Intelligent Techniques for Prediction of Engineering Colleges After XII

Introduction

Every year, lakhs of students passes the XII class in India. There are only few thousand students who are sure about their future goals. Colleges are not only a place to study but also helps the student to overcome the issues arouse at the corporate world environment. A good college is one which not only has good academic environment but also excels in extracurricular activities. A good overall environment of colleges prepares the student for better future which also helps to improve the society. Thus, in the competitive world students are worried about their colleges after schooling to choose the appropriate college.

Predicting a college on scholastic basis was a history, with more and more involvement in extra-curricular activities these days students wants college which promotes their personality development and also gives them a platform to develop their skills. The basic idea behind this research is to predict the colleges using intelligent techniques. Intelligent system for college prediction requires is to study different types of students and choices of the student for opting the colleges. The selection of various colleges depends on the various parameters such as courses offered, college structure, fee structure etc. In this particular request and understudies generally pick those streams for designing in which more grounds arrangement happened. Because of interest of the understudies towards building, the opposition for admission to prime designing establishment has turned out to be exceptionally mind boggling. The problem in the process of a discovering knowledge from data, in the field of educational data mining, is to identify a representative set of data, so that a classification model will be constructed. There is a lack of data on extra-curricular activities of students. Today, more and more students are involved in extra-curricular activities, thus this parameter should also be taken into consideration for college prediction. Currently College Prediction Systems in India uses only scholastic scores to predict the college; whereas other factors such as family income, extra-curricular activities, fee structure etc. were ignored. Findings show that extracurricular activities also play a vital role in knowing and taking admission in the college Hence this research work proposes an intelligent technique for College Prediction is to specifically provide students a platform which will help them to form their profile and match it to the colleges based on their academics and extra-curricular qualifications.

Data mining techniques and machine learning techniques have been used to predict the performance of a student. This paper uses a Mamdani inference method to predict the college of a student basis of score of extra-curricular and scholastic achievements. A weighted fuzzy decision tree is also proposed to calculate the performance score. This score is used to help to predict the appropriate college to student. Survey work demonstrates that grouping is the effective technique among the current strategies. The data collected from the survey via google form. A statistical method is used to analyze the result of survey. To validate the result of weighted fuzzy decision tree, an adaptive neuro fuzzy approach is applied. Further sections explain the related work, methodology and result analysis’s for prediction of appropriate college to the student.