Evidence map›Paper›PMID 41335148›Full record

ArticleBioresources and bioprocessing2025

Development of robust machine learning models to estimate hydrochar higher heating value and yield based upon biomass proximate analysis.

Guoliang Hou, Ahmad Alkhayyat, Ahmad Almalkawi, Anupam Yadav, H S Shreenidhi, Vishnu Saini, Shirin Shomurotova, Devendra Singh, Vatsal Jain, Aseel Smerat and 1 more

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In one paragraph

Article in Bioresources and bioprocessing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Guoliang HouSchool of Mathematics, Changchun Normal University, Changchun, 130032, Jilin, China. houguoliang@ccsfu.edu.cn.
Ahmad AlkhayyatDepartment of Computers Techniques Engineering, College of Technical Engineering, The Islamic University, Najaf, Iraq. ahmedalkhayyat85@gmail.com.
Ahmad AlmalkawiCenter for ESL & Academic Preparation, Modern College of Business and Science, Muscat, Oman.
Anupam YadavDepartment of Computer Engineering and Application, GLA University, Mathura, 281406, India.
H S ShreenidhiDepartment of Computer Science and Engineering, School of Engineering and Technology, JAIN (Deemed to Be University), Bangalore, Karnataka, India.
Vishnu SainiSharda School of Engineering and Sciences, Sharda University, Knowledge Park III, Greater Noida, 201310, Uttar Pradesh, India.
Shirin ShomurotovaDepartment of Chemistry Teaching Methods, National Pedagogical University of Uzbekistan, Bunyodkor Street 27, Tashkent, Uzbekistan.
Devendra SinghDepartment of Computer Science & Engineering, Uttaranchal Institute of Technology, Uttaranchal University, Dehradun, Uttarakhand, 248007, India.
Vatsal JainCentre for Research Impact & Outcome, Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura, Punjab, 140401, India.
Aseel SmeratFaculty of Educational Sciences, Al-Ahliyya Amman University, Amman, 19328, Jordan.
Ahmad KhalidFaculty of Engineering, Sana'a University, Sanaa, Yemen. ahmad.khalidd1401@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study introduces a robust machine learning framework for predicting hydrochar yield and higher heating value (HHV) using biomass proximate analysis. A curated dataset of 481 samples was assembled, featuring input variables such as fixed carbon, volatile matter, ash content, reaction time, temperature, and water content. Hydrochar yield and HHV served as the target outputs. To enhance data quality, Monte Carlo Outlier Detection (MCOD) was employed to eliminate anomalous entries. Thirteen machine learning algorithms, including convolutional neural networks (CNN), linear regression, decision trees, and advanced ensemble methods (CatBoost, LightGBM, XGBoost) were systematically compared. CatBoost demonstrated superior performance, achieving an R

Indexed as

Biomass proximate analysisCatBoost algorithmHigher heating value (HHV)Hydrochar yield predictionMachine learning

Identifiers

PMID41335148
PMCPMC12675903

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.