DESIGN AND IMPLEMENTATION OF A WEBBASED UNIVERSITY ADMISSION AND PLACEMENT NEURAL NETWORK MODEL

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dc.contributor.authorAIGBE, PATIENCE ERINMA
dc.date.accessioned2014-02-21T10:15:58Z
dc.date.available2014-02-21T10:15:58Z
dc.date.issued2008-08
dc.descriptionA THESIS SUBMITTED TO THE POSTGRADUATE SCHOOL IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE AWARD OF THE DEGREE OF MASTER OF SCIENCE IN COMPUTER SCIENCE DEPARTMENT OF MATHEMATICS FACULTY SCIENCES AHMADU BELLO UNIVERSITY ZARIA NIGERIA. AUGUST, 2008en_US
dc.description.abstractEvery year the number of applicants seeking admission into Nigerian Universities increases by leaps and bounds although the Universities lack the commensurate facilities to meet the challenges of admitting the high number of applicants. For this reason, the admission officers have to manually evaluate every candidate’s data against the set admission requirements to screen the applicants in order to select the number of candidates that their universities can accommodate. The procedures involved are very cumbersome, time consuming and prone to a lot of human errors and irregularities. Many candidates miss out on the admission every year, and the most painful aspect of this manual process is that many who are not qualified for a particular course end up being given placement into such courses while the more qualified ones are left out. Consequently, for lack of aptitude for the course, the students struggle through and many even resort to cheating their way through examinations and then graduate out of the Universities ill-equipped for the job market and the society. On the other hand, some of the less fortunate but qualified ones who are not given University admission year after year, become so frustrated over time and end up in hideous lifestyles. Whichever way, the society suffers and national growth is hindered. In this work, a web-based model was designed to considerably take care of the above problems. The system was developed to provide a time-efficient, detailed and unbiased automated procedure for selecting the most qualified candidates for admission into universities, and ensure that qualified candidates, who fail to meet the requirements for a particular course, are automatically placed into other courses for which they meet the admission requirements and where vacancies exist, using neural network model. The model also provides an avenue for students self-screening admission system. The system design, implementation and results are presented in chapter four. The implementation was based on AMP (Apache, MySQL, and PHP) open source solutions.en_US
dc.identifier.urihttp://hdl.handle.net/123456789/2289
dc.language.isoenen_US
dc.subjectDESIGNen_US
dc.subjectIMPLEMENTATION OF A WEBen_US
dc.subjectWEBBASED UNIVERSITY ADMISSIONen_US
dc.subjectWEBBASED UNIVERSITY ADMISSIONen_US
dc.titleDESIGN AND IMPLEMENTATION OF A WEBBASED UNIVERSITY ADMISSION AND PLACEMENT NEURAL NETWORK MODELen_US
dc.typeThesisen_US
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