Abstract
Along with the rapid development of the new internet media, people’s lives are becoming increasingly digital, information is diversified, and communication methods have undergone significant changes. “Emoticon pack,” as a kind of visual symbol that was generated and developed in the context of the internet, can use nonverbal symbols such as words, images, symbols, and other nonverbal symbols to simulate expressions, posture, and movements and a new expression and cultural phenomenon. In this study, the principle of neural network optimization is analyzed by applying the particle swarm algorithm, incorporating the harmonic search algorithm to neural network optimization, and the principle of neural network optimization is analyzed. This study is aimed at college students, investigating the consumption status of emoticon packs and the consumption amount of emoticon packs for men and women; among them, people who only use free emoji packs and those who only use emoji packs under 10 yuan account for the highest proportion, accounting for 73.07% and 22.41% of the surveyed people. Among the people who buy emoticons, boys are more likely to have large consumption behaviors than girls. In the consumption segment below ten yuan and above 150 yuan, the ratio of men to women is the same; in the consumption range of 11–50 yuan, the number of girls exceeds than that of boys, accounting for 70% of the number; however, in the consumption range of 51 yuan to 150 yuan, the proportion of boys surpassed than that of girls and the number of consumers accounted for more than 60%.
Highlights
Along with the rapid development of the new internet media, people’s lives are becoming increasingly digital, information is diversified, and communication methods have undergone significant changes
Since the accuracy of the performance of the artificial neuron network (ANN) prediction depends on the appropriate set of parameters for the inputs, the concentration is placed on the choice and readiness of the underlying data that have a significant effect on the electricity price. is is achieved by using various clustering algorithms and comparing the configuration results of the selected model with different input argument parameters
The KNN model, which is used for in-sample and out-of-sample analysis, has been developed. e results show that the integrated approach results in very favorable electricity price estimates, with lower or lower estimation error than other electricity price estimation tools recognized in the document [3]
Summary
Artificial neural network theory is a theory in which intelligent computers use the mental functions and technology of the human brain to track information about human neurons. It is currently one of the most active research fields in the world. E constructed neural network is a theoretical mathematical model of the human brain and its functions It is composed of several interconnected process units. It is a nonlinear adaptor system, and the resulting neural network is similar to the biological nervous system and performs basic brain functions. Suppose the actual calculation result of the network is Oj, and the expected result of the sample is Tj, as long as the error between Oj and Tj is minimized and the network output is close to the expected output, the network can obtain better predictive ability and generalization ability [10]. e input and output are expressed in matrix form, and the formula can be written as follows: In ωλ Z
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