Search Results - (( pattern learning algorithm ) OR ( between teaching algorithm ))

Impact of Computational Thinking and Computer Science (CTCS) Teaching Technique at Seleceted Schools in Sarawak : A Qualitative Analysis by Nor Iqbal, Mohd Sait, Noor'ain, Aini, Kartinah, Zen

“…Computational thinking and computer science (CTCS) is an educational approach that involves a four-stage process involving concepts of decomposition, pattern recognition, abstraction, and algorithm that promotes greater levels of thinking. …”
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Current applications of machine learning in dentistry by Ghazali, Ahmad Badruddin, Reduwan, Nor Hidayah, Ibrahim, Roliana

“…Artificial intelligence (AI) is the general description given to computer systems that can perform tasks and mimic the requirement of human intelligence input (Pesapane et al., 2018). Machine learning (ML), a subset of AI was described as an algorithm with the ability to "learn" by identifying patterns in a large dataset (Rowe, 2019). …”
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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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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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Acquisition of context-based word recognition by reinforcement learning using a recurrent neural network by Ahmad Afif, Mohd Faudzi

“…The developed learning system has a 4-layered RNN and it was trained by BPTT method based on teaching signal that was generated by Q-Learning algorithm. …”
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Acquisition of context-based word recognition by reinforcement learning using a recurrent neural network by Ahmad Afif, Mohd Faudzi

“…The developed learning system has a 4-layered RNN and it was trained by BPTT method based on teaching signal that was generated by Q-Learning algorithm. …”
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Bridging Mayer’s cognitive theory of multimedia learning and computational thinking in tackling the cognitive load issues among young digital natives : a conceptual framework by Wan Nor Ashiqin Wan Ali, Wan Ahmad Jaafar Wan Yahaya

“…CT refers to the capacity of learners to systematically tackle unstructured tasks focused on four computing concepts such as decomposition, abstraction, pattern recognition, and algorithmic thinking. The purpose of this paper is to study the relationship between CT and Mayer’s Cognitive Theory of Multimedia Learning (CTML) