The release analysis of As and Cr metals in lead-zinc smelting slag: Mineralogical analysis, bioavailability and leachability analysis

Ma, Yaoqiang; Li, ChenChen; Yan, Jinpei; Yu, Hanjing; Kan, Huiying; Yu, Wanquan; Zhou, Xinyu; Meng, Qi; Yu, Xuegong

doi:10.1016/j.envres.2023.115751

Cited by 10 publications

(2 citation statements)

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“…Step 4: If the food quantity Q is less than 0.25, enter the foraging mode to search for food, and update the coordinates according to Equations ( 5) and (6).…”

Section: Improved Snake Optimization Algorithm Processmentioning

confidence: 99%

“…There have been numerous studies on methods for the recovery of secondary metal resources from zinc smelting slag [6][7][8], including leaching methods, electrochemical methods, and smelting roasting methods. Wei et al successfully recovered cobalt and zinc from leachate of zinc smelting slag using a leaching method, achieving good recovery results [9].…”

Section: Introductionmentioning

confidence: 99%

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Optimization of Zinc Smelting Slag Melting Point Based on Catboost and Improved Snake Optimization Algorithm

Kong,

Liu

2024

Applied Sciences

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The regulation of the melting point of zinc smelting slag has an important impact on the subsequent smelting processes of the metal. In actual production, uncontrollable melting points may result in inconsistent product quality, which has a great negative impact on the smelter’s efficiency and environmental protection. However, the regulation mechanism of the melting point of the smelting slag is complex, with many influencing factors, and there is no recognized high-precision calculation method. In response to these challenges, this study introduces an innovative approach for optimizing the melting point of zinc smelting slag based on the improved Snake Optimization (ISO) algorithm. The melting point of zinc smelting slag is modeled using the Catboost algorithm, and the model parameters are optimized using the Tree-structured Parzen Estimator (TPE) to improve the accuracy of the model. Next, the ISO algorithm is employed to conduct optimization calculations, determining the optimal values of various production process parameters that minimize the melting point. The effectiveness of this approach was evaluated using diverse modeling algorithms and test functions, subsequently applied to optimize and validate actual production data from a smelter in Shaanxi, China. Statistical analyses reveal that the TPE-optimized Catboost model exhibits an R2 of 93.89%, an RMSE of 7.02 °C, an MAE of 6.19 °C, and an MRE of 7.88%, surpassing performance metrics of alternative algorithms. Regarding optimization efficacy, the proposed ISO algorithm achieves an average reduction of 65 °C in the melting point and demonstrates superior robustness compared to both actual production data and alternative algorithms.

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“…Step 4: If the food quantity Q is less than 0.25, enter the foraging mode to search for food, and update the coordinates according to Equations ( 5) and (6).…”

Section: Improved Snake Optimization Algorithm Processmentioning

confidence: 99%