Abstract
The problem of Germany’s daily oil shortage draws our attention to determine the factors contributing to the large in oil consumption. In this project, we are interested to investigation whether conventional cars industry are the primary cause to the problem. This project aims to use Logistics and Lotka Volterra models to find the growth rate and to analyze the population dynamic of conventional cars and oil production. To elaborate, the major goal of this research we used a logistics model to find the growth rate of conventional cars and oil production, as well as a lotka volterra model to analyze the dynamic population of conventional cars and oil industry, particularly in Germany. We have the prey, which is oil production, and the predator, which is conventional cars, in the Lotka Volterra model. As a result, we aim to find a solution to the problem of conventional cars being the primary cause of oil production fluctuations in Germany. In this work, we utilised two methods to calculate the growth rate which are the logistic model and Lotka Volterra model for oil production and conventional cars in Germany. We entered the growth rate figures into Microsoft Excel to forecast future production for these two industries. We saw the relationship between them by entering the growth rate acquired in the first objective into Python. As a result, the growth rate of prey and predators plays a substantial impact in the development of an industry, according to our findings. Among these, conventional cars will be unable to function if oil production ceases. In conclusion, this technique is crucial because it allows the oil industry to correctly build long-term operating plans without having to deal with complications when inevitable events occur. As a result, the idea of conducting an oil peak risk analysis to determine the benefits and costs of minimising the likelihood of oil peak events might be very useful, and the option of oil fuel switching transportation should be strongly supported.
Metadata
Item Type: | Student Project |
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Creators: | Creators Email / ID Num. Muhammad Daud, Nur Faqihah 2020993331 Mohammad, Muhammad Alif 2020993207 Mohd Nazita, Nurul Izzah 2020985341 |
Contributors: | Contribution Name Email / ID Num. Advisor Ismail, Mardhiyah UNSPECIFIED |
Subjects: | Q Science > QA Mathematics > Analysis T Technology > TL Motor vehicles. Aeronautics. Astronautics > Motor vehicles. Cycles T Technology > TP Chemical technology > Oils, fats, and waxes |
Divisions: | Universiti Teknologi MARA, Kelantan > Machang Campus > Faculty of Computer and Mathematical Sciences |
Programme: | Bachelor of Science (Hons) Mathematics |
Keywords: | Logistics and Lotka Volterra models, Microsoft Excel, Python, Transportation |
Date: | February 2022 |
URI: | https://ir.uitm.edu.my/id/eprint/72352 |
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