Prediction and field application of water-conducting fracture zone height using a PSO-BP neural network optimised by dynamic mutation

W Weiyu Guo Y Yu Wang Y Yi Tan (State Key Laboratory of Bioactive Molecules and Druggability Assessment, and School of Pharmacy, Jinan University, 601 Huangpu Avenue West, Guangzhou 510632, China) X Xuhan Liu Y Yixiang Feng S Sijiang Wei X Xiaolei Wang (State Key Laboratory of Natural Product Chemistry, College of Chemistry and Chemical Engineering) W Weiyong Lu

Article Details

Volume / Issue Vol. 1, Issue 1
Published July 14, 2026
ISSN 2045-2322
Publisher Nature Portfolio

Journal Info

Scientific Reports

Nature Portfolio

ISSN: 2045-2322 Open Access Life Sciences

Authors (8)

W

Weiyu Guo

Y

Yu Wang

Y

Yi Tan

State Key Laboratory of Bioactive Molecules and Druggability Assessment, and School of Pharmacy, Jinan University, 601 Huangpu Avenue West, Guangzhou 510632, China

X

Xuhan Liu

Y

Yixiang Feng

S

Sijiang Wei

X

Xiaolei Wang

State Key Laboratory of Natural Product Chemistry, College of Chemistry and Chemical Engineering

W

Weiyong Lu