Zhou, Feng, Zhou, Hao-min, Yang, Zhihua, and Yang, Lihua. EMD2FNN: A strategy combining empirical mode decomposition and factorization machine based neural network for stock market trend prediction. Retrieved from https://par.nsf.gov/biblio/10100547. Expert Systems with Applications 115.C Web. doi:10.1016/j.eswa.2018.07.065.

Zhou, Feng, Zhou, Hao-min, Yang, Zhihua, & Yang, Lihua. EMD2FNN: A strategy combining empirical mode decomposition and factorization machine based neural network for stock market trend prediction. Expert Systems with Applications, 115 (C). Retrieved from https://par.nsf.gov/biblio/10100547. https://doi.org/10.1016/j.eswa.2018.07.065

Zhou, Feng, Zhou, Hao-min, Yang, Zhihua, and Yang, Lihua. "EMD2FNN: A strategy combining empirical mode decomposition and factorization machine based neural network for stock market trend prediction". Expert Systems with Applications 115 (C). Country unknown/Code not available. https://doi.org/10.1016/j.eswa.2018.07.065. https://par.nsf.gov/biblio/10100547.

@article{osti_10100547,
place = {Country unknown/Code not available}, title = {EMD2FNN: A strategy combining empirical mode decomposition and factorization machine based neural network for stock market trend prediction}, url = {https://par.nsf.gov/biblio/10100547}, DOI = {10.1016/j.eswa.2018.07.065}, abstractNote = {}, journal = {Expert Systems with Applications}, volume = {115}, number = {C}, author = {Zhou, Feng and Zhou, Hao-min and Yang, Zhihua and Yang, Lihua}, }