a supply plan. The apparatuses include a supply chain planner that interacts with the processes of a supply chain network. To provide a complete optimization for the type of platform being deployed in theater a heuristic algorithm is devised to decompose the supply plan problem into a production center schedule and an asset routing problem, which will be tackled one after the other. The decomposed supply plan problem is solved with different heuristic algorithms. Namely, genetic algorithms are used to optimize the supply plans based on ever changing set of operational demands from in theater and the priority of those demands to the assigned depots, while efficient constructive heuristics are used to deal with footprint and timing constraints.
Owner:LOCKHEED MARTIN CORP
Propylene polymerization production process optimal soft survey instrument and method based on genetic algorithm optimization BP neural network
InactiveCN101315557AExcellent soft measurement resultsCalculation speedGenetic modelsBiological neural network modelsSurvey instrumentAlgorithm
A propylene polymerization production process optimal soft-measurement meter based on genetic algorithm optimized BP neural network comprises a propylene polymerization production process, a site intelligent meter, a control station, a DCS databank used for storing data, an optimal soft measurement model based on genetic algorithm optimized BP neural network, and a melting index soft-measurement value indicator. The site intelligent meter and the control station are connected with the propylene polymerization production process and the DCS databank; the optimal soft-measurement model is connected with the DCS databank and the soft-measurement value indicator. The optimal soft measurement model based on genetic algorithm optimized BP neural network comprises a data pre-processing module, an ICA dependent-component analysis module, a BP neural network modeling module and a genetic algorithm optimized BP neural network module. The invention also provides a soft measurement method adopting the soft measurement meter. The invention can realize on-line measurement and on-line automatic parameter optimization, with quick calculation, automatic model updating, strong anti-interference capability and high accuracy.
Owner:ZHEJIANG UNIV
Device-to-device relay communication-based resource allocation method
ActiveCN103796317AReduce the probability of allocation failureIncrease profitWireless communicationMix networkResource assignment
The invention relates to a device-to-device relay communication-based resource allocation method. In a single cell, an LTE-Advanced cellular network and a device-to-device (D2D) system constitute a hybrid network, and the duplex mode of the cellular network is a time division duplex mode, and the device-to-device (D2D) system utilizes the uplink resources of the cellular network in the cell in a multiplex mode. The device-to-device relay communication-based resource allocation method includes the steps of interaction with a base station, update of a resource record table, application and distribution of resources, and selection of relay nodes. According to the device-to-device relay communication-based resource allocation method of the invention, at first, system resources are allocated to active cellular subscribers according to polling standards under the premise that communication quality can be ensured, and then, most suitable resources are selected for device-to-device (D2D) subscribers in the cell through using a genetic algorithm according to maximum resource utilization rate standards. The objective of the invention is to minimize the probability of resource allocation failure and enable more device-to-device (D2D) subscribers can perform communication with normal communication of the cellular subscribers ensured.
Owner:江苏众成通信技术有限公司
Method for diagnosing crop water deficit through hyperspectral image technology
InactiveCN102495005AHigh precisionIncrease diversityColor/spectral properties measurementsVisual technologyMultidimensional data
Owner:JIANGSU UNIV
Dynamic goods allocation planning method and system for processing multi-variety goods and material storage
ActiveCN103473616AOptimize the handling pathRealize multiplexingGenetic modelsForecastingMultiplexingGenetic algorithm
The invention discloses a dynamic goods allocation planning method and system for processing multi-variety goods and material storage, and belongs to a planning method of intelligent loading. The method comprises the steps that S1. goods allocation information, goods classification and goods information in a storage environment are stored into a system database through a data management module; S2. unprocessed warehouse-in warrants and warehouse-out warrants are guided into the system database through a service section management module, then stored goods involved in the warehouse-in warrants are extracted according to time sequence, warehouse-in goods list information and the like are generated; the executing scheme of storage is subjected to optimizing calculation by introducing a genetic algorithm, goods allocation is dynamically planned in a subsection-service-section mode, multiplexing of storage space is achieved, the probability that the storage space is not occupied and is wasted in a large quantity of time is lowered, the requirement for ceaseless storing and taking at any time of goods is met, and the new requirement for storage management under enterprise large-scale customization service is especially met.
