To reduce the interference of subjective factors and meet the diverse perceptual needs of users, an intelligent cockpit perceptual image design method based on BP neural network optimization genetic algorithm is proposed. The user’s perceptual image is obtained and divided into intensities, the factor analysis method is used to reduce the dimensionality to obtain the target image, the new energy vehicle cockpit sample is obtained. The cluster analysis method is used to screen out the advantageous samples, and the intelligent cockpit central control is extracted using the morphological analysis method. Styling characteristic factors provide new ideas and references for the diversification of smart cockpit styling design. As automobile production technology continues to advance, the interaction methods, functions, and structures of automobile cockpits have also undergone a series of changes, bringing great convenience to people. In particular, the smart cockpit is an important element that cannot be ignored in the field of automobile design and can be used as a major innovation point to attract consumers.


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    Title :

    Intention prediction model of automobile intelligent cockpit based on optimized genetic algorithm


    Contributors:
    Fang, Lin (author) / Han, Ruilong (author) / Qin, Chuanqi (author) / Liu, Shuai (author)


    Publication date :

    2023-12-08


    Size :

    519635 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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