Paper Title
Applications of Artificial Neural Networks (ANN) and Response Surface Methodology (RSM) to Enhance Sustainable Phytoextraction of Lead From Polluted Soil

Abstract
Soil surface containment of lead (Pb) is widely recognized. Phytoremediation, which involves a number of chemical reactions and cost analysis, has proven to be the most effective approach to recover lead from soil in the previous few decades. This paper compares two modeling approaches, artificial neural networks (ANNs) with the genetic algorithm (GA) and response surface methodology (RSM), with the goal of modeling and optimizing Pb extraction from the contaminated soil via Pelargonium hortorum. The Pb tolerance of bacterial strains (NCCP 1844, 1848, 1857, and 1862) was assessed in vitro essays, and then bacteria and citric acid were co-applied on a Pb hyperaccumulator (Pelargonium hortorum L.) on Murashige and Skoog (MS) agar medium to ascertain the significance of the suggested solution. After that, Pelargonium hortorum L. was used in a pot culture experiment to maximize Pb extraction competency from Pb-spiked (0 mg kg−1, 500 mg kg−1, 1000 mg kg−1, and 1500 mg kg−1) soil. Citric acid (5 and 10 mmol L−1) and Microbacterium paraoxydance (1 and 1.5 OD) were added to the mixture. Plants were taken out at 30, 60, and 90-day intervals, and their dry biomass and Pb uptake properties were examined. After using 500 mg kg−1 soil Pb for 60 days, the highest Pb extraction efficiency of 86.0% was attained. Moreover, RSM was used to simulate Pb extraction from the soil. It was based on the Box-Behnken design (BBD) and the ANN-based Levenberg-Marquardt Algorithm (LMA). The RSM and LMA projected values were close to 36.0% and 86.05%, respectively, indicating their relevance. The thorough analysis of these results supported the ANN's efficiency, accuracy, and dependability during the optimization process. Therefore, in addition to being potentially economical and environmentally benign, experimental results demonstrated that ANN is an accurate technique to optimize an integrated phytoremediation system for sustained Pb removal. Keywords - Soil Contamination; Citric Acid; Bacteria; ANN; RSM