Forecasting the time stock for chemical plant protection based on computer simulations
Article Sidebar
Main Article Content
Abstract
The approach, algorithm, and intelligent system of support of decision-making of management for forecasting of time fund for the performance of the mechanized chemical protection of plants are offered. They are based on the formation of a database and knowledge of the weather from the Open Weather Map service for individual countries and their regions. They provide the formation of databases and knowledge for a given country or its region, taking into account the characteristics of natural, climatic, and industrial conditions based on computer modelling. Also, the proposed intelligent management decision support system provides a systematically accountable set of variable agrometeorological components of the mechanized chemical plant protection system and their impact on the projected time fund of the relevant work. Based on the use of the developed intelligent system of support of acceptance of administrative decisions forecasting of time fund for the performance of the mechanized chemical protection of plants and the set natural-climatic and industrial conditions is executed. The climatically admissible time fund model for mechanized chemical protection of plants during the day for May, which is described by Weibull distribution, is substantiated. The obtained research results can be used by managers of agricultural enterprises during the management processes of forecasting the time fund for the implementation of mechanized chemical plant protection. The developed intelligent decision support system provides further research on forecasting the time fund for the implementation of mechanized chemical plant protection and substantiation of its models for different countries and their regions.
Downloads
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
1. Proposal of Policy for Free Access Periodics
Authors whom publish in this magazine should agree to the following terms:
a. Authors should keep the copyrights and grant to the magazine the right of the first publication, with the work simultaneously permitted under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 that allows the sharing of the work with recognition of the authorship of the work and initial publication in this magazine.
b. Authors should have authorization for assuming additional contracts separately, for non-exclusive distribution of the version of the work published in this magazine (e.g.: to publish in an institutional repository or as book chapter), with recognition of authorship and initial publication in this magazine.
c. Authors should have permission and should be stimulated to publish and to distribute its work online (e.g.: in institutional repositories or its personal page) to any point before or during the publishing process, since this can generate productive alterations, as well as increasing the impact and the citation of the published work (See The Effect of Free Access).
Proposal of Policy for Periodic that offer Postponed Free Access
Authors whom publish in this magazine should agree to the following terms:
a. Authors should keep the copyrights and grant to the magazine the right of the first publication, with the work simultaneously permitted under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 [SPECIFY TIME HERE] after the publication, allowing the sharing of the work with recognition of the authorship of the work and initial publication in this magazine.
b. Authors should have authorization for assuming additional contracts separately, for non-exclusive distribution of the version of the work published in this magazine (e.g.: to publish in institutional repository or as book chapter), with recognition of authorship and initial publication in this magazine.
c. Authors should have permission and should be stimulated to publish and to distribute its work online (e.g.: in institutional repositories or its personal page) to any point before or during the publishing process, since this can generate productive alterations, as well as increasing the impact and the citation of the published work (See The Effect of Free Access).
d. They allow some kind of open dissemination. Authors can disseminate their articles in open access, but with specific conditions imposed by the editor that are related to:
Version of the article that can be deposited in the repository:
Pre-print: before being reviewed by pairs.
Post-print: once reviewed by pairs, which can be:
The version of the author that has been accepted for publication.
The editor's version, that is, the article published in the magazine.
At which point the article can be made accessible in an open manner: before it is published in the magazine, immediately afterwards or if a period of seizure is required, which can range from six months to several years.
Where to leave open: on the author's personal web page, only departmental websites, the repository of the institution, the file of the research funding agency, among others.
References
Bashynsky, O. (2019). Coordination of dairy workshops projects on the community territory and their project environment. In: 14-th International Scientific and Technical Conference on Computer Sciences and Information Technologies. Lviv Polytechnic National University, 17–20 September. Lviv, 51–54.
Bazzaz, F., & Sombroek, W. (1996). Global climate change and agricultural production: direct and indirect effects of changing hydrological soil and plant physiological processes. FAO, Rome, Italy. Available at: http://www.fao.org/docrep/w5183e/w5183e00.htm#Contents.
Boyarchuk, V. & Ftoma, O. (2019). Forecasting of a lifecycle of the projects of production of biofuel raw materials with consideration of risks. International Conference on Advanced Trends in Information Theory (ATIT), pp. 420-425.
Boyarchuk, V., Boyarchuk, V. & Ftoma, O. (2019). Evaluation of risk value of investors of projects for the creation of crop protection of family dairy farms. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 67(5), 1357–1367.
Boyarchuk, V., Ftoma, O., Francik, S., & Rudynets, M. (2020). Method and software of planning of the substantial risks in the projects of production of raw material for biofuel. In: International Workshop IT Project Management. Ukrainian Project Management Association “UKRNET” & Lviv Polytechnic National University, 18–20 February. Slavsko, pp. 116–129.
Boychenko, S., & Voloshchuk, V. (2007). The stochastic semi-empirical model of space-temporal transformation of the modern climate of Ukraine. National Academy of Science of Ukraine, 1,105-109.
Fraisse, C. W., Breuer, N. E., Zierden, D., Bellow, J. G., Paz, J., Cabrera, V. E., … O'brien, J. J. (2006). AgClimate: a climate forecast information system for agricultural risk management in the southeastern USA. Computers and Electronics in Agriculture, 53(1), 13–27.
Hulida, E., Pasnak I., & Koval, O. (2019). Determination of the Critical Time of Fire in the Building and Ensure Successful Evacuation of People. Periodica Polytechnica Civil Engineering, 63(1), 308-316.
Islam, S., & Mandal, W. A. (2017). A fuzzy inventory model (EOQ model) with unit production cost, time depended holding cost, without shortages under a space constraint: a fuzzy parametric geometric programming (FPGP) approach. Independent Journal of Management & Production, 8(2), 299-318. DOI: 10.14807/ijmp.v8i2.535.
