Upper limb posture recognition algorithm based on genetic algorithm coding

A genetic algorithm and algorithm technology, applied in the direction of genetic law, genetic model, advanced technology, etc., can solve the problems of slow convergence speed, easy to fall into local minimum points, etc., to improve the accuracy, save the diversity, and improve the speed of parameter optimization. Effect

Active Publication Date: 2019-01-11
BEIJING UNIV OF TECH
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Problems solved by technology

[0007] Aiming at the problem of slow convergence speed and easy to fall into local minimum point in the optimization process of genetic algorithm, a new population selection mechanism is proposed

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  • Upper limb posture recognition algorithm based on genetic algorithm coding
  • Upper limb posture recognition algorithm based on genetic algorithm coding
  • Upper limb posture recognition algorithm based on genetic algorithm coding

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Embodiment Construction

[0069] 12 populations are used in the project. If generalization is performed, the idea is to classify all populations, including four categories, namely the best (Top), good (best), general (normal) and For the poor population (worse), select all the good populations and select the best, normal and worse populations in proportion. After the selection, the insufficient part is randomly generated, and the number of populations in each round remains unchanged.

[0070] The overlapping range can be 0, the time window cannot be 0, the number of neurons cannot be 0, and the length of the experimental data is 89. Therefore, the overlapping range can be 0-88, and the time window range is 1-89, that is, take one at a time Data, two data, up to 89 data (that is, all data) can be obtained at one time, the minimum number of neurons in the hidden layer is 6, that is, 6 categories, there is no upper limit, but based on practical considerations, too many neurons The number will not bring mo...

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Abstract

The invention relates to an upper limb posture recognition algorithm based on a genetic algorithm for super-parameter optimization. At that move end, the upper limb posture movement is collected, andthrough the analysis of the collected data, six kinds of motion information are identified. The upper limb posture data are time series, time window length, data overlap rate and the number of hiddenneurons, which will affect the accuracy of recognition. Therefore, a genetic algorithm is used to optimize the super-parameters and find the most appropriate set of solutions. The traditional geneticalgorithm is slow and easy to fall into the local solution, the invention sorts the population according to the fitness function, the sorted populations are divided into four parts, namely, Top, Best,Normal and Worse. All the good populations are selected and the best, Normal and Worse populations are selected proportionally. After selection, the inadequate populations are randomly generated to ensure that the number of population remains unchanged in each round. The invention accelerates the speed of parameter optimization, and simultaneously finds the global optimal solution.

Description

technical field [0001] The present invention proposes an algorithm for optimizing hyperparameters of collected upper limb motion posture data based on a genetic algorithm, and at the same time develops an information collection system for collecting upper limb motion posture based on a portable mobile terminal. The mobile terminal information collection includes Setting of attitude sensor parameters, real-time display of data, rotation of 3D model, saving of data and real-time recognition of attitude. Simultaneously optimize the three hyperparameters through the genetic algorithm. The optimized parameters are the length of the time series time window, the repetition rate of each data acquisition and the number of hidden layer neurons. At the same time, a new population selection is proposed. mechanism. This patent involves mobile terminal development and genetic algorithm optimization. Background technique [0002] At present, there are mainly three ways for gesture recogn...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/12
CPCG06N3/126Y02D30/70
Inventor 张俊杰孙光民张子昊付晓辉姜明
Owner BEIJING UNIV OF TECH
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