Muhadith: A Cloud Based Distributed Expert System for Classification of Ahadith

2012 ◽  
Author(s):  
Kashif Bilal ◽  
Sajjad Mohsin
Keyword(s):  
Expert System

Numerical classification of French vegetation of Carici caryophylleae – Genistetea lobelii J.-C. Klein 1972

2021 ◽  
Vol 42 ◽  
pp. e68062
Author(s):  
Pauline Delbosc ◽  
Mathieu Le Dez ◽  
Jean-Bernard Bouzillé ◽  
Kevin Cianfaglione ◽  
Frédéric Bioret
Keyword(s):  
Expert System ◽  
Dominant Species ◽  
Numerical Classification ◽  
Distribution Map ◽  
Diagnostic Species ◽  
Plant Associations ◽  
Formal Definitions ◽  
Twinspan Classification ◽  
New Association

Carici-Genistetea lobelii Klein 1972 corresponds to cyrno-sardinian oromediterranean cushion scrub and related grasslands. In France, this class is only present in Corsica and the syntaxonomic scheme is debated among phytosociologists. The aim of this paper is to highlight the main plant associations of Carici-Genistetea lobelii Klein 1972 and to define the diagnostic species for each phytosociological unit. We compiled 519 vegetation plots and we applied EuropeanVegetationChecklist expert system for the classes of European vegetation to retain only vegetation plots belonging to Carici-Genistetea lobelii. We obtained a dataset with 189 vegetation plots and we classified them with Modified TWINSPAN classification. Our analyses recognized 6 plant associations and 3 sub-associations already described in the literature; and to describe a new alliance corresponding to the supra-mediterranean vegetations (Genistion salzmannii), a new association (Brimeuro fastigiatae-Juniperetum nanae) and its sub-association (alnetosum suaveolentis). For each of them, we identified diagnostic, constant and dominant species and produced their distribution map. Formal definitions were then written for each phytosociological unit (from subassociation to class) and grouped in an expert system to automatically classify the vegetations of Carici-Genistetea lobelii.

scholarly journals Defect characterization, diagnosis and repair of wood flooring based on a field survey

2018 ◽  
Vol 68 (329) ◽  
pp. 149 ◽  
Author(s):  
A. Delgado ◽  
C. Pereira ◽  
J. De Brito ◽  
J. D. Silvestre
Keyword(s):  
Expert System ◽  
Field Survey ◽  
Diagnostic Methods ◽  
Defect Characterization ◽  
Statistical Characterization ◽  
Affected Area ◽  
Wood Flooring ◽  
Repair Techniques

A statistical characterization of defects in 35 buildings and 98 wood floorings (softwood and hardwood floors, and laminated and engineered wood floors), their diagnostic methods and repair solutions is presented. An expert system for inspecting wood flooring, comprising the classification of defects, their most probable causes, diagnostic methods and repair techniques, was used. Results include age, affected area, severity and frequency of defects and their main causes, as well as appropriate diagnostic methods, preventive and curative repair solutions most prescribed and the most significant correlations. Scratches were detected in more than five sixths of the sample, highly associated with exterior mechanical actions, and with an inadequate finishing layer. Wearing of the finishing layer was detected in a quarter of the inspected floorings. Accordingly, the application of a suitable finishing layer and, alternatively, its replacement are the most prescribed repair techniques.

Expert system classification of urban land use/cover for Delhi, India

2008 ◽  
Vol 29 (15) ◽  
pp. 4405-4427 ◽  
Author(s):  
Elizabeth A. Wentz ◽  
David Nelson ◽  
Atiqur Rahman ◽  
William L. Stefanov ◽  
Shoursaseni Sen Roy
Keyword(s):  
Land Use ◽  
Expert System ◽  
Urban Land ◽  
Urban Land Use

A Fuzzy–Expert System For Classification Of Short Duration Voltage Disturbances

2012 ◽  
Author(s):  
Ghafour Amouzad Mahdiraji ◽  
Azah Mohamed
Keyword(s):  
Expert System ◽  
Power Quality ◽  
Short Duration ◽  
Automated Detection ◽  
Voltage Sag ◽  
Fuzzy Expert System ◽  
Correct Classification Rate ◽  
Classification Rate ◽  
Fast Fourier Transform Analysis

Satu aspek penting dalam penilaian kualiti kuasa adalah pengesanan dan pengkelasan gangguan kualiti kuasa secara automatik yang memerlukan penggunaan teknik kepintaran buatan. Kertas kerja ini membentangkan penggunaan sistem pakar-kabur untuk pengkelasan gangguan voltan jangka masa pendek yang termasuk lendut voltan, ampul dan sampukan. Untuk memperolehi sifat unik bagi gangguan voltan, analisis jelmaan Fourier pantas dan teknik purataan punca min kuasa dua digunakan untuk menentukan parameter gangguan seperti tempoh masa, magnitud voltan pmk maksimum dan minimum. Berasaskan pada parameter ini, sebuah sistem pakar–kabur telah dibangunkan dengan mengset aturan kabur yang menimbangkan lima masukan dan tiga keluaran. Sistem ini direka bentuk untuk mengesan dan mengkelaskan tiga jenis gangguan voltan tempoh masa pendek dengan menentukan sama ada gangguan adalah gangguan ketika, gangguan seketika dan bukan gangguan lendut, ampul dan sampukan. Untuk mengesahkan kejituan sistem yang dicadangkan, ia telah diuji dengan gangguan voltan yang diperolehi dari pengawasan. Keputusan ujian menunjukkan bahawa sistem pakar–kabur yang dibangunkan telah memberikan kadar pengkelasan yang betul sebanyak 98.4 %. Kata kunci: Kualiti kuasa, sistem pakar–kabur, lendut, ampul dan sampukan One of the important aspects in power quality assessment is automated detection and classification of power quality disturbances which requires the use of artificial intelligent techniques. This paper presents the application of fuzzy–expert system for classification of short duration voltage disturbances which include voltage sag, swell and interruption. To obtain unique features of the voltage disturbances, fast Fourier transform analysis and root mean square averaging technique are utilized so as to determine the disturbance parameters such as duration, maximum and minimum rms voltage magnitudes. Based on these parameters, a fuzzy-expert system has been developed to set the fuzzy rules incorporating five inputs and three outputs. The system is designed for detecting and classifying the three types of short duration voltage disturbances, so as to determine whether the disturbance is instantaneous, momentary and non sag, swell and interruption. To verify the accuracy of the proposed system, it has been tested with recorded voltage disturbances obtained from monitoring. Tests results showed that the developed fuzzy–expert system gives a correct classification rate of 98.4 %. Key words: Power quality, fuzzy–expert system, sag, swell and interruption.

Expert system support using a Bayesian belief network for the classification of endometrial hyperplasia

2002 ◽  
Vol 197 (3) ◽  
pp. 403-414 ◽  
Author(s):  
M. L. Morrison ◽  
W. G. McCluggage ◽  
G. J. Price ◽  
J. Diamond ◽  
M. R. M. Sheeran ◽  
...  
Keyword(s):  
Expert System ◽  
Endometrial Hyperplasia ◽  
Bayesian Belief Network ◽  
System Support ◽  
Belief Network
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