evaluating student performance using fuzzy inference
Recommend Documents
fuzzy inference methodologies in the performance testing of refrigerators, as an ... software solution has been developed to monitor the change in temperature ...
2 Ningbo Institute of Technology, Zhejiang University, Ningbo, 315100, China. Abstract: View .... where dvi. (iâ[0, 7]) is disparity of eight neighborhood of current block, the current disparity dv is regarded .... Conf on Multimedia and Expo, 2006
In the last years, grammatical inference using recurrent neural network has been a .... The network we propose, Figure 1, consists of ] fuzzy recurrent neurons labelled .... seen yet, acting in the following way: if one sequence of this set is not ..
mechanical failure in electric power transmission lines, under oscillating movement ... data acquisition, wireless communication, transmission lines, MEMS, GPS.
With respect to OSCEs, the authors call for collaborative efforts among consortia schools in concert with the Center for the Advancement of ..... manager. ⢠Charge the âPerformance Committeeâ with the responsibility of acting upon evaluations .
a merchant's website to increase customers' trust when shopping online. .... For the decision maker module, we use all three membership ..... variables should be used by default for the best results; (2) if it is actually possible for a computer.
Sep 4, 2001 ... Tsukamoto Model et cetera. Fuzzy Rules and Fuzzy Reasoning. 5. Motivation.
Fuzzy Reasoning left us with something similar to: Real world:.
for collaboration between expert knowledge and data using FisPro. Serge Guillaume a,* ... terms of accuracy, and the behavior of their inference engine is.
Oct 31, 2018 - ğerlendirilen öğrencinin performans görevi puanının 81.2 (100) olduğu saptanmıştır. ...... ifade edilen düşünce bağlamında, AHP ve TOPSIS'in bütüncül bir yapıda ... lenmesiyle ölçme ve değerlendirmede temsil gücü yüksek olan kriterleri
Michael et al., [2] have discussed .... L. (0,20,40). Medium. M. (20,40,60). High. H. (40,60,80). Very High. VH. (60,80,100) ... Michael L, Seaman JW, Douglas JB,.
inference system (FIS) for teaching staff performance appraisal using Matlab. The research formulates the mappings from factors affecting performance to the ...
Aug 17, 2012 - ATMEL, www.atmel.com/Images/doc2503.pdf. Baturone, I. .... Sulaiman, N., Obaid, Z.A., Marhaban, M.H. and Hamidon,. M.N. (2009).
May 30, 2018 - fundamentally involve a non-linear modeling approach that gives a fairly .... In this study, an adaptive technique called momentum Levenberg-.
Asset Liability Management (ALM) which deals with adjustment of investments with ... [1] In this paper mathematical formulation of the Investment ..... NumMFs=3.
After the original work conducted by Holland (Holland, 1975), GA were developed. These algorithms ..... of 1.3 maybe suitable settings (Carlisle. & Dozier, 2001).
If Input 1 = x and Input 2 = y, then Output is z = ax + by + c. For a zero-order Sugeno model, the output level z is a constant (a=b =0). The output level zi of each ...
form proposed by Charles Peirce : âthe surprising fact .... B(v)â as âthe redder the tomato, the riper it isâ. Sec- ..... [2] Lubbe J.C.A. van der, Backer E., Human-like.
leads to degradation of the network performance by increasing routing loads and ..... mobile ad hoc networks: Issues and challenges", In Performance Tools and.
Aug 11, 2016 - The Earned Value Management (EVM) has been extensively employed in the literature for analysing the schedule and cost performance ...
ISSN : 0976-8491 (Online) | ISSN : 2229-4333 (Print) www.ijcst.com. 36 INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND ... to increase the performance by integrates the best features of ..... Bachelor's degree (B.Tech) with.
Pran Hari Talukdar3. Gauhati University, Guwahati, India. [email protected]. Gauhati University, Guwahati, India. [email protected]. Gauhati ...
may add other sounds such as S3, S4, opening snaps, ejection clicks, splits, murmurs or stenosis into the normal cycle. Feature extraction of PCG initiates from ...
