Using Fuzzy Logic Evaluation of Academic Performance of Students

Using Fuzzy Logic Evaluation of Academic Performance of Students

Using Fuzzy Logic Evaluation of Academic Performance of Students management report in PHP. Fuzzy Inference System for student academic performance evaluation is based on Fuzzy Logic Techniques (FLT). In this system student performance depends on exam paper results and it is evaluated only as success or failure. The study proposes a new performance evaluation method based on the Fuzzy Logic System (FLS). The study proposes a new evaluation method to find a performance of students results based an FLS and also compared with the Classical Method (CL). This is one of the best PHP project on Using Fuzzy Logic Evaluation of Academic Performance of Students. You can download best PHP project on and report on Using Fuzzy Logic Evaluation of Academic Performance of Students. Click here to get complete php projects lists.

Students’ performance based on organizing technique at Monomania Substandard University in the Department of Statistics was carried out using FLT and it was compared with the CL. You can get report on Using Fuzzy Logic Evaluation of Academic Performance of Students. Twenty students took part for the statistical course were considered as study samples. Several approaches using FLT have been proposed a practical method for evaluating student academic performance and compared with existing statistical method. In this paper, evaluation of the results showed variations between the CL and FLMs. You can download PHP project on Using Fuzzy Logic Evaluation of Academic Performance of Students easily.

Conclusion

Using Fuzzy Logic Evaluation of Academic Performance of Students management report in php.The t-test is conducted using MS Excel. As per value of t test we cannot reject the null hypothesis that two results are similar as p-value of test statistics is 0.927( < 0.975) and the t-statistic is -0.09, which does not fall into the rejection region. In other words, we accept the null hypotheses that means conventional result is equal to the mean fuzzy system result with 95% confidence level. This shows that that the expert system can provide the same results as conventional method. Therefore one can apply computer based Fuzzy System Approach in plane of time consuming conventional method.

However, in some cases, the variations in results from fuzzy system have been observed for some students who have same result through conventional method. It was due the difference in their attendance which shows that expert system incorporates input attendance effectively. On the contrary in the conventional system, for a regular course, a student must have mandatory attendance failing to which the student may not be allowed to appear in exams. This shows that the expert system provides flexibility to the inflexible conventional system which is greatly required in present age of technology.

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