Performance Prediction and Ratio Design of Coal-Based Solid Waste Cemented Filling Materials Based on Ensemble Learning

Authors

Yupeng Li (ORCID: https://orcid.org/0000-0001-5394-8186)
Jiachen Liu (ORCID: https://orcid.org/0000-0002-9222-1876)
Shenyang Ouyang (ORCID: https://orcid.org/0000-0002-0304-3730)
Xin Cao
Yanli Huang

Institutions

Xi'an University of Science and Technology (CN)
China University of Mining and Technology (CN)
Xinjiang Institute of Engineering (CN)

Publication Details

Journal: Buildings
Published: 2026-08-21
DOI: https://doi.org/10.3390/buildings16163327
Primary Topic: Tailings Management and Properties
Type: article
Field-Weighted Citation Impact: 0.00

Funders

National Natural Science Foundation of China
China Postdoctoral Science Foundation
Fundamental Research Funds for the Central Universities

Controls

|||

ALL TIME

JAN

FEB

MAR

APR

MAY

JUN

JUL

AUG

SEP

OCT

article

Performance Prediction and Ratio Design of Coal-Based Solid Waste Cemented Filling Materials Based on Ensemble Learning

Yupeng Li, Jiachen Liu, Shenyang Ouyang, Xin Cao et al.

Aug 21, 2026

Buildings

Tailings Management and Properties

article

Performance Prediction and Ratio Design of Coal-Based Solid Waste Cemented Filling Materials Based on Ensemble Learning

Yupeng Li, Jiachen Liu, Shenyang Ouyang, Xin Cao, Yanli Huang

August 21, 2026article en

Abstract

No abstract available for this paper.

BuildingsVol. 16(16)

Xi'an University of Science and Technology (CN), China University of Mining and Technology (CN), Xinjiang Institute of Engineering (CN)

National Natural Science Foundation of China, China Postdoctoral Science Foundation, Fundamental Research Funds for the Central Universities

Openalex Percentile: Top 16%

Tailings Management and Properties

DOI Open Access PDF OpenAlex

AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.