Machine learning and analytic hierarchy process integration for selecting a sustainable tractor.

Selecting the appropriate tractor for small-scale farms is a complex process due to the multitude of technical, environmental, and economic criteria that must be evaluated. This study addresses this challenge by integrating the Analytic Hierarchy Process (AHP) with machine learning (ML) to reduce the number of criteria and simplify the decision-making process. The research aims to determine the most relevant criteria aligned with sustainable development goals for selecting the right tractor, focusing on small farms in the Egyptian Delta.

Energy-conversion efficiency for producing oxy-hydrogen gas using a simple generator based on water electrolysis.

Producing hydrogen efficiently through water electrolysis could greatly reduce fossil fuel consumption. As well as this renewable energy source will also help combat global warming and boost economic investment opportunities. This paper studied some factors affecting the performance of oxy-hydrogen/hydroxy (HHO) gas generator, such as applied voltage (from 10.