| 000 | 01498cam a2200277 a 4500 | ||
|---|---|---|---|
| 003 | EG-GiCUC | ||
| 008 | 170821s2016 ua dh f m 000 0 eng d | ||
| 040 |
_aEG-GiCUC _beng _cEG-GiCUC |
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| 041 | 0 | _aeng | |
| 049 | _aGift | ||
| 097 | _aM.Sc | ||
| 099 | _aCai01.34.M.Sc.2016.No.O | ||
| 100 | 0 | _aNourhan Ehab Abdelhamid Azab | |
| 245 | 1 | 0 |
_aOn the use of graded propositions in uncertain non-mamotonic reasoning : _bWith an application to plant disease forecast / _cNourhan Ehab Abdelhamid Azab ; Supervised Haythem Ismail |
| 260 |
_aCairo : _bNourhan Ehab Abdelhamid Azab , _c2016 |
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| 300 |
_a116 Leaves : _bchart , facmiles ; _c30cm |
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| 502 | _aThesis (M.Sc.) - Garman University - Faculty of Postgraduate Studies and Scientific Research - Department of Computer Science and Engineering | ||
| 520 | _aMost of the reasoning we perform in our everyday lives typically involves uncertain, possibly contradicting, konwledge. Accordingly, any intelligent system that tries to emulate human reasoning must be able to draw conclusions from ucertian konwledge and uncertain input and resolve contradictions when ther arise. In this thesis, a weighted non-mamotonic logic we refer to as LogAG for reasoning with uncertainty is presented | ||
| 653 | 4 | _aGraded propositions | |
| 653 | 4 | _aPlant disease forecast | |
| 653 | 4 | _aUncertain non-mamotonic reasoning | |
| 700 | 0 |
_aHaythem Ismail , _eSupervisor |
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| 905 |
_aNazla _eRevisor |
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| 905 |
_aShimaa _eCataloger |
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| 942 |
_2ddc _cTH |
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| 999 |
_c62091 _d62091 |
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