Owner:SICHUAN AEROSPACE SYST ENG INST
Online test method for characteristic parameter of bearing-rotor system
ActiveCN103076163AOnline test operation method is simple and reliableStrong practical valueMachine bearings testingSlider bearingOnline test
The invention discloses an online test method for a characteristic parameter of a bearing-rotor system. The online test method comprises the steps of: installing a signal acquisition system on the bearing-rotor system supported by a sliding bearing; regulating the rotation speed of a main shaft, and starting a drive motor and a signal acquisition instrument; acquiring vibration signals of specific positions in real time by an eddy current displacement sensor, and storing the vibration signals by the signal acquisition system; establishing a bearing-rotor system model by adopting a finite element method; and applying a characteristic parameter optimization method of the bearing-rotor system based on combination of machinery dynamics modeling with a genetic algorithm to ensure that a theoretical vibration state obtained through the simulation model is close to an actual measurement value, thereby realizing online solving of the rigidity and damping coefficient of the sliding bearing, the off set of a rotor and the like of the bearing-rotor system. Compared with the traditional method, the online test method disclosed by the invention has the obvious advantages that external excitation or multiple machine start / stop does not need to be performed on the bearing-rotor system, and the online test method is simple and reliable and has the characteristics of high efficiency, high stability and high precision.
Owner:XI AN JIAOTONG UNIV
A fault diagnosis method of high voltage circuit breaker based on depth belief network
ActiveCN109086817AImprove utilization efficiencyImprove the accuracy of judgmentCharacter and pattern recognitionNeural architecturesDeep belief networkAlgorithm
The invention discloses a fault diagnosis method of a high-voltage circuit breaker based on a depth belief network, which comprises the following steps: step 1, selecting a data sample required by anexperiment, and dividing the unified standardized sample data into a test sample and a training sample according to a specific proportion; Step 2: building and initializing the DBN deep belief networkfault diagnosis model; Step 3, inputting a large number of unlabeled samples or unlabeled samples in the pre-training set from the bottom of the model, and pre-training the RBM in the model by usinglayer-by-layer unsupervised greedy learning; Step 4: the whole model being fine-tuned by genetic algorithm; Step 5, the fault diagnosis model of the high-voltage circuit breaker obtained by training being classified to the fault samples of the test set in step 1, so as to obtain the fault classification result, and the diagnosis accuracy rate of the model being counted. The invention discloses a fault diagnosis method of a high-voltage circuit breaker based on a depth belief network, which can train a large amount of data samples to realize the fault diagnosis function of the high-voltage circuit breaker.
Owner:XI'AN POLYTECHNIC UNIVERSITY
Performance of artificial neural network models in the presence of instrumental noise and measurement errors
InactiveUS7313550B2Improve accuracyImprove performanceGenetic modelsDigital computer detailsObservational errorData set
A method is described for improving the prediction accuracy and generalization performance of artificial neural network models in presence of input-output example data containing instrumental noise and / or measurement errors, the presence of noise and / or errors in the input-output example data used for training the network models create difficulties in learning accurately the nonlinear relationships existing between the inputs and the outputs, to effectively learn the noisy relationships, the methodology envisages creation of a large-sized noise-superimposed sample input-output dataset using computer simulations, here, a specific amount of Gaussian noise is added to each input / output variable in the example set and the enlarged sample data set created thereby is used as the training set for constructing the artificial neural network model, the amount of noise to be added is specific to an input / output variable and its optimal value is determined using a stochastic search and optimization technique, namely, genetic algorithms, the network trained on the noise-superimposed enlarged training set shows significant improvements in its prediction accuracy and generalization performance, the invented methodology is illustrated by its successful application to the example data comprising instrumental errors and / or measurement noise from an industrial polymerization reactor and a continuous stirred tank reactor (CSTR).