Ljaskovska, S., Martyn, Y., Malets, I., & Prydatko, O. (2018). Information technology of process modeling in the multiparameter systems. In: II International Conference on Data Stream Mining and Processing. Lviv Polytechnic National University, 21–25 August. Lviv, pp. 177–182.
Lobell, D., & Field, C. (2007). Global scale climate–crop yield relationships and the impacts of recent warming. Environ. Res. Lett., 2, 1-7.
Lohosha, R., Mykhalchyshyna, L., Prylutskyi, A., & Kubai, O. (2020) Institutionalization of the agrarian market in Ukraine and European economic community: genesis, evaluation and analysis. Independent Journal of Management & Production, 11(8), 727-750. DOI: 10.14807/ijmp.v11i8.1232.
Nuzhna, O., Tluchkevych, N., Semenyshena, N., Nahirska, K., & Sadovska, I. (2019). Making managerial decisions in the agrarian management through the use of ABC-Analysis tool. Independent Journal of Management & Production, 10(7), 798-816. DOI: http://dx.doi.org/10.14807/ijmp.v10i7.901.
Pavlikha, N., Rudynets, M., Grabovets, V., Skalyga, M., Tsymbaliuk, I., Khomiuk, N., & Fedorchuk-Moroz, V. (2019). Studying the influence of production conditions on the content of operations in logistic systems of milk collection. Eastern-European Journal of Enterprise Technologies: Control processes, 99(3/3), 50–63.
Ratushny, R., Bashynsky, O. & Shcherbachenko, O. (2018). Identification of firefighting system configuration of rural settlements Fire and Environmental Safety Engineering. MATEC Web Conf (FESE 2018), 247. DOI: https://doi.org/10.1051/matecconf/201824700035.
Ratushny, R., Bashynsky, O., & Ptashnyk, V. (2019). Development and usage of a computer model of evaluating the scenarios of projects for the creation of firefighting systems of rural communities. In: XI-th International Scientific and Practical Conference on Electronics and Information Technologies. Ivan Franko National University of Lviv, 16–18 September. Lviv, 34–39.
Ratushnyi, R., Khmel, P., Martyn, E., & Prydatko, O. (2019). Substantiating the effectiveness of projects for the construction of dual systems of fire suppression. Eastern-European Journal of Enterprise Technologies: Control processes, 100(4/3), 46–53.
Roy, P. C., Guber, A., Abouali, M., Pouyan Nejadhashemi, A., Deb, K., & Smucker, A. (2019). Crop yield simulation optimization using precision irrigation and subsurface water retention technology. Environmental Modelling & Software, 119, 433–444.
Serrano, I. V., Gonzalez–Hidalgo, S. M., De Luis, J. C., & Raventos, M. J. (2004). Drought patterns in the Mediterranean area: the Valencia region (Eastern Spain). Climate Research, 26, 5-15.
Sokulskyi, O., Hilevska, K., Chumakevych, V., Ptashnyk, V., & Sachenko, A. (2020). The Internet of Things Solutions in the Investigation of Urban Passenger Traffic and Passenger Service Quality. IEEE European Technology and Engineering Management Summit (E-TEMS). DOI: 10.1109/E-TEMS46250.2020.9111658.
Syrotiuk, V., Syrotiuk, S., Ptashnyk, V., Baranovych, S., Gielzecki, J., & Jakubowski, T. (2020). A hybrid system with intelligent control for the processes of resource and energy supply of a greenhouse complex with application of energy renewable sources. Przegląd elektrotechniczny, 96(7), 149-152.
Tryhuba, A., Boyarchuk, V., Tryhuba, I., Ftoma, O., Padyuka, R., & Rudynets, M. (2019). Forecasting the Risk of the Resource Demand for Dairy Farms Basing on Machine Learning. Proceedings of the 2nd International Workshop on Modern Machine Learning Technologies and Data Science (MoMLeT+DS 2020), I, 327-340.
Тryhuba, A., Bashynskyi, O., Medvediev, Y., Slobodian, S., & Skorobogatov, D. (2019). Justification of models of changing project environment for harvesting grain, oilseed and legume crops. Independent Journal of Management & Production, 10(7), 658-672.
Тryhuba, A., Hridin, O., Slavina, N., Mushenyk, I., & Dobrovolska, E. (2020). Managerial decisions in logistic systems of milk provision on variable production conditions. Independent Journal of Management & Production, 11(8), 783-800.
Тryhuba, A., Hutsol, T., Glowacki, S., Tryhuba, I., Tabor, S., Kwaśniewski, D., Sorokin, D., & Yermakov, S. (2021). Forecasting Quantitative Risk Indicators of Investors in Projects of Biohydrogen Production from Agricultural Raw Materials. Processes, 9(2), 258. DOI: https://doi.org/10.3390/pr9020258.
Тryhuba, A., Ivanyshyn, V., Chaban, V., Mushenyk, I., & Zharikova, O. (2021). Influence of agrometeorological component of the project environment on the duration of works in chemical protection projects of agricultural crops. Independent Journal of Management & Production (Special Edition ISE, S&P), 12(3), 138-149. DOI: https://doi.org/10.14807/ijmp.v12i3.1531.
Тryhuba, A., Тryhuba, І., Mushenyk, І., Pashсhenko, О., & Likhter, М. (2020). Computer model of resource demand planning for dairy farms. Independent Journal of Management & Production, 11(9), 658-672. DOI: https://doi.org/10.14807/ijmp.v11i9.1410.