Search Results - (( developing function learning algorithm ) OR ( learner generated based algorithm ))

Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool by Nurshafiqa Saffah, Mohd Sharif

“…In future, this research can be an initial work in automating tutorial decisions in an intelligent tutoring system which are able to adapt to the behaviour of the learners based on the detected mental states. Therefore, more relevant information about the students can be provided to the schools and teachers in order to increase the learning impacts.…”
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Meta-Heuristic Algorithms for Learning Path Recommender at MOOC by Son, N.T., Jaafar, J., Aziz, I.A., Anh, B.N.

“…This study proposes a multi-objective optimization model as a knowledge-based recommender. Our model can generate an appropriate learning path for learners based on their background and job goals. …”
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A new hybrid fuzzy ARTMAP and radial basis function neural network with online pruning strategy by Leow S.Y., Wong S.Y., Yap K.S., Yap H.J.

A Reference Based Surface Defect Segmentation Algorithm For Automatic Optical Inspection System by Wong, Ze-Hao

“…This study aims to develop an algorithm for the AOI system to segment and detect surface defects, requiring low processing power and a small number of learning dataset with labelling error resistance. …”
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Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Pr... by Sammen S.S., Ehteram M., Sheikh Khozani Z., Sidek L.M.

“…In this study, we used extreme learning machine (ELM)-multi-kernel least square support vector machine (ELM-MKLSSVM), extreme learning machine (ELM)-LSSVM-polynomial kernel function (PKF) (ELM-LSSVM-PKF), ELM-LSSVM-radial basis kernel function (RBF) (ELM-LSSVM-RBF), ELM-LSSVM-Linear Kernel function (LKF), ELM, and MKLSSVM models to predict water level. …”

Automatic Mind Maps Generation for The Holy Quran by Khedher, Akram M.Z.M., Issa, Hamed, Wasiq, Shafiullah

“…Therefore, the aim of this paper is to develop an algorithm that automatically generate the topics ‎based on the mind map of a set of verses in the Holy Quran. …”
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Hybrid Harmony Search Algorithm with Grey Wolf Optimizer and Modified Opposition-based Learning by Alomoush, Alaa A., Alsewari, Abdulrahman A., Alamri, Hammoudeh S., Aloufi, Khalid, Kamal Z., Zamli

“…Many variants have been developed to cope with this problem and improve algorithm performance. …”
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Particle swarm optimization for neural network learning enhancement by Abdull Hamed, Haza Nuzly

“…Two programs have been developed; Particle Swarm Optimization Feedforward Neural Network (PSONN) and Genetic Algorithm Backpropagation Neural Network (GANN). …”
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Support directional shifting vector: A direction based machine learning classifier by Kowsher, Md., Hossen, Imran, Tahabilder, Anik, Prottasha, Nusrat Jahan, Habib, Kaiser, Zafril Rizal, M Azmi

“…The positional error of the linear function has been modelled as a loss function which is iteratively optimized using the gradient descent algorithm. …”
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Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

“…This paper presents a classification approach on android malware using candidate detectors generated from an unsupervised association rule of Apriori Algorithm. …”
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Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

“…These algorithms can be used successfully in many applications requiring the optimization of a certain multi-dimensional function. …”
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E-history Malaysian secondary school textbook using TF-IDF algorithm and text visualization / Nur Hafizah Mohd Ridzuan by Mohd Ridzuan, Nur Hafizah

“…The objective of the project is to design and develop an E-History Malaysian secondary school textbook system using Term Frequency-Inverse Document Frequency (TF-IDF) algorithm with text visualization and also to test the functionality and usability of the system through a web-based system. …”
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Development of Hybrid Convolutional Neural Network and Radial Basis Function for Autism Spectrum Disorder Classification by Huey Chern, Lim

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Ensemble model of Artificial Neural Networks with randomized number of hidden neurons by Fatai Adesina, Anifowose, Jane, Labadin

“…Ten base learners of the ANN model were created with each using a randomly generated number of hidden neurons. …”
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Evaluation of optimal MLP structure for heart disease diagnosis / Salbiah Ab Hamid by Ab Hamid, Salbiah

“…A transfer function simulation model is developed by using the MATLAB software. …”
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Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

“…An efficient iterative algorithm is developed to optimize the objective function of the proposed algorithm since it is non-smooth and difficult to solve. …”
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Acceleration Strategies For The Backpropagation Neural Network Learning Algorithm by Zainuddin, Zarita

“…In this thesis, factors that govern the learning speed of the backpropagation algorithm are investigated and mathematically analyzed in order to develop strategies to improve the performance of this neural network learning algorithm. …”
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Quantum-Behaved Lightning Search Algorithm to Improve Indirect Field-Oriented Fuzzy-PI Control for im Drive by Hannan M.A., Ali J.A., Mohamed A., Amirulddin U.A.U., Tan N.M.L., Uddin M.N.

Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

“…In order to address the above mentioned challenges, this study is devoted towards the development of a clusterer and a clustering ensemble learning method based on incremental genetic algorithms addressing group unlabeled samples. …”
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RECURSIVE LEARNING ALGORITHMS ON RBF NETWORKS FOR NONLINEAR SYSTEM IDENTIFICATION by CATUR ANDRYANI, NUR AFNY

“…Science and technology development has the tendency of learning from nature where human also try to develop artificial intelligent by imitating biological neuron network which is popularly termed Artificial Neural Network (ANN). …”
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