Innovative design of digital neural network-based biodata integration technology in cultural tourism management: Insights from cellular molecular biomechanics perspective
Abstract
Based on the related feature selection algorithm, this paper builds the basic framework of the multi-strategy method of Fastest Virtual Reality (FVR) feature selection algorithm, and obtains the final collection of biometric data after feature dimensionality reduction and removal of redundant feature values. In the context of cellular molecular biomechanics, the retina sampling network’s extraction of pupil biometric features is related to the autonomic nervous system’s influence on the iris muscles. The autonomic nervous system, through neurotransmitters and intracellular signaling pathways, regulates the contraction and dilation of the iris, which is reflected in the dynamic change of the pupil diameter. The retina sampling network is established to extract the pupil biometric features in it, and Gabor filtering is applied to extract the image feature data of a small area around a specific point in the image, to obtain the dynamic change data of the visitor’s pupil diameter, and combine with the K* algorithm to evaluate the emotional state of the data segment. Emotional states can affect hormone secretion, such as cortisol and adrenaline, which in turn impact cellular metabolism and neural activity. Use the Radial Basis Function (RBF) network structure model for face biometric data fusion, and according to this method to realize the statistics of attraction foot traffic. The model is applied to the visitor management of a scenic spot, and the emotional state of visitors on holidays is generally higher, among which the highest is 4.2145 on Qingming Festival, and the average pupil diameter of the visitors on that day is also the largest, reaching 3.9615mm.The peak average of the visitor flow of the scenic spot in the morning of the test day is about 44,076 person-times, and the peak average in the afternoon is about 16,254 person-times, among which the average of the flow of the visitors on 2 May is the was the highest, reaching 38,698 person-times. Understanding the cellular molecular biomechanics behind these biometric data helps design more effective strategies to enhance tourists’ travel experience.
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