Big data dressing recommendation based on ant colony algorithm to optimize BP network

Jihao Chang; Junzhao Zhang; Weiguo Li; Kenyuan Fan

doi:10.1117/12.2659700

22 November 2022 Big data dressing recommendation based on ant colony algorithm to optimize BP network

Jihao Chang, Junzhao Zhang, Weiguo Li, Kenyuan Fan

Proceedings Volume 12475, Second International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2022); 124751W (2022) https://doi.org/10.1117/12.2659700
Event: Second International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2022), 2022, Hulun Buir, China

Abstract

Aiming at the problem that there are many deficiencies in the existing dressing recommendation service, a big data dressing recommendation service system based on the optimization algorithm of BP neural network combined with the ant colony is designed. First, based on the weather data of the city where the recommended service object is located, the weather data set is constructed, and then, the dress recommendation model is constructed, based on the current weather data set, the dressing index is calculated, and finally, the push set is generated according to the dressing index recommendation table to recommend the dressing to the user. Based on the real data collected by the smart light pole, the local weather data set is constructed to achieve the recommendation results, and the recommendation results show that the recommendation algorithm improves the recommendation accuracy. Addresses issues such as inaccurate recommendation results.

Citation Download Citation

Jihao Chang, Junzhao Zhang, Weiguo Li, and Kenyuan Fan "Big data dressing recommendation based on ant colony algorithm to optimize BP network", Proc. SPIE 12475, Second International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2022), 124751W (22 November 2022); https://doi.org/10.1117/12.2659700

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