Type-II Fuzzy Decision Support System for Fertilizer
Type-II fuzzy sets are used to convey the uncertainties in the membership function of type-I fuzzy sets. Linguistic information in expert rules does not give any information about the geometry of the membership functions. These membership functions are mostly constructed through numerical data or ra...
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2014/695815 |
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| author | Ather Ashraf Muhammad Akram Mansoor Sarwar |
| author_facet | Ather Ashraf Muhammad Akram Mansoor Sarwar |
| author_sort | Ather Ashraf |
| collection | DOAJ |
| description | Type-II fuzzy sets are used to convey the uncertainties in the membership function of type-I fuzzy sets. Linguistic information in expert rules does not give any information about the geometry of the membership functions. These membership functions are mostly constructed through numerical data or range of classes. But there exists an uncertainty about the shape of the membership, that is, whether to go for a triangle membership function or a trapezoidal membership function. 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. The output of the fuzzy inference engine, which is in the form of interval value type-II fuzzy sets, reduced to an interval type-I fuzzy set, defuzzifies it to a crisp value and generates a spatial surface of fertilizers. This spatial surface shows the spatial trend of the required amount of fertilizer needed to cultivate a specific crop. The complexity of our algorithm is O(mnr), where m is the height of the raster, n is the width of the raster, and r is the number of expert rules. |
| format | Article |
| id | doaj-art-82aa5c93aa374add96d2283e54f4374f |
| institution | Kabale University |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-82aa5c93aa374add96d2283e54f4374f2025-02-03T05:52:15ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/695815695815Type-II Fuzzy Decision Support System for FertilizerAther Ashraf0Muhammad Akram1Mansoor Sarwar2Punjab University College of Information Technology, University of the Punjab, Old Campus, Lahore 54000, PakistanDepartment of Mathematics, University of the Punjab, New Campus, Lahore 54590, PakistanPunjab University College of Information Technology, University of the Punjab, Old Campus, Lahore 54000, PakistanType-II fuzzy sets are used to convey the uncertainties in the membership function of type-I fuzzy sets. Linguistic information in expert rules does not give any information about the geometry of the membership functions. These membership functions are mostly constructed through numerical data or range of classes. But there exists an uncertainty about the shape of the membership, that is, whether to go for a triangle membership function or a trapezoidal membership function. 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. The output of the fuzzy inference engine, which is in the form of interval value type-II fuzzy sets, reduced to an interval type-I fuzzy set, defuzzifies it to a crisp value and generates a spatial surface of fertilizers. This spatial surface shows the spatial trend of the required amount of fertilizer needed to cultivate a specific crop. The complexity of our algorithm is O(mnr), where m is the height of the raster, n is the width of the raster, and r is the number of expert rules.http://dx.doi.org/10.1155/2014/695815 |
| spellingShingle | Ather Ashraf Muhammad Akram Mansoor Sarwar Type-II Fuzzy Decision Support System for Fertilizer The Scientific World Journal |
| title | Type-II Fuzzy Decision Support System for Fertilizer |
| title_full | Type-II Fuzzy Decision Support System for Fertilizer |
| title_fullStr | Type-II Fuzzy Decision Support System for Fertilizer |
| title_full_unstemmed | Type-II Fuzzy Decision Support System for Fertilizer |
| title_short | Type-II Fuzzy Decision Support System for Fertilizer |
| title_sort | type ii fuzzy decision support system for fertilizer |
| url | http://dx.doi.org/10.1155/2014/695815 |
| work_keys_str_mv | AT atherashraf typeiifuzzydecisionsupportsystemforfertilizer AT muhammadakram typeiifuzzydecisionsupportsystemforfertilizer AT mansoorsarwar typeiifuzzydecisionsupportsystemforfertilizer |