Search Results - (( variable education data algorithm ) OR ( java adaptation optimization algorithm ))

Parallel distributed genetic algorithm development based on microcontrollers framework by Krishnan P.S., Kiong T.S., Koh J.

Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions by Saraswati, Galuh Wilujeng

“…The project has also implemented the optimization process onto the proposed ANFIS model through the hybrid of Genetic Algorithm on the fuzzy membership function of the ANFIS model. …”
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Improved Variable Neighbourhood Descent (VND) to Solve Universiti Malaysia Sarawak (UNIMAS) Course Timetabling Problem by Mei Ching, Chen

“…The improved algorithm was tested on real-world data instances (in semesters 1 and 2 of 2019/2020) at the FCSIT, UNIMAS. …”
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Analyzing students records to identify patterns of students' performance by Hoe A.C.K., Ahmad M.S., Hooi T.C., Shanmugam M., Gunasekaran S.S., Cob Z.C., Ramasamy A.

“…Consequently, the ability to predict a student's performance could be useful in many ways to stakeholders of higher education institutions. This paper discusses the data mining technique used to identify the significant variables that affects and influences the performance of undergraduate students. …”

Harmony Search algorithm-based gasoline consumption modeling for Indonesia by Anggarani, Riesta, Watada, Junzo

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Prediction of electronic cigarette and vape use among Malaysian: decision tree analysis by Kartiwi, Mira, Ab Rahman, Jamalludin, Nik Mohamed, Mohamad Haniki, Draman, Samsul, Ab Rahman, Norny Syafinaz

“…Methods: The dataset was extracted from the National Electronic Cigarette Survey (NECS) 2016.A total of 4,288 responses were collected. The collected data was used to build and verified the model. Eight demographics variables (i.e., age, gender, race, religion, residence (urban/rural), marital, occupation and education) and twenty variables on perception of ECV were included as predictor variables. …”
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Empowering Industry 5.0: Nurturing STEM tertiary education and careers through additional mathematics by Chuan, Zun Liang, Abraham Lim, Bing Sern, Tan, Chek Cheng, David Lau, King Luen, Japashov, Nursultan, Tan, Ee Hiae

“…The proposed modified stacked AI predictive algorithm shows superior accuracy to benchmark algorithms. …”
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Predicting students’ STEM academic performance in Malaysian secondary schools using educational data mining by Termedi @ Termiji, Mohammad Izzuan

“…Data mining has been widely applied in educational area recently and it is commonly called Educational Data Mining (EDM). …”
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Technical efficiency performance of Malaysian public research universities: Fuzzy data envelopment analysis / Saber Abdelall Mohamed Ahmed by Saber Abdelall, Mohamed Ahmed

“…Secondly, while DEA model requires precise input and output data of HEIs, this study utilizes the QS World University Ranking research output indicators as the output variables of the Fuzzy DEA model. …”
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Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud by Shariff, S. Sarifah Radiah, Hud, Hady

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Assessment and Evaluation of Different Machine Learning Algorithms for Predicting Student Performance by Alsariera Y.A., Baashar Y., Alkawsi G., Mustafa A., Alkahtani A.A., Ali N.

Examining the potential of machine learning for predicting academic achievement: A systematic review by Nazir, M., Noraziah, Ahmad, Rahmah, M., Sharma, Aditi

“…Predicting student academic performance is a critical area of education research. Machine learning (ML) algorithms have gained significant popularity in recent years. …”
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Examining the potential of machine learning for predicting academic achievement: A systematic review by Nazir, M., Noraziah, Ahmad, Rahmah, M., Sharma, Aditi

“…Predicting student academic performance is a critical area of education research. Machine learning (ML) algorithms have gained significant popularity in recent years. …”
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Characteristics of electronic cigarette and vape users in Malaysia: Lessons from decision tree analysis by Kartiwi, Mira, Nik Mohamed, Mohamad Haniki, Ab Rahman, Jamalludin, Draman, Samsul, Ab Rahman, Norny Syafinaz

“…Several predictor variables included in this study were: seven demographics variables (i.e., age, gender, race, residence, marital, occupation and education) and twenty variables on the perception of ECV use. …”
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Neighbour-based on-demand routing algorithms for mobile ad hoc networks by Ejmaa, Ali Mohamed E.

“…In terms of the applications, The DCFP is more suitable to be used for education applications, while the SNBR is a good algorithm designed to be used for rescue system as data and energy is the main concern. …”
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Academic Achievement Prediction Model Using Neural Networks by Normaziah, Abdul Rahman

“…A neural network technique, using Multi Layer Perceptron (MLP) and back propagation algorithm was employed. A total of 248 data samples from Information Technology and Multimedia Diploma students were collected, trained and tested using this model. …”
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An application of predicting student performance using kernel k-means and smooth support vector machine by Sajadin, Sembiring

“…This studyshowedthat the kernel methodhasa capabilityas data mining technique on educational data mining. …”
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Optimizing decentralized exam timetabling with a discrete whale optimization algorithm by Emily Sing Kiang Siew, San nah sze, Say leng goh

“…This paper presents a novel discrete Whale Optimization Algorithm approach, integrating the strengths of population-based and local-search algorithms for addressing the examination timetabling problem, a significant challenge many educational institutions face. …”
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Optimizing Decentralized Exam Timetabling with a Discrete Whale Optimization Algorithm by Emily Siew, Sing Kiang, Sze, San Nah, Goh, Say Leng

“…This paper presents a novel discrete Whale Optimization Algorithm approach, integrating the strengths of population-based and local-search algorithms for addressing the examination timetabling problem, a significant challenge many educational institutions face. …”
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Determining malaria risk factors in Abuja, Nigeria using various statistical approaches by Segun, Oguntade Emmanuel

“…Data collected were used for the multilevel analysis, Markov Chain Monte Carlo (MCMC) simulation via WinBUGS algorithm and influence diagrams for BBNs. …”
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