Owner:COUNCIL OF SCI & IND RES
Genotic algorithm optimization method and network
InactiveUS6957200B2Digital computer detailsElectric digital data processingPopulationFitness function
Sensors are selected from a sensor network for tracking of at least one target. The sensors are selected using a genetic algorithm construct having n chromosomes, wherein each chromosome represents one sensor, defining a fitness function based on desired attributes of the tracking, selecting one or more of the individuals for inclusion in an initial population, executing a genetic algorithm on the initial population until defined convergence criteria are met, wherein execution of the genetic algorithm has the steps of choosing the fittest individual from the population, choosing random individuals from the population and creating offspring from the fittest and randomly chosen individuals. In one embodiment, only i chromosomes are mutated during any one mutation, wherein i has a value of from 2 to n−1.
Owner:HONEYWELL INT INC
Multiple-target operation optimizing and coordinating control method and device of garbage power generator
The invention provides a multiple-target operation optimizing and coordinating control method and a device of a garbage power generator. The multiple-target operation optimizing and coordinating control method includes the following steps. Operational parameters are downloaded from a data communication system (DCS), data judged as reasonable based on a threshold value are transmitted to a database. In terms of environmental protection, economy and safety of the power generator, three models are respectively set up by means of a support vector machine and a fuzzy neural network. A modified strength PARETO genetic algorithm is used for comprehensively optimizing multiple targets and then optimum operation parameters under the present working condition are worked out. Operational staff can adjust operation of corresponding parts based on the optimum operation parameters. The device comprises a data collecting module, a data filtering module, a database module, a data modeling module, an optimizing module, a forecasting module, a remote monitoring module, a monitor, an alarming module and a manual alarming module. The multiple-target operation optimizing and coordinating control method and the device of the garbage power generator achieve multiple functions of real-time forecasting, offline simulation, dynamic optimizing and the like and have the advantages of being strong in adaptability, good in self-learning ability, high in fitting precision, obvious in optimizing effect and the like.
Owner:SOUTH CHINA UNIV OF TECH
Task scheduling method of multilayer shuttle vehicle automatic warehousing system
The invention discloses a task scheduling method applied to a multilayer shuttle vehicle automatic warehousing system. The task scheduling method comprises the steps of firstly establishing an operation time model of the system according to the operation execution process of a device; then changing the scheduling problems of a multilayer shuttle vehicle and an elevator into a production line parallel operation problem, establishing a task scheduling mathematic model for a task queue in a time window designated in size; for solving the multi-task multi-target optimization problem, designing a non-dominated sorting genetic algorithm with an elitist strategy based on a pareto optimality so as to perform model solution. By applying the task scheduling method, the waiting time of the shuttle vehicle and the idle time of the elevator can be effectively shortened, and accordingly the device utilization rate and handling capacity of a distribution center are improved.
Owner:SHANDONG UNIV
Intelligent stored cargo space distribution and optimization method
InactiveCN103942617AImprove operational efficiencyReduce inventory and other operationsForecastingLogisticsMathematical modelStack machine
The invention discloses an intelligent stored cargo space distribution and optimization method. The method comprises the following steps that 1, the frequency of cargo to leave from storage or be put into storage and the running speed of a stacking machine are counted, and a mathematic model is built; 2, two solutions are provided for different scales and include the Hungarian method and the genetic algorithm. By the intelligent stored cargo space distribution and optimization method, the utilization rate of cargo space is improved, the efficiency of cargo to leave from storage or be put into storage and the utilization rate of the stacking machine and other equipment are also improved, and the box shift operation and other operations can be reduced.
Owner:JIANGSU R & D CENTER FOR INTERNET OF THINGS
Iron-making and steel-making continuous casting integrated dispatching system
InactiveCN101908092ASolve the integrated scheduling problem of ironmaking-steelmaking-continuous castingFast Online SchedulingSpecial data processing applicationsData acquisitionSteelmaking continuous casting
The invention discloses an iron-making and steel-making continuous casting integrated dispatching system, and belongs to the planning and dispatching field of iron-making and steel-making continuous casting production. The dispatching system comprises system implementing conditions and four sub-modules, wherein the system implementing conditions comprise equipment state and data acquisition programs, a database server, a database management program, database software and a client application program; and the four sub-modules comprise a torpedo ladle and foundry ladle dispatching planning and blast furnace area-converter area molten iron planning matching model module, an iron-steel interface molten iron dispatching framework module, a molten iron pretreatment-continuous casting dispatching module and an information communication module. Iron-steel interface torpedo ladle dispatching is implemented by monitoring the equipment state, judging the abnormal condition of the production, recording the operation performance, combining the setting parameters of dispatching personnel and establishing a blast furnace area-converter area molten iron planning matching model; static dispatching of a molten iron pretreatment-continuous casting section is generated by adopting a heuristic algorithm, and dynamic dispatching is implemented by using a hybrid genetic algorithm; and quick and flexible on-line dispatching of the molten iron pretreatment-continuous casting section is implemented.
