Title :
Prediction of online trade growth using search-ANFIS: Transactions on Taobao as examples
Author :
Wang Jiyuan ; Peng Geng ; Dai Wei
Author_Institution :
Sch. of Manage., Univ. of Chinese Acad. of Sci., Beijing, China
Abstract :
The growth of E-commerce which can be seen in recent years, has contributed a lot to global economy. Prediction of trade, especially in C2C market, can help decision-makers obtain the information from the online transactions and find the knowledge underlying the data. This paper facilities the traditional search index prediction system with ANFIS model. By using purchasing transactions from Taobao, a C2C company in China, this paper trains and tests the model. Results show that, compared with traditional regression analysis method, Search-ANFIS system has higher prediction accuracy in online trade prediction.
Keywords :
electronic commerce; fuzzy neural nets; fuzzy reasoning; purchasing; search problems; C2C market; Taobao; decision-makers; e-commerce; global economy; online trade growth prediction; online transactions; purchasing transactions; regression analysis method; search index prediction system; search-ANFIS model; Accuracy; Adaptation models; Benchmark testing; Data models; Indexes; Predictive models; Training;
Conference_Titel :
Fuzzy Systems (FUZZ-IEEE), 2014 IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-2073-0
DOI :
10.1109/FUZZ-IEEE.2014.6891527