Quantitative Chemical Oxygen Demand Prediction Model based on Improved African Vulture Optimization Algorithm

Q: What does this research mean for the field?

An improved African Vulture Optimization Algorithm provides an effective quantitative prediction model for Chemical Oxygen Demand (COD) in surface water by addressing complex non-linear interferences like turbidity in UV-Vis spectroscopy. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

Xin Eric Wang; Xiaomei Cui; Qiaoling Du

doi:10.1039/d5ew01047k

January 1, 2026Environmental Science Water Research & Technology

Quantitative Chemical Oxygen Demand Prediction Model based on Improved African Vulture Optimization Algorithm

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Key Points

The aim is to develop a predictive model for chemical oxygen demand (COD) using UV-Vis spectroscopy.
Utilized an improved African Vulture Optimization Algorithm for model development.
Applied this model to analyze surface water samples for COD detection.
Assessed performance under varying turbidity and interfering factors.
Achieved significant accuracy in COD prediction despite complex non-linear relationships.
Reduction in prediction errors compared to traditional methods was noted.
Demonstrated robust performance in multiple surface water conditions.

Implication

Develops a model to predict COD in surface water, suggesting enhanced detection methods.

Abstract

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Cite This Study

Wang et al. (2026) studied this question.

synapsesocial.com/papers/6a1bd0b55783ba022b6fc71b https://doi.org/10.1039/d5ew01047k

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Quantitative Chemical Oxygen Demand Prediction Model based on Improved African Vulture Optimization Algorithm

Key Points

Implication

Abstract

Discussion

Cite This Study

Quantitative Chemical Oxygen Demand Prediction Model based on Improved African Vulture Optimization Algorithm

Key Points

Implication

Abstract

Discussion

Cite This Study

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