Owner:QINHUANGDAO SHOUQIN METAL MATERIAL +2
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
Waveform shapes for treating neurological disorders optimized for energy efficiency
ActiveUS20120136408A1Extend battery lifeImprove energy efficiencyHead electrodesImplantable neurostimulatorsDiseaseNervous system
Systems and methods for stimulation of neurological tissue apply a stimulation waveform that is derived by a developed genetic algorithm (GA), which may be coupled to a computational model of extracellular stimulation of a mammalian myelinated axon. The waveform is optimized for energy efficiency.
Owner:NDI MEDICAL
Location method for single-phase earth fault of power distribution network based on genetic algorithm and location device
ActiveCN102981099AThe amplitude and phase characteristics are obviousGuaranteed accuracyGenetic modelsFault locationPhase currentsEngineering
The invention relates to a section location method and a location device for a single-phase earth fault of a power distribution network. The location method comprises the steps that terminals mounted at different positions of a line captures zero-sequence current transient signals at two cycles before and after zero-sequence current exceeds a start value, conduct wavelet transformation and reconstruction on the zero-sequence current transient signals, and are encoded according to reconstructed detail components, and a section where a fault point is located is searched by a genetic algorithm. The location device consists of the terminals and a master station, wherein the terminals are mounted on overhead line towers or in cable ring main units; input ends of the terminals receive zero-sequence current signals synthesized by phase current signals of CT (Current Transformer) secondary sides of distribution lines (comprising overhead lines and cables); the terminals are connected with the master station through optical fiber communication or mobile communication; and the master station is mounted in a transformer substation or a dispatch center, comprises an optical fiber communication module and a mobile communication module and receives signals sent by the terminals. The location method and the location device are mature in technology and high in reliability.
Owner:SHENYANG POWER SUPPLY LIAONING POWER +2
Evolutionary controlling system
An evolutionary control for a subject such as an engine installed in a vehicle is conducted by the steps of: selecting coefficients, as genes, affecting the control characteristics of the control system; creating plural control units as chromosomes, each being constituted by plural genes; expressing the genes of each chromosome as control characteristics by controlling the subject using the control system having the control characteristics; selecting at least one chromosome from the created chromosomes based on the control characteristics expressed by the genes in view of the user's preference; and causing the at least one chromosome to evolve using a genetic algorithm, thereby obtaining control characteristics suitable to the user. In this method, the characteristics of the product can effectively be adjusted after its purchase based on the user's preference.
Owner:YAMAHA MOTOR CO LTD
Solution method for independent and joint dispatching of distribution network with micro-grids
InactiveCN108734350AFully consider the characteristics of electricity consumptionIn line with the concept of electricity consumptionForecastingArtificial lifePower gridWind field
The invention discloses a solution method for independent and joint dispatching of a distribution network with micro-grids. The method comprises the following steps: establishing a model of the distribution network with the micro-grids; establishing an objective function for dispatching of the micro-grids and an objective function for dispatching of the distribution network; determining constraints for independent and joint dispatching of the micro-grids and the distribution network; and solving household microgrids and distribution network by a particle swarm optimization algorithm, and solving thermoelectric microgrids with a Benders decomposition method. In the household microgrids, the demand response is considered, and a load curve is optimized by a genetic algorithm. Aiming at the prediction error of wind power, a wind field model with three-parameter Weibull distribution is established. The method can be applied in the technical field of economic dispatching of a plurality of microgrids, and a plurality of stakeholders are satisfied on the premise of satisfying system constraints. The Benders decomposition method is used to solve a thermoelectric system, thereby effectivelyprotecting the privacy of the information of electric and thermal systems, and improving the accuracy of the calculation.
