Methodology for Selection and Placement of Agricultural Crops using Artificial Intelligence
Vladimir K. Kalichkin1, Roman A. Koryakin2, Tatyana A. Luzhnykh3, Vera S. Riksen4, Anastasia S. Rudneva5
1Vladimir K. Kalichkin*, Siberian Federal Scientific Centre of Agro-BioTechnologies of the Russian Academy of Sciences, Krasnoobsk, Russia.
2Roman A. Koryakin, Siberian Federal Scientific Centre of Agro-BioTechnologies of the Russian Academy of Sciences, Krasnoobsk, Russia.
3Tatyana A. Luzhnykh, Siberian Federal Scientific Centre of Agro-BioTechnologies of the Russian Academy of Sciences, Krasnoobsk, Russia; Novosibirsk State Agrarian University, Novosibirsk, Russia.
4Vera S. Riksen, Siberian Federal Scientific Centre of Agro-BioTechnologies of the Russian Academy of Sciences, Krasnoobsk, Russia; Novosibirsk State Agrarian University, Novosibirsk, Russia.
5Anastasia S. Rudneva, Novosibirsk State Agrarian University, Novosibirsk, Russia.
Manuscript received on November 12, 2019. | Revised Manuscript received on November 25, 2019. | Manuscript published on 30 November, 2019. | PP: 6059-6063 | Volume-8 Issue-4, November 2019. | Retrieval Number: D8638118419/2019©BEIESP | DOI: 10.35940/ijrte.D8638.118419
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The conceptualization of the domain knowledge “selection and placement of a crop” was carried out. The model contains ontological entities – classes and the relationships between classes, presented in the Unified Modeling Language format. The model describes five classes – “Crop”, “Crop biology”, “Conditions for growth and development”, “Control actions”, and “Placement”, as well as a list of characteristics that affect the performance targets of factors. An algorithm based on the control matrix has been proposed. With the participation of an expert, values from zero to one were assigned for seven factors of “Control actions”, based on the assumption that the control actions affect 22 factors of three other classes: “Crop biology”, “Conditions for growth and development”, and “Placement”. A crop selection can be performed by comparing these matrices with each other. A flow diagram for the preparation of decisions for crop cultivation management, which includes 84 control action chains, has been proposed. Each of these chains was also rated from zero to one for conformity with a certain ideal agronomic strategy. According to these estimates, it is possible to obtain the strongest and weakest strategies for the decision-maker. The structural management of crop selection and placement does not include changing of the models that calculate numbers in the final tables for each crop, but rather is the development of criteria for the presence of the class characteristics in the table for the domain knowledge. Adding or removing characteristics for each crop changes ratings and total values. Artificial intelligence identifies a set of strategies according to the algorithm of their evaluation, which was developed with the participation of an expert.
Keywords: Crop Selection And Placement, Domain Knowledge Conceptualization, Structural Management, UML Diagrams, Artificial Intelligence.
Scope of the Article: Artificial Intelligence.