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Article

Comparison of Three Computational Approaches for Tree Crop Irrigation Decision Support

1
Faculty of Automatic Control and Computers, University Politehnica of Bucharest, 060042 Bucharest, Romania
2
Department of Agriculture, Hellenic Mediterranean University, 71410 Heraklion, Greece
3
LANDCO S.A., 15122 Maroussi, Greece
*
Author to whom correspondence should be addressed.
Mathematics 2020, 8(5), 717; https://doi.org/10.3390/math8050717
Received: 30 March 2020 / Revised: 13 April 2020 / Accepted: 15 April 2020 / Published: 3 May 2020
(This article belongs to the Special Issue Computational Intelligence)
This paper explores methodologies for developing intelligent automated decision systems for complex processes that contain uncertainties, thus requiring computational intelligence. Irrigation decision support systems (IDSS) promise to increase water efficiency while sustaining crop yields. Here, we explored methodologies for developing intelligent IDSS that exploit statistical, measured, and simulated data. A simple and a fuzzy multicriteria approach as well as a Decision Tree based system were analyzed. The methodologies were applied in a sample of olive tree farms of Heraklion in the island of Crete, Greece, where water resources are scarce and crop management is generally empirical. The objective is to support decision for optimal financial profit through high yield while conserving water resources through optimal irrigation schemes under various (or uncertain) intrinsic and extrinsic conditions. Crop irrigation requirements are modelled using the FAO-56 equation. The results demonstrate that the decision support based on probabilistic and fuzzy approaches point to strategies with low amounts and careful distributed water irrigation strategies. The decision tree shows that decision can be optimized by examining coexisting factors. We conclude that irrigation-based decisions can be highly assisted by methods such as decision trees given the right choice of attributes while keeping focus on the financial balance between cost and revenue. View Full-Text
Keywords: DSS; multicriteria; fuzzy logic; decision trees; ID3; irrigation management; olive trees DSS; multicriteria; fuzzy logic; decision trees; ID3; irrigation management; olive trees
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MDPI and ACS Style

Christias, P.; Daliakopoulos, I.N.; Manios, T.; Mocanu, M. Comparison of Three Computational Approaches for Tree Crop Irrigation Decision Support. Mathematics 2020, 8, 717. https://doi.org/10.3390/math8050717

AMA Style

Christias P, Daliakopoulos IN, Manios T, Mocanu M. Comparison of Three Computational Approaches for Tree Crop Irrigation Decision Support. Mathematics. 2020; 8(5):717. https://doi.org/10.3390/math8050717

Chicago/Turabian Style

Christias, Panagiotis, Ioannis N. Daliakopoulos, Thrassyvoulos Manios, and Mariana Mocanu. 2020. "Comparison of Three Computational Approaches for Tree Crop Irrigation Decision Support" Mathematics 8, no. 5: 717. https://doi.org/10.3390/math8050717

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