International Journal of Social Science & Economic Research
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Title:
FAILURE ANALYSIS OF "PHOTOGRAPHING AND MAKING MONEY" TASK BASED ON B-P NEURAL NETWORK

Authors:
Zeng Yunhui, Guo Hongfei, Zhang Yuanbiao, Huang Guoquan, Huang Shusheng, Chen Yilin, Shen Shiyue, Chen Zhengguo

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1*Zeng Yunhui, 2Guo Hongfei, 3Zhang Yuanbiao, 4Huang Guoquan, 1Huang Shusheng, 1Chen Yilin, 1Shen Shiyue, 1Chen Zhengguo
1. Bachelor Research Scholar?College of Intelligent Science and Engineering, Jinan University, No. 206, Qianshan Road, Xiangzhou District, Zhuhai City, Guangdong Province
2. Associate Professor?College of Internet of Things and Logistics Engineering, Jinan University, No. 206, Qianshan Road, Xiangzhou District, Zhuhai City, GuangdongProvince
3. Associate Professor?College of Intelligent Science and Engineering, Jinan University,No. 206, Qianshan Road, Xiangzhou District, Zhuhai City, Guangdong Province.
4. Professor, Department of Industrial and Manufacturing Systems Engineering, , The University of Hong Kong, Hong Kong, China,
*. Corresponding Author

MLA 8
Yunhui, Zeng, et al. "FAILURE ANALYSIS OF "PHOTOGRAPHING AND MAKING MONEY" TASK BASED ON B-P NEURAL NETWORK." Int. j. of Social Science and Economic Research, vol. 3, no. 9, Sept. 2018, pp. 5316-5334, ijsser.org/more2018.php?id=367. Accessed Sept. 2018.
APA
Yunhui, Z., Hongfei, G., Yuanbiao, Z., Guoquan, H., Shusheng, H., Yilin, C., Shiyue, S., & Zhengguo, C. (2018, September). FAILURE ANALYSIS OF "PHOTOGRAPHING AND MAKING MONEY" TASK BASED ON B-P NEURAL NETWORK. Int. j. of Social Science and Economic Research, 3(9), 5316-5334. Retrieved from ijsser.org/more2018.php?id=367
Chicago
Yunhui, Zeng, Guo Hongfei, Zhang Yuanbiao, Huang Guoquan, Huang Shusheng, Chen Yilin, Shen Shiyue, and Chen Zhengguo. "FAILURE ANALYSIS OF "PHOTOGRAPHING AND MAKING MONEY" TASK BASED ON B-P NEURAL NETWORK." Int. j. of Social Science and Economic Research 3, no. 9 (September 2018), 5316-5334. Accessed September, 2018. ijsser.org/more2018.php?id=367.

References
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Abstract:
This article takes a new mobile self-service method under the mobile Internet to "photograph and make money" as the research object. First, using the Surfer software, the contour map of the task distribution and price is drawn. Guess that the original pricing scheme is not only related to the latitude and longitude of the task distribution. It is also related to factors such as the degree of matching between members and tasks, the economic level of the city where the task is located, and the distance of tasks from the central city. The above conjecture was verified by B-P neural network. Finally, the Pearson coefficient is used to analyze the relevance of the task pricing, and the reasons for the failure to complete the main value theory and price theory are analyzed. It includes not considering the impact of the member's reputation value on its completion task, the remote task location the low pricing and the impact of non-monetary value of self-service labor crowdsourcing on members' completion of tasks, etc. This paper provides a theoretical basis and guiding significance for the pricing of self-service labor crowdsourcing under the mobile Internet in the future.