30 results about "Genetic programming algorithm" patented technology

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

The invention provides an incremental data mining method based on a genetic programming algorithm. Incremental data mining can complete the incremental model learning task of increasing data samples from few to many, input data into the model, and the input layer performs linear mapping on the data, and the The result is transmitted to the middle layer; the middle layer performs nonlinear transformation and spatial enhancement mapping respectively, and outputs the result to the voting system; the voting system determines the category; the feedback system optimizes the network parameters. Multiple iterations complete the learning process. When processing incremental data, the coupling degree of old and new data samples is low, and old data samples are no longer considered when mining new data, which has a good inheritance.

The invention discloses an urban rail train network topology optimization method belonging to the technical field of rail transit communication networks. The present invention realizes the optimal design process that simultaneously satisfies the reliability and real-time performance of the communication network under the economic constraints by means of the idea of ​​double-layer planning; the double-layer planning regards the planning of the physical topology of the train network as a discrete network planning , while the logical topology planning is regarded as a shortest time delay planning, and the two-level planning model is solved by using the genetic algorithm; the optimization method of the present invention can effectively find the balance point of cost, reliability and time. The present invention provides a solution result based on genetic genetic algorithm for a given example, indicating that the present invention can be applied to practical engineering problems, and the application of the present invention to the construction of rail transit train network can make the train network operate more economically and efficiently, effectively saving Construction costs, reducing unnecessary waste and redundancy.

The invention discloses an urban open channel drainage system control method based on a self-correcting genetic algorithm. According to the method, firstly, modeling is conducted according to an urban open channel system, rainfall prediction amount in the next 24 hours of a city is introduced as system disturbance, and then control over an open channel water pump in the next 24 hours is optimized by means of a genetic programming algorithm to achieve the aims of tracking the target water level and reducing energy consumption. Specially, a state feedback and rolling optimization algorithm is introduced to overcome the defects that a traditional genetic algorithm is large in algorithm model error, poor in disturbance resistance and the like, and robustness and instantaneity of a control system are improved. The method has important scientific meaning and application value in building of an urban open channel system.

The invention provides a genetic programming classification method based on geometric semantics. A training process and a prediction process are separated, so as to complete classification of tested samples; the training process comprises the steps of: solving an optimal individual through the geometric semantics, extracting a classifier formula of the optimal individual, and storing the classifier formula of the optimal individual in a magnetic disk; the prediction process comprises the steps of: invoking the classifier formula, which is stored in the magnetic disk, of the optimal individual, recovering the classifier formula through loading and calculation, and outputting classification results according to the classifier formula, so as to classify a plurality of individuals. The problems of too early convergence, low classification accuracy and the like of an existing genetic programming algorithm are solved, the classification accuracy is high, and the individual formula can be stored.

The invention belongs to the technical field of image processing, and specifically discloses a graphic image recognition and matching method based on a genetic programming algorithm of a new coding method, the purpose of which is to obtain more suitable features in image matching through the new algorithm to improve image recognition and matching retrieval Accuracy. The steps include: (1) parameter setting, population initialization and selection of matching methods; (2) calculation of population fitness and genetic operations including crossover, mutation, self-crossover, and self-exchange operations; (3) optimizing individuals after genetic operations, Carry out local search; (4) further optimize the population, and judge whether the evolution is terminated; (5) decode the individual tree, get the way of extracting new features, and obtain new image features; (6) for new image features, according to the set Matching method, the output image matching model. The training model generated by the invention can effectively improve the accuracy of image recognition and matching.

The invention discloses a DFB laser frequency stabilization method based on current control, and the method comprises the steps: carrying out the wavelength-current modeling through employing the current tuning characteristics of a DFB laser and a genetic programming algorithm, so as to set the constant frequency DC work environment of the DFB laser; obtaining a saturated absorption spectrum signal based on the saturated absorption principle; obtaining an odd harmonic differential error signal containing frequency information through employing a phase sensitive detection principle, and carrying out the PID control parameter optimization of the error signal through employing the genetic algorithm. The method achieves the quick and accurate adaptive frequency locking control, gives consideration to the high precision of saturated absorption frequency stabilization, and can guarantee the long-time high precision and stability of the frequency of the laser.