5100 results about "Genetics algorithms" patented technology

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.

The invention relates to a method for diagnosing the crop water deficit through a hyperspectral image technology, and especially relates to a method for diagnosing the Lycopersicon esculentum Mill. leaf area water based on hyperspectral images. The method comprises the following steps: 1, acquiring Lycopersicon esculentum Mill. leaf hyperspectral image data through a self-constructed hyperspectral imaging system; 2, selecting a characteristic wavelength by optimizing through an adaptive band selection process to realize multidimensional datum dimensionality reduction; 3, dividing the image ofeach sample at the characteristic wave, counter-rotating, carrying out form operation to obtain a target image, and extracting the leaf gray level and the leaf texture characteristic from the target image; and 4, selecting an optimal characteristic subclass through a GA-PLS (genetic algorithm-partial least square) process by fusing the gray scale and the texture characteristic and aiming at ten characteristic variables, and establishing a partial least square regression model based on the optimal characteristic, wherein the correlation coefficient R between a predicted value and a measured value of the model is 0.902. Compared with routine detection methods, the method of the invention has the advantages of rapid detection speed, and simple and convenient operation; and compared with a single near infrared spectroscopy or computer vision technical means, the method of the invention allows obtained information to be comprehensive, and the accuracy and the stability of the detection result to be improved.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

The invention relates to a task observation plan solution method and system based on a genetic algorithm for multiple agile satellites. The method and system can support task planning of the agile satellites, and a target function and a constraint analysis model are constructed according to the features of the agile satellites; by figuring out a solution to the constructed constraint analysis model satisfying task planning, selection, overlapping and variation of genetic searching algorithms are conducted to achieve conflict between every two adjacent tasks, an observation planning scheme is optimized, an optimal observation plan satisfying constraint conditions is generated, the resource utilization rate of the satellites is improved, and a timeliness problem during task execution of theagile satellites is solved. For different task conditions, different disposal methods are selected to achieve reasonable distribution of satellite resources, the quantity of single-track observation tasks is increased, and the response timeliness is improved.

The invention discloses a global optimization, search and machine learning method based on the Lamarckian principle of inheritance of acquired characteristics, comprising step 1: constructing an objective function ƒ(P) according to the problem being solved, where P represents a set of candidate solutions to the problem; step 2: encoding P into a genetic algorithm (GA) chromosome, inputting or automatically calculating algorithmic parameters of the GA, and initializing the algorithm and the population of candidate solution generation G₀={P₀¹, P₀², . . . , P₀^S}, where S is the size of the population G and 0 stands for the initial generation; step 3: at generation k, optimizing the prevailing population of the candidate solutions G_k={P_k¹, P_k², . . . , P_k^S} iteratively using a Lamarckian “Heredity Operator” and a “Use-and-Disuse Operator” based on the values of ƒ(G_k); and step 4: outputting the final set of optimal solutions to the problem.

The invention discloses a vibration fault diagnosis method of a wind generating set. A vibration sensor collects a vibration fault signal of the wind generating set; a variation modal method is used to extract fault characteristic information, and further extracts a fault characteristic vector via normalization; and the fault characteristic vector is input to a model of a genetic algorithm optimized support vector machine, and fault identification and diagnosis are realized. The method is suitable for fault diagnosis and identification of the wind generating set, the diagnosis precision is higher, timely and reliable maintenance suggests can be provided for maintenance staff of the set, and unnecessary economic loss is reduced.