Wen Song

Waseda University

H-index: 3

Asia-Japan

About Wen Song

Wen Song, With an exceptional h-index of 3 and a recent h-index of 3 (since 2020), a distinguished researcher at Waseda University, specializes in the field of Time series Forecasting.

His recent articles reflect a diverse array of research interests and contributions to the field:

Sensor data prediction in process industry by capturing mixed length of time dependencies

Distributed-elite local search based on a genetic algorithm for bi-objective job-shop scheduling under time-of-use tariffs

Capturing combination patterns of long-and short-term dependencies in multivariate time series forecasting

Short-term electricity consumption forecasting based on the attentive encoder-decoder model

特集 2019 年電子・情報・システム部門大会

Wen Song Information

University	Waseda University
Position	___
Citations(all)	41
Citations(since 2020)	41
Cited By	2
hIndex(all)	3
hIndex(since 2020)	3
i10Index(all)	2
i10Index(since 2020)	2
Email	Access Email
University Profile Page	Waseda University
Google Scholar	View Google Scholar Profile

Wen Song Skills & Research Interests

Time series Forecasting

Wen Song

Waseda University

About Wen Song

Wen Song Information

Wen Song Skills & Research Interests

Top articles of Wen Song

Sensor data prediction in process industry by capturing mixed length of time dependencies

Wen Song

Distributed-elite local search based on a genetic algorithm for bi-objective job-shop scheduling under time-of-use tariffs

Bobby Kurniawan

Wen Song

Wei Weng

Capturing combination patterns of long-and short-term dependencies in multivariate time series forecasting

Wen Song

Short-term electricity consumption forecasting based on the attentive encoder-decoder model

Wen Song

Wei Weng

特集 2019 年電子・情報・システム部門大会

Wen Song

Wei Weng