Logarithmic Pythagorean neutrosophic vague aggregating operators and their real-life applications

Abstract

This article examines Pythagorean neurosophic vague set (PyNVS) problems relevant to multiple attribute decision-making (MADM). Pythagorean vague set (PyVS) and neutrosophic set (NS) can be generalized into Pythagorean neutrosophic vague set (PyNVS). We discuss log Pythagorean neutrosophic vague weighted averaging (log PyNVWA), logarithmic Pythagorean neutrosophic vague weighted geometric (log PyNVWG), log generalized Pythagorean neurosophic vague weighted averaging (log GPyNVWA) and log generalized Pythagorean neutrosophic vague weighted geometric (log GPyNVWG). In this article, we define the Euclidean distance (ED), Hamming distance (HD), operator laws, and flowchart using an algorithm. By analyzing log PyNVS through algebraic operations, we discuss its properties. They can identify the best option more quickly and understand the practicalities better. An illustrative example of this is the fusion of computer science and machine tool technology in agriculture. Furthermore, there are autonomous robot tractors and soil sterilization robots that can harvest crops, weed, and take photos of seed planting with seedlings. A random selection of five farmers (alternatives) has been made. Climate, water, soil, disease, and flooding are all criteria to consider when choosing a farmer. Our goal is to narrow down the options by comparing expert judgments with the criteria.