Application of machine learning for environmentally friendly advancement: exploring biomass-derived materials in wastewater treatment and agricultural sector − a review

Journal of Environmental Science and Health Part A, Год журнала: 2025, Номер unknown, С. 1 - 16

Опубликована: Фев. 2, 2025

There are several uses for biomass-derived materials (BDMs) in the irrigation and farming industries. To solve problems with material, process, supply chain design, BDM systems have started to use machine learning (ML), a new technique approach. This study examined articles published since 2015 understand better current status, future possibilities, capabilities of ML supporting environmentally friendly development applications. Previous applications were classified into three categories according their objectives: material process performance prediction sustainability evaluation. helps optimize BDMs systems, predict properties performance, reverse engineering, data difficulties evaluations. Ensemble models cutting-edge Neural Networks operate satisfactorily on these datasets easily generalized. neural network poor interpretability, there not been any studies assessment that consider geo-temporal dynamics; thus, building methods is currently practical. Future research should follow workflow. Investigating potential system optimization, evaluation sustainable requires further investigation.

Язык: Английский

Fluorescent Rhodamine Sensors for Mercury, Iron, and Copper Ion Detection in Water: Mechanisms and Applications

Journal of Fluorescence, Год журнала: 2025, Номер unknown

Опубликована: Апрель 16, 2025

Язык: Английский

Advances in Nanoparticle-Enhanced Paper Sensor for Detecting Toxic Metals in Water

Talanta, Год журнала: 2025, Номер 293, С. 128146 - 128146

Опубликована: Апрель 14, 2025

Язык: Английский