An Efficient Computational Model for Assessing the Stability Characteristics of Electro-active Natural Bio-resources

Abstract

Background: The properties of the natural bio-sensors as the fuel after treatment, is beneficial and considered as the most environmental friendly alternative. The microbial fuel cell will help in the bio electricity generation. To use them first, it is important to know the stability and the characteristics of such organic compound. The research presents the computational methods of assessment of stability and characteristics analysis of organic herbs, Syzygium and Citrus. Objective: MFC has a very vast research area and many scientists are rigorously working on MFCs. Here, we have explained research work related to what we have presented in the paper. Methods: To compute the stability of these microbial fuel cells, we have used two different methods on each herb, Structural Similarity Index Method (SSIM) and Graph Comparison using their Coordinates (GCC). Results: This research work provides the results of convergence towards the stability of herbs. Further, this section also presents the performance characteristics of the software algorithms and their comparative results to verify the outcomes of the herb characteristics using both methods. Conclusion: The proposed work is efficient in finding stability of MFCs on the selected herbs. The approach should work fine on other herbs as well. Machine Learning could have been much useful for this purpose if the availability of the data would have been much high.