Owner:YANSHAN UNIV
Near infrared spectrum analyzing method based on isolated component analysis and genetic neural network
InactiveCN101520412AImprove forecast accuracyRich Chemometric MethodsBiological neural network modelsColor/spectral properties measurementsInfraredMetrology
The invention discloses a near infrared spectrum analyzing method based on the isolated component analysis and genetic neural network, which comprises the following steps for the acquired near infrared spectrum: firstly, effectively compressing spectrum data by using wavelet transform; secondly, extracting an independent component and a corresponding mixed coefficient matrix of a near infrared spectrum data matrix by using an isolated component analysis method; thirdly, building a three-layer BP neutral network, using the mixed coefficient matrix of a training sample as the input and correspondingly measured component concentration matrix as the output, and optimizing a neutral network structure by adopting a genetic algorithm, and obtaining a GA-BP neutral network by the training of the training sample; fourthly, predicting and analyzing the measured component concentration of the predicted set sample by using the GA-BA neutral network. The method enriches the chemical measurement method, widens the application range of the isolated component analysis and has favorable application prospect.
Owner:CHINA JILIANG UNIV
Rolling bearing fault prediction method based on continuous deep belief network
InactiveCN105973594AStrong reliabilityHigh precisionMachine bearings testingCharacter and pattern recognitionTime domainRestricted Boltzmann machine
The invention proposes a rolling bearing fault prediction method based on a continuous deep belief network. The method comprises the following steps: first, extracting the time-domain characteristic quantity of vibration signals of a rolling bearing; then, fusing the extracted time-domain characteristic information using a locally linear embedding method, so as to define a new comprehensive monitoring index for better quantitative evaluation of performance degradation of the bearing; training a continuous restricted Boltzmann machine step by step to construct a continuous deep belief network prediction model; and using a genetic algorithm to optimize the structure of the continuous deep belief network so as to further improve the prediction precision. The prediction method is reliable in result, has good real-time performance, is simple and feasible, and is suitable for rolling bearing fault prediction.
Owner:NORTHWESTERN POLYTECHNICAL UNIV
Intelligent layout method used for rectangular part
InactiveCN103500255AMeet the process requirementsEfficient searchSpecial data processing applicationsRelevant informationAlgorithm
The invention discloses an intelligent layout method used for a rectangular part. The method comprises the steps that S1 relative parameters of the genetic algorithm are initialized; S2 relative information of the rectangular part is extracted from a rectangular part bank to be laid out; S3 relative information of raw material boards is extracted from a board tank; S4 the obtained information is coded, and primary species are generated randomly; S5 one-by-one decoding is conducted on the primary species by means of the lowest horizontal line search algorithm to obtain solution using efficiency; S6 selection, crossover and mutation operation is conducted according to the genetic algorithm until iteration is finished, and the optimal layout scheme is output. According to the intelligent layout method, the process requirement of the rectangular part can be met well, the intelligent algorithm and the heuristic algorithm are combined, one optimizing scheme can be found rapidly and efficiently, and therefore the material using rate of an enterprise is greatly improved, layout time can be obviously shortened, and layout efficiency is improved.
Owner:NANTONG UNIVERSITY
Central air conditioner fine control method
ActiveCN104613602AReduce power consumptionRealize fine controlMechanical apparatusSpace heating and ventilation safety systemsGenetics algorithmsGlobal optimization
The invention discloses a central air conditioner fine control method. The method includes the steps of establishing energy consumption models of all sub-systems of an air conditioner, determining parameters to be recognized in the models of all the sub-systems, determining constraint conditions, establishing a target function of a global optimization control model, and conducting optimizing through a genetic algorithm. Modeling is conducted for energy consumption of a central air conditioning system, and the power consumed when the central air conditioning system runs in a working state of the capacity smaller than the rated capacity is reduced through the genetic algorithm; through the cooperation of various control strategies, the all-directional air conditioner fine control is achieved, the energy conservation scheme is more comprehensive and exquisite, and the energy conservation effect is more remarkable.
Owner:HOHAI UNIV
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