Search Results - (( student classification using algorithm ) OR ( using optimization based algorithm ))

High voltage transmission line fault classification based on neural network trained by particle swarm optimization by Zukri, Muhamad Amirul Aizad

“…Every one of these factors then will be tried and thought about by Particle Swarm Optimization (PSO) algorithm to the outcomes got. Extension of simulation carried out by MATLAB with the highlight PSO features and advantages over others algorithms that very reliable, fast and efficient. …”
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Development of classification model between clean water and polluted water based on capacitance properties using Levenberg Marquardt (LM) algorithm of artificial neural network / M... by Mohamad Salehuddin, Mohamad Firdaus

“…The accuracy from the selected most optimized models were 100%. The selected most optimized models were then can be used to classify between clean water and polluted water based on capacitance input.…”
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Multichannel optimization with hybrid spectral- entropy markers for gender identification enhancement of emotional-based EEGs by Al-Qazzaz, Noor Kamal, Sabir, Mohannad K., Mohd Ali, Sawal Hamid, Ahmad, Siti Anom, Grammer, Karl

“…The results show linear and nonlinear features are remarkable neuromarkers for investigating gender-based differences in emotional states. Moreover, the results show significant enhancement in the overall accuracy of classification achieved by using the BGSA optimization algorithm with the proposed hybrid SEA set when compared to individual features. …”
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Optimizing in-car-abandoned children’s sounds detection using deep learning algorithms / Nur Atiqah Izzati Md Fisol by Md Fisol, Nur Atiqah Izzati

“…To address this problem, an optimized in-car-abandoned children's sounds detection model using deep learning algorithms is proposed. …”
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Multilingual Sentiment Analysis From Students Feedback: Optimal Techniques And Resources For Bengali Lingual Data by Mohammad Aman Ullah

Mental Stress Classification Among Higher Education Students In Malaysia From Electroencephalogram (Eeg) Using Convolutional Neural Network With Modified Stochastic Gradient D... by Rashid, Nur Ramizah Ramino

“…This study investigates the classification of mental stress among Malaysian university students using Electroencephalogram (EEG) data and a 1D-Convolutional Neural Network (1D-CNN) optimized with Modified Stochastic Gradient Descent (SGD). …”
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Artificial intelligence to predict pre-clinical dental student academic performance based on pre-university results: a preliminary study by Lestari, Widya, Abdullah, Adilah Syahirah, Ahmad Amin, Afifah Munirah, faridah, Nur, Sukotjo, Cortino, Ismail, Azlini, mohamad ibrahim, mohamad shafiq, Insani, Nashuha, Utomo, Chandra Prasetyo

“…No definitive model stood out as the best algorithm for predicting student academic success in this study.…”
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P300 detection of brain signals using a combination of wavelet transform techniques by Motlagh, Farid Esmaeili

“…In this research the BCI competition data-set has been processed through 5 optimized detection methods. Wavelet transform (WT), student’s two-sample t-statistic (T-Test) and support vector machines (SVM) used in designing the algorithms. …”
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Enhancing teaching and learning through data-driven optimization of servicing code demand and lecturer allocation using WEKA analysis by Rochin Demong, Nur Atiqah, Mohamed Razali, Murni Zarina, Kamaruddin, Juliana Noor, Shamsuddin, Sazwan, Awang, Nor Ain, Kamarudin, Norjuliatie, Wan Othman, Noor Faradilla

“…Attribute selection through Information Gain Attrite Evaluation model highlighted Program Code, Course Code and Type of Course as the strongest predictors of course approval and demand levels. Furthermore, classification using the Random Forest algorithm depicted that a 95.3% accuracy (k=0.768), confirming robust predictive capability in identifying course approval status and demand trends. …”
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Predicting breast cancer using ant colony optimisation / Siti Sarah Aqilah Che Ani by Che Ani, Siti Sarah Aqilah

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Minimizing Classification Errors in Imbalanced Dataset Using Means of Sampling by Khan I., Ahmad A.R., Jabeur N., Mahdi M.N.

Student performance classification using support vector machine (SVM) with polynomical kernel on online student activities / Muhammad Hareez Mohd Zaki ... [et al.] by Mohd Zaki, Muhammad Hareez, Abdul Aziz, Mohd Azri, Sulaiman, Suhana, Hambali, Najidah

“…The purpose of this study is to classify students’ performance by using a polynomial kernel of Support Vector Machine (SVM) on online students’ activities. …”
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Development of I-Complain@META: a complaint management system for FKMT students using naive bayes classification algorithm by Cheah, Jia Ni

“…Development of I-Complain@META: a complaint management system for FKMT students using naive bayes classification algorithm by Cheah, Jia Ni…”
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First Semester Computer Science Students’ Academic Performances Analysis by Using Data Mining Classification Algorithms by Azwa, Abdul Aziz, Fadhilah, Ahmad

“…The prediction model can be used to classify the students so the lecturer can take an early action to improve students’ performance.…”
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Predicting autistic spectrum disorder for toddler using ant colony optimization / Nur Ibtisyam Zafri by Zafri, Nur Ibtisyam

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Backpropagation algorithm for classification problem: academic performance prediction model for UiTM Melaka Mengubah Destini Anak Bangsa (MDAB) program. / Fadhlina Izzah Saman, Nur... by Saman, Fadhlina Izzah, Zainuddin, Nurulhuda, Md Shahid, Khairiyah

“…UiTM Melaka has set one of the Quality Objectives to be achieved for each faculty is to produce at least 65% of full time students graduating with a CGPA of at least 3.00. There is no existing tool to assist faculties in estimating the number of students that can achieve the objective, hence a prediction model using Backpropagation Algorithm is proposed by using a case study of UiTM Bandaraya Melaka Bachelor of Administrative Science students. …”
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Classification of students' performance in computer programming course according to learning style by Norwawi N.M., Abdusalam S.F., Hibadullah C.F., Shuaibu B.M.

Fault classification in transmission line using single layer feed-forward network trained by extreme learning machine / Muhamad Azfar Abd Ghafar by Abd Ghafar, Muhamad Azfar

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Prediction of college student academic performance using data mining techniques. by Abd Jalil, Azura, Mustapha, Aida, Santa, Dzulizah, Zain, Nurul Zaiha, Radwan, Rizalina

“…The classification algorithms used are the Decision Tree, Naïve Bayesian, and Multilayer Perception with the highest classification accuracy by the Naive Bayes algorithm with accuracy of 95.3%. …”
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A comparative analysis of four classification algorithms for university students performance detection by Dipta, Das, Asif Khan, Shakir, Sah Golam, Rabbani, Mostafijur, Rahman, Syamimi Mardiah, Shaharum, Sabira, Khatun, Norasyikin, Fadilah, Khandker, M. Qaiduzzaman, Md. Shariful, Islam, Md. Shohel, Arman

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