Issue |
E3S Web of Conf.
Volume 539, 2024
III International Conference on Agriculture, Earth Remote Sensing and Environment (RSE-III-2024)
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Article Number | 01013 | |
Number of page(s) | 7 | |
Section | Ecology, Environmental Protection and Conservation of Biological Diversity | |
DOI | https://doi.org/10.1051/e3sconf/202453901013 | |
Published online | 17 June 2024 |
Modeling the rational use of natural resources and innovative quantum technologies in agribusiness
1 Tashkent Institute of Irrigation and Agricultural Mechanization Engineers National Research University, Tashkent, Uzbekistan
2 Samarkand State University of Veterinary Medicine, Livestock and Biotechnologies, Samarkand, Uzbekistan
The influence of quantum computing techniques on the optimization of resource allocation in the agricultural sector is analyzed. The use of variational quantum eigensolver (VQE) algorithm to achieve optimal resource allocation is explored. It has been found that production functions, such as the Cobb-Douglas function, effectively describe the transformation of input parameters into output. Parameterization of a quantum circuit and minimization of the expected value of the Hamiltonian to optimize resource allocation are studied. It is determined that the quantum optimization approach demonstrates improved computational efficiency compared to classical methods. It has been found that the integration of quantum technologies can significantly improve resource allocation in agriculture. An assumption has been made about increasing productivity and sustainability in the agricultural sector thanks to quantum methods. Further research on quantum algorithms is proposed to improve the efficiency of natural resource management. New software has been developed for modeling and optimizing production functions in agriculture. The use of quantum computing to solve complex problems in the agricultural sector is justified. A detailed description of the quantum algorithm and its benefits in the context of agriculture is presented.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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