[PDF] Top 20 EVALUATION OF STUDENT ACADEMIC PERFORMANCE USING ADAPTIVE NEURO-FUZZY APPROACH

... for evaluation of students’ academic ...work, fuzzy inference models provided an efficient and effective way to evaluate students’ academic per- formance in a quantitative ...of fuzzy ... See full document

... and performance modeling, medical disease diagnosis, stock market forecasting, electric load prediction, supply chain management, network traffic control, image processing and feature extraction, ...comprise ... See full document

... an evaluation of student academic ...a fuzzy logic techniques and fuzzy rule induction approach to obtain user-comprehensible knowledge from historical data to justify any ...the ... See full document

... transform approach and fuzzy- adaptive reduced pulse-coupled neural network (RPCNN) ...the fuzzy membership values, signifying their importance in the conforming input ... See full document

... these neuro-adaptive learning techniques is to provide a method for the fuzzy modelling procedure to learn information about a data set, in order to automatically compute the membership function ... See full document

... modeling approach based on large-scale climate indices by using the adaptive neuro-fuzzy inference system (ANFIS), the M5P model tree and the multilayer perceptron ...signals ... See full document

... This project will be carried out in two semesters. The first part of the project is done in the first semester where the understandings of literature review and methodology that will be used are done. Gathering ... See full document

... modelled using a neural network (Farkas et ...the performance of a continuous fluidized bed ...modelled using ANN and empirical mathematical ...seven performance indices based on the three ... See full document

... This approach, nevertheless, doesn’t insure that students have attained the qualifications needed for the after ...new approach which relies on what the student learns rather than what he/she have ... See full document

... the fuzzy logic approach on the educational system lead to enhance the evaluation techniques of students so that better results can be ...the performance improvement in result ...the ... See full document

... a fuzzy inference system (FIS) whose membership function parameters are tuned using either a backpropagation algorithm alone, or in combination with a least squares type o f ...allows fuzzy systems ... See full document

... and evaluation of different versions of neuro-fuzzy model for prediction of spike discharge ...variation using first spike latency and frequency-following ...cat. Adaptive ... See full document

... fusion using the combination of wavelet transform and adaptive neuro fuzzy logic is ...with fuzzy and neuro fuzzy logic approach along with the quality ... See full document

... current limiters, and the placement of FACTS devices [2]. Power systems exhibit various modes of oscillation due to interactions among system components. Most of these oscillations are generally associated with ... See full document

... conditions (e. g solar irradiation and temperature). So it is necessary to couple the PV array with a boost converter. More over our system is designed in such a way that with variation in load, the change in input ... See full document

... used adaptive fuzzy inference methods for this task in continuous double auctions [5] and the Trading Agent Competition ...the fuzzy rules was limited. To rectify this, here we exploit fuzzy ... See full document

... of fuzzy techniques in image noise reduction processing is a promising research field ...[5]. Fuzzy techniques have already been applied in several domains of image processing, ...These fuzzy ... See full document

... The end product will have the ability to accept or reject a job applicant based on two factors the requirements of the company should match the skills mentioned in the applicants CV and the other factor is the test ... See full document

... Prediction will provide a powerful tool for managers to be more successful in the long and short term planning for their organization. Prediction can be done in two ways: it can either be the result of deduction and ... See full document

... the neuro-fuzzy network and the mixture process is implemented by the fuzzy inference mechanism of the neuro- fuzzy ...The neuro-fuzzy network is a first order Sugeno type ... See full document