Constarium
← Search

Data · dataset · 2025

Dataset for "An Explainable Ensemble Machine Learning Approach for Coefficient of Compressibility Prediction of Chengdu Clay"

Listed in ScienceDB

This dataset contains the geotechnical parameters of Chengdu Clay used in the study titled “An Explainable Ensemble Machine Learning Approach for Coefficient of Compressibility Prediction”.

Description

The data includes [water content, specific gravity, liquidity index, plasticity index, and the measured coefficient of compressibility (av)] collected from [borehole samples in Chengdu, China]. The dataset comprises a total of [338] samples and is organized in a single CSV file.

It is intended to be used for training and validating machine learning models for predicting soil compressibility, ensuring the reproducibility of the aforementioned study.

Links

Where it is published

Catalogue records · 1

Topics

Inferred from text
Machine learning 70%
Provenance · 1 source records, 11 field assertions
SourceKeyLast seenRaw
ScienceDB10.57760/sciencedb.3445710 d agoJSON v1
FieldAssertionExtractorEvidence
concepts[field].anzsrc:group:4611enrichment · scidb cntaxonomy-embedding@1.0.0title+keywords+description (70%)
concepts[field].local:field:computer-science-aimapping · scidb cnconnector:scidb_cn@1.0.0
concepts[field].local:field:earth-environmentalmapping · scidb cnconnector:scidb_cn@1.0.0
concepts[field].local:field:engineeringmapping · scidb cnconnector:scidb_cn@1.0.0
concepts[field].local:field:humanitiesmapping · scidb cnconnector:scidb_cn@1.0.0
concepts[field].local:field:life-sciencesmapping · scidb cnconnector:scidb_cn@1.0.0
concepts[field].local:field:social-sciencemapping · scidb cnconnector:scidb_cn@1.0.0
descriptionsource · scidb cnconnector:scidb_cn@1.0.0/metadata/dc/description
license_textsource · scidb cnconnector:scidb_cn@1.0.0
publication_datesource · scidb cnconnector:scidb_cn@1.0.0
titlesource · scidb cnconnector:scidb_cn@1.0.0/metadata/dc/title