Evaluation of Academic Performance of Students with Fuzzy Logic

Evaluation of Academic Performance of Students with Fuzzy Logic

Abstract:

Students’ educational success depends on academic performance evaluation. Traditional methods evaluate students using institute or university exams. This article proposes evaluating performance with fuzzy logic. This method evaluates students’ academic performance using attendance, internal marks, and external marks. Using a fuzzy inference system to evaluate students’ attendance and marks improves accuracy.

Introduction:

Universities value student academic success. Exams measure student performance. Conventional evaluation methods may lack comprehensiveness and accuracy. To assess students’ academic performance more holistically, a fuzzy logic-based performance evaluation method has been proposed.

Objectives:

This project aims to create a fuzzy logic-based academic performance evaluation system. The system uses fuzzy logic to overcome traditional evaluation methods and better represent students’ achievements. Attendance, internal marks, and external marks will determine student academic performance.

Project Details:

Fuzzy logic is used to evaluate academic performance. The project’s main features are listed below.:

1. Data Collection:
   • The system will collect attendance data, internal marks, and external marks for each student.
   • The data will be stored in a database for further processing and analysis.
2. Fuzzy Logic Implementation:
   • Fuzzy logic principles will be applied to evaluate the academic performance of students.
   • The fuzzy inference system will be utilized to handle the uncertainty and imprecision inherent in the evaluation process.
   • Membership functions will be defined for attendance and marks to represent the linguistic variables.
3. Performance Calculation:
   • The system will use the collected data and fuzzy logic rules to calculate the performance of students.
   • Fuzzy inference techniques, such as fuzzy rules and fuzzy logic operators, will be employed to derive accurate results.
4. Result Presentation:
   • Student academic performance will be clearly presented.
   • Reports or graphs can simplify interpretation.

Conclusion:

Fuzzy logic can improve traditional evaluation methods by assessing students’ academic performance. This method incorporates attendance, internal, and external marks to better assess students’ performance. Fuzzy inference systems improve evaluation accuracy and reliability. This project can improve educational institution evaluation systems for students and educators.

Note: Please discuss with our team before submitting this abstract to the college. This Abstract or Synopsis varies based on student project requirements.