基于区块链熵预测的贝叶斯估计密度模糊模函数改善供应链可持续性

Brandon Foley , James A. Rodger
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引用次数: 0

摘要

这项研究对三个相互关联和相互依存的目标进行了三角分析。首先,我们提供了一个框架,在可持续性理论的九个浪潮的关键范围内建立供应链理论。其次,我们提供了一个区块链如何运作的真实世界例子,以支持黑客攻击区块链需要非常大的计算能力这一前提。我们还展示了一种检测黑客攻击为区块链提供信息的单个节点的可能性的方法。第三,我们利用区块链收集了数千个数据点,并从统计上证明,石油和天然气行业的代币化将增加市场流动性、市场容量、盈利能力和可持续性,同时减少交易时间。通过模糊模块函数哈希和盐析算法以及熵密度,研究了机器人区块链作为提高天然气SC资源使用效率的机制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Bayes Estimate Density Fuzzy Modular function for improving supply chain sustainability through blockchain entropy prediction

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.

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