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Synthesis Biometric Materials Based on Cooperative Among (DSA, WOA and gSpan-FBR) to Water Treatment

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Proceedings of the 12th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2020) (SoCPaR 2020)

Abstract

Starting from a training point in the chemical laboratory, whose events take place in the chemical laboratory in addition to wasting time and money, in addition to the revolution, the dream in the world of technology and electronic computing is intelligence and feasibility, so that they can be creative and innovative, in addition to that, reduce the material costs and efforts in this field. Therefore, our research aims to analyze the complex chemical materials to generate new materials from them and to verify them from a computerized validity before performing this experiment in a laboratory. The proposed model consists of three basic steps: First: Dismantling the chemical compound, which represents a complex network, and converting it into a group of subgraphs through the use of one of the graph mining algorithms. Second: After that, each subgraph is taken and the stimulating substance is added to it to speed up the work of the chemical reaction until it reaches a state of stability, by adding new nodes and connections to that subgraph which leads to the production of New subgraph. Third: One of the optimization techniques is applied to each new set of subgraphs to produce a set of patterns that represent the best materials that can be produced from the original spoilers. Thus, we have determined in advance to the researcher what materials can be added to accelerate the chemical reaction and what percentages are accurately mixed using electronic computing before this reaction is carried out in his laboratory.

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Correspondence to Samaher Al-Janabi .

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Al-Janabi, S., Kadhum, G. (2021). Synthesis Biometric Materials Based on Cooperative Among (DSA, WOA and gSpan-FBR) to Water Treatment. In: Abraham, A., et al. Proceedings of the 12th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2020). SoCPaR 2020. Advances in Intelligent Systems and Computing, vol 1383. Springer, Cham. https://doi.org/10.1007/978-3-030-73689-7_3

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