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https://www.sciencedirect.com/science/article/pii/S0168169911001451
A fuzzy decision support system was designed and implemented in this work, proposing a way of dealing with the uncertainty of natural and anthropogenic resources in order to manage nitrogen fertilizing practices.Cited by: 25
https://www.researchgate.net/publication/241082767_Decision_support_system_for_nitrogen_fertilization_using_fuzzy_theory
In this paper, the design and application of a fuzzy decision support system, concerning site specific nitrogen fertilization, is described. The system uses …
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4032872/
In this paper we use a type-II fuzzy set to overcome this uncertainty, and develop a fuzzy decision support system of fertilizers based on a type-II fuzzy set. This type-II fuzzy system takes cropping time and soil nutrients in the form of spatial surfaces as input, fuzzifies it using a type-II fuzzy membership function, and implies fuzzy rules on it in the fuzzy inference engine.Cited by: 5
https://core.ac.uk/display/38446845
In this paper, the design and application of a fuzzy decision support system, concerning site specific nitrogen fertilization, is described. The system uses an easy but efficient way of solving the nitrogen equation under agricultural conditions and is based on knowledge elicitation and fuzzy logic methodologies. More specifically, the system is composed of two parts; a knowledge base and an analytical modular part which simulates nitrogen balance.Cited by: 25
https://www.hindawi.com/journals/tswj/2014/695815/
In this paper we have introduced a fuzzy decision support system for modeling a spatial surface of fertilizer. This work is an extension of fuzzy system based on type-I fuzzy sets. There was an ambiguity in defining the membership function of nutrients in type-I fuzzy sets.Cited by: 5
https://www.deepdyve.com/lp/elsevier/decision-support-system-for-nitrogen-fertilization-using-fuzzy-theory-iOLo009qT0
Sep 01, 2011 · Highlights We developed a fuzzy decision support system which simulates nitrogen balance. It is composed by a knowledge base and by a fuzzy modular part. The system was developed with MATLAB and was applied in cotton fields. A sensitivity analysis of the decision support system was carried out. According to the system’s results, 77.6% of the test sites are over fertilized.
https://link.springer.com/article/10.1007/s00521-014-1639-4
Jun 19, 2014 · Fertilizer is a key input for the agriculture sector. In this article, the spatial surfaces of fertilizers are developed for the wheat crop using a fuzzy decision support system. The algorithm of our system takes soil nutrients and cropping time as input, applies fuzzy logic on the input values, defuzzifies the fuzzy output to crisp value,...Cited by: 6
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