A Bayes Estimate Density Fuzzy Modular function for improving supply chain sustainability through blockchain entropy prediction

Abstract

This study triangulates three interrelated and interdependent goals. First, we provide a framework to establish the supply chain (SC) theory within the linchpins of the nine waves of sustainability theory. Second, we provide a real-world example of how blockchain operates to support the premise that hacking a blockchain requires very large capacities of computing power. We also demonstrate a method of detecting the possibility of hacking individual nodes that supply information to the blockchain. Third, we utilize the blockchain and gather thousands of data points and prove statistically that the tokenization of the oil and gas industry will increase market liquidity, market volume, profitability, and sustainability while reducing transaction time. The robotic blockchain is investigated as a mechanism for improving the efficiency of natural gas SC resource use through fuzzy modular function hashing and salting algorithms and entropy density.