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System ekspertowy wspomagający podejmowanie decyzji w procesie zwalczania szkodników warzyw w okresie wegetacji
Języki publikacji
Abstrakty
The paper presents a computer system supporting the identification of vegetable pests during the vegetation period and the way in which it works on the example of red beet. The objective was to develop an expert system to facilitate the identification of pests and suggest an appropriate method of controlling them. Filling the database with the knowledge applying to one narrow area of knowledge turns the expert system framework into an expert system in this area of knowledge. The system consists of the expert system and the database in the form of text files, which contain additional explanations. The user of the expert system - “DSS - pest control” needs to answer the following questions: in the first stage the user selects the diagnosed vegetable, in the second stage, the user selects the symptom or symptoms on the above-ground vegetable part, in the third stage, the user selects the symptom or symptoms on the below-ground vegetable part. The designed decision support system (“DSS - pest control”) may be used by individual vegetable growers. It may also serve as an educational program, e.g. for students who want to find out more about the specific areas of knowledge as well as for scientists and researchers.
Artykuł przedstawia system komputerowy wspomagający identyfikację szkodników warzyw podczas procesu wegetacji, a także sposób jego działania na przykładzie buraka czerwonego. Celem było opracowanie systemu ekspertowego ułatwiającego identyfikację szkodników oraz zaproponowanie odpowiedniej metody ich zwalczania. Wypełnienie bazy wiedzy informacjami odnoszącymi się do wąskiego obszaru wiedzy zamienia system ekspertowy w system w danej dziedzinie wiedzy. System składa się z systemu ekspertowego oraz bazy danych w postaci plików tekstowych, które zawierają dodatkowe wyjaśnienia. Użytkownik systemu ekspertowego - "DSS - zwalczanie szkodników" musi odpowiedzieć na następujące pytania: w pierwszym etapie użytkownik wybiera diagnozowane warzywo, w drugim etapie użytkownik wybiera objaw lub objawy na nadziemnej części warzywa, w trzecim etapie użytkownik wybiera objaw lub objawy na podziemnej części warzywa. Zaprojektowany system wspomagania decyzji ("DSS - zwalczanie szkodników") może być stosowany przez indywidualnych plantatorów warzyw. Może również służyć jako program edukacyjny, np. dla studentów, którzy chcą pogłębić swoją wiedzę, może być także pomocny dla naukowców i badaczy.
Czasopismo
Rocznik
Tom
Strony
331--348
Opis fizyczny
Bibliogr. 30 poz., rys., tab.
Twórcy
autor
- Institute of Mechanical Engineering, Warsaw University of Life Sciences, ul. Nowoursynowska 164, 02-787 Warszawa, Poland
autor
- Institute of Mechanical Engineering, Warsaw University of Life Sciences, ul. Nowoursynowska 164, 02-787 Warszawa, Poland
autor
- Institute of Mechanical Engineering, Warsaw University of Life Sciences, ul. Nowoursynowska 164, 02-787 Warszawa, Poland
autor
- Institute of Mechanical Engineering, Warsaw University of Life Sciences, ul. Nowoursynowska 164, 02-787 Warszawa, Poland
autor
- Department of Mechanics and Agroecosystems Engineering, Polissia National University, 10-008, Zhytomyr, Ukraine
autor
- Odesa State Agrarian University, 65-012 Odesa, Ukraine
- Innovative Program of Strategic Development of the University, European Social Fund, University of Agriculture in Krakow, 30-149 Krakow, Poland
autor
- Innovative Program of Strategic Development of the University, European Social Fund, University of Agriculture in Krakow, 30-149 Krakow, Poland
- Higher Educational Institution “Podillia State University”, 32-300 Kamianets-Podilskyi, Ukraine
autor
- Metacon AB, Drottninggatan 1B, 75310 Uppsala, Sweden
- Ukrainian University in Europe - Foundation, Balicka 116, 30-149 Kraków, Poland
autor
- Institute of Design and Engineering Technologies, Slovak University of Agriculture in Nitra,Slovakia
Bibliografia
- Białko, M. (1996). Methods and application of artificial intelligence. Poland: Politechnika Koszalińskia Press.
- Cohen, Y., Cohen, A., Hetzroni, A., Alchanatis, V., Broday, D., Gazit, Y. & Timar, D. (2008). Spatial decision support system for Medfly control in citrus. Computers and Electronics in Agriculture. 62, 107-117.
- Duch, W. (1997). Fascinating world of computers. Poland: Nakom Press.
- Francik, K. & Pudło, M. (2016). Decision Support Systems in the Aspect of Risk Management in Enterprise. Zeszyty Naukowe Politechniki Częstochowskiej. Zarządzanie. 22, 23-32.
- Gonzalez-Andujar, J.L., Fernandez-Quintanilla, C., Izquierdo, J. & Urbano, J.M. (2006). SIMCE: An expert system for seedling weed identification in cereals. Computers and Electronics in Agriculture. 54, 115-123.
