Modeling of the Mechanism of Action of Epilame Film in the Process of Processing

Zvyagina, Elena A.; Selemenev, M.F.; Frolenkova, Larisa; Kravchenko, I.; Kuznetsov, Yu. A.; Величко, С. А.; Ašonja, Aleksandar; Kalashnikova, Larisa

doi:10.46793/adeletters.2022.1.1.2

Cited by 2 publications

(1 citation statement)

References 14 publications

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“…In addition, the low supply of labor in agriculture requires that agricultural activities should be carried out using agricultural machinery [3]. Much attention should be paid to the selection of appropriate machinery in agriculture [4]. The basic requirement in agriculture is to reduce the costs of land cultivation [5], because it is necessary to reduce production costs to achieve higher revenues through the sale of agricultural products [6].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Agricultural Machinery Using Multi-Criteria Analysis Methods

et al. 2022

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To achieve the highest possible agricultural production, it is necessary to procure the appropriate agricultural machinery. A tractor is the most useful machine in agriculture that performs various functions. Therefore, the selection of a tractor is one of the key decisions in the agriculture-production process. This study aims to evaluate heavy tractors for agricultural production in Bosnia and Herzegovina. Since this is a selection between different tractors, which are evaluated using several criteria, the methods of multi-criteria analysis (MCDA) were used in this study. Five different methods were used to determine the weight of the criteria, of which a modified standard-deviation method is a new method used in practice, while the tractor ranking was performed using the CRADIS (compromise ranking of alternatives from distance to ideal solution) method. The results showed that the best-ranked tractor is A4, while the most deviations from the ranking occur when the entropy method is used. The contribution of this study is in the systematization of the methods for the objective determination of the criteria weights and the development of new methods to facilitate decision-making in agriculture and other industries.

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Section: Introductionmentioning

confidence: 99%

Evaluation of Agricultural Machinery Using Multi-Criteria Analysis Methods

et al. 2022

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

Sayed,

Abdelhamid,

Abdelkader

et al. 2024

Sci Rep

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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. Four tractors, with horsepower ranging from 55 to 95, were evaluated based on inputs from forty-two governmental service providers in the study area. Initially, nine criteria were identified, encompassing key technical, environmental, and economic factors. These criteria were reduced to three—price, power, and maintenance costs by weights 0.142, 0.334, and 0.525, respectively—using Hierarchical Agglomerative Clustering with Euclidean distance. This reduction streamlined the selection process, making it more practical for farmers. Results show that the second tractor (T2), with a priority score of 0.326 and a normalized value of 33.4%, emerged as the optimal choice for small-scale farmers, outperforming the first tractor (T1) (28.7%) and third tractor (T3) (21%). Integrating AHP and ML simplifies tractor selection, ensuring sustainability, cost-efficiency, and operational effectiveness.

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Modeling of the Mechanism of Action of Epilame Film in the Process of Processing

Cited by 2 publications

References 14 publications

Evaluation of Agricultural Machinery Using Multi-Criteria Analysis Methods

Evaluation of Agricultural Machinery Using Multi-Criteria Analysis Methods

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

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