Apr 11, 2013 - sequence is implemented in an open source software, FisPro, made for fuzzy inference system ..... as many fuzzy set centers as linguistic terms, these center ... rized below: 1) Call Fistree, the FisPro fuzzy decision tree, to sort.
cessful operation of multi-megawatt sized wind turbines. However, wind ... adequately sustainable everywhere to build an economical wind farm. The potential ...
evaluating student performance using fuzzy inference
Exam performance. Class Record. Linguistic variable: Exam Performance: Outstanding, Satisfactory, Unsatisfactory. Class Record: Highest, Higher, High, Above ...
EVALUATING STUDENT PERFORMANCE USING FUZZY INFERENCE SYSTEM IN FUZZY ITS FIS_Student INPUT: Exam performance Class Record Linguistic variable: Exam Performance: Outstanding, Satisfactory, Unsatisfactory Class Record: Highest, Higher, High, Above Average, Average, Low, Lower, Lowest
OUTPUT: Student Performance Linguistic variable: Remarkable, Excellent, Proficient, Fair, LessFair, Poor, Very poor, Fail
MEMBERSHIP FUNCTION: Triangular Membership Function
IMPLEMENTATION OF FUZZY LOGIC:
Fig.1: The input and output parameters of proposed system
Fig.2: Membership function for input Class Record
Fig.3: Membership function for input Exam Performance
Fig.4 : Membership function for input Student Performance
Fig.5 : Rules Editor
FUZZY RULES: 1. If (ClassRecord is Outstanding) and (ExamPerformance is high) then (StudentPerformance is Excellent) 2. If (ClassRecord is Unsatisfactory) and (ExamPerformance is Lowest) then (StudentPerformance is Fail) 3. If (ClassRecord is Outstanding) and (ExamPerformance is highest) then (StudentPerformance is Remarkable) 4. If (ClassRecord is Satisfactory) and (ExamPerformance is highest) then (StudentPerformance is Excellent) 5. If (ClassRecord is Unsatisfactory) and (ExamPerformance is highest) then (StudentPerformance is Proficient) 6. If (ClassRecord is Unsatisfactory) and (ExamPerformance is high) then (StudentPerformance is Fair) 7. If (ClassRecord is Satisfactory) and (ExamPerformance is high) then (StudentPerformance is Proficient) 8. If (ClassRecord is Outstanding) and (ExamPerformance is higher) then (StudentPerformance is Remarkable) 9. If (ClassRecord is Satisfactory) and (ExamPerformance is higher) then (StudentPerformance is Excellent) 10. If (ClassRecord is Unsatisfactory) and (ExamPerformance is higher) then (StudentPerformance is Fair) 11. If (ClassRecord is Outstanding) and (ExamPerformance is AbvAvg) then (StudentPerformance is Profficient) 12. If (ClassRecord is Satisfactory) and (ExamPerformance is AbvAvg) then (StudentPerformance is Fair) 13. If (ClassRecord is Unsatisfactory) and (ExamPerformance is AbvAvg) then (StudentPerformance is LessFair) 14. If (ClassRecord is Satisfactory) and (ExamPerformance is Lower) then (StudentPerformance is Poor) 15. If (ClassRecord is Unsatisfactory) and (ExamPerformance is Lower) then (StudentPerformance is VeryPoor) 16. If (ClassRecord is Outstanding) and (ExamPerformance is Lowest) then (StudentPerformance is VeryPoor) 17. If (ClassRecord is Outstanding) and (ExamPerformance is Avg) then (StudentPerformance is Fair) 18. If (ClassRecord is Satisfactory) and (ExamPerformance is Avg) then (StudentPerformance is LessFair) 19. If (ClassRecord is Unsatisfactory) and (ExamPerformance is Avg) then (StudentPerformance is Poor) 20. If (ClassRecord is Outstanding) and (ExamPerformance is Low) then (StudentPerformance is LessFair) 21. If (ClassRecord is Satisfactory) and (ExamPerformance is Low) then (StudentPerformance is Poor)
22. If (ClassRecord is Unsatisfactory) and (ExamPerformance is Low) then (StudentPerformance is VeryPoor) 23. If (ClassRecord is Outstanding) and (ExamPerformance is Lower) then (StudentPerformance is Poor) 24. If (ClassRecord is Satisfactory) and (ExamPerformance is Lowest) then (StudentPerformance is VeryPoor)
Fig.6: Rule Viewer with input and output variables
