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A Novel Methodology for Blockchain Traceable Food Supply Chain Based on the Composite Control Adaptive Neuro Fuzzy Inference System Technique

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Abstract

A transnational network in the agricultural supply chains has surfaced as a result of the development of a large number of stakeholders who are connected to one another via intricate interactions. Agricultural supply chains are plagued by a lack of openness, which is supported by the fact that fraudulent acts are committed on a regular basis. This lack of transparency gives rise to concerns about potential financial losses, disintegration of consumer confidence, and a decline in the company's brand image. These days, customers expect food production systems that put an emphasis on equality, sustainability, and safety respectively. Businesses use platforms such as blockchains and the internet of things in order to satisfy these expectations. Combining blockchain technology with an Adaptive Neuro-Fuzzy Inference System (ANFIS) brought to the development of the SecureTrace3+ protocol, which was designed to fulfil these objectives. For the purpose of identifying potential dangers to a network, SecureTrace3+ makes use of fuzzy control, fuzzy matching, and an improved Composite Controller ANFIS (CC-ANFIS) attack detection model. In order to verify transactions, SecureTrace3+ makes use of fuzzy matching. In addition to addressing the challenges posed by uncertainty, this strategy offers more flexibility in terms of decision-making and transaction approval inside the blockchain layer. When it comes to identifying potential dangers on blockchain and Internet of Things networks, the evaluation findings indicate that the blockchain layer is effective based on throughput and latency measures, but the fuzzy layer is effective based on performance metrics such as accuracy, precision, recall, and F1-score scores.Article title: Kindly check and confirm the edit made in the title.Yes. It is finePlease check and confirm that the authors and their respective affiliations have been correctly identified and amend if necessary.Yes, it is correctly done

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Data Availability

The dataset produced and examined in this study can be obtained upon reasonable request from the corresponding author.

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Acknowledgements

We extend our heartfelt thanks to the Jain Deemed to be University, Bengaluru, Karnataka, India for spearheading this research endeavour.

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Correspondence to Feon Jaison.

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Jaison, F., Janaki, K. A Novel Methodology for Blockchain Traceable Food Supply Chain Based on the Composite Control Adaptive Neuro Fuzzy Inference System Technique. SN COMPUT. SCI. 5, 1095 (2024). https://doi.org/10.1007/s42979-024-03450-8

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