- Górnicki, K. & Sojak, M. (1999). The features of a computer system analyzing processes undergoing in vegetables during drying and storage. In Artificial Intelligence - the new face (research-applications-development) AI-14’99, 29-30.09.1999 (275-280), Poland.
- Hermann, O. (2006). Report N° 14. Survey on pests and diseases in red beet growing and the cost of plant protection products in Europe. Poland, Kraków: Sigma-not.
- Kaleta, A., Górnicki, K. & Sojak, M. (2005). A decision support system for vegetables quality assessment during drying and storage. In Trajer J. & Jaros M., The application of artificial intelligence for the assessment of changes in the quality of selected vegetables during drying and storage (68-110). Warsaw: SGGW Press.
- Kaloudis, S.T., Yialouris, C.P., Lorentzos, N.A., Karteris, M. & Sideridis, A.B. (2010). Forest management planning expert system for wildfire damage reduction. Computers and Electronics in Agriculture. 70, 285-291.
- Karmakar, S., Ketia, M.N., Laguë, C. & Agnew, J. (2010). Development of expert system modeling based decision support system for swine manure management. Computers and Electronics in Agriculture. 71, 88-95.
- Kuflik, T., Prodorutti, D., Frizzi, A., Gafni, Y., Shoham, S. & Pertot, I. (2009). Optimization of copper treatments in organic viticulture by using a web-based decision support system. Computers and Electronics in Agriculture. 68, 36-43.
- Kuo, S.F., Merklem, G.P. & Liu, C.W. (2000). Decision support for irrigation project planning using a genetic al-gorithm. Agriculture Water Management. 45(3), 243-266.
- Mahaman, B.D., Harizanis, P., Filis, I., Antonopoulou, E., Yialouris, C.P. & Sideridis, A.B. (2002). A diagnostic expert system for honeybee pests. Computers and Electronics in Agriculture. 36, 17-31.
- Mahaman, B.D., Passam, H.C., Sideridis, A.B. & Yialouris, C.P. (2003). DIARES-IPM: a diagnostic advisory rule-based expert system for integrated pest management in Solanaceous crop systems. Computers and Electronics in Agriculture. 76, 1119-1135.
- Mann, D., Jayas, D., White, N., Muir, W. & Evans, M. (1997). A grain storage information system for Canadian farmers and grain storage managers. Canadian Agricultural Engineering. 39 (1), 49-56.
- Michalik, K. (1998). In-tegrated AI package SPHINX. Knowledge engineer textbook. Katowice: AITECH - Artifical Intelligence Laboratory.
- Molina-Martínez, J.M. & Ruiz-Canales, A. (2009). Pocket PC software to evaluate drip irrigation lateral diameters with on-line emitters. Computers and Electronics in Agriculture. 69, 112-115.
- Morimoto, T., Purwanto, W., Suzuki, J. & Hashimoto, Y. (1997). Optimization of heat treatment for fruit during storage using neural networks and genetic algorithms. Computers and Electronics in Agriculture. 19, 87-101.
- Mulawka, J. (1996). Expert systems. Warszawa. WNT.
- Nieć, H. (1989). Root vegetables. Warszawa. PWRiL.
- Power, D. J. (2014, August). Decision Support Systems Glossary. Retrieved May 17, 2023, from https://DSSResources.COM/glossary.
- Robak, J. & Wiech, K. (1998). Vegetable diseases and pests. Kraków: Plantpress.
- Seidel, M., Breslin, C., Christley, R.M., Gettinby, G., Reid, S.W. & Revie, C.W. (2003). Comparing diagnoses from expert systems and human experts. Agricultural Systems. 76, 527-538.
- Sojak, M. & Głowacki, S. (2005). Applicability of the expert system for decision support in the process of controlling pests of red beet during its vegetation. Inżynieria Rolnicza. 14(74), 323-330.
- Sojak, M. & Trajer, J. (1999). Diagnosis of the condition of vegetables using an expert system. In Trajer J., Methods of computer analysis of the processes undergoing in vegetables during drying and storage (54-59). Warszawa: SGGW Press.
- Sojak, M. (1995). Determination of the mass diffusion coefficient in the process of drying red beet. Unpublished master dissertation, SGGW, Warszawa, Poland.
- Trajer, J., Górnicki, K. & Sojak, M. (1999). A computer analysis system "Warzywo-Bit". In Trajer J., Methods of computer analysis of the processes vegetables undergo during drying and storage (60-71). Warszawa. SGGW Press.
- Weres, J., Kostrzewski, B. & Rudowicz, J. (1999). A computer system supporting the design of the technology of grain drying and storage. In 2nd National Scientific Conference on "The use of information technologies in agriculture”. Poznań.
- Wolniewicz, B. (1997). Tractatus logico-philosophicus, 2nd edition, with amendments: On the Treatise (Wittgenstein, L. 1921). Poland. PWN Scientific Press.
- Woźniak, K. & Kosecka, K. (2020). Expert system. Retrieved May 17, 2023, from https://mfiles.pl/pl/index.php/System_ekspercki.
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-5dc41839-8e4b-41ba-aeb6-9af9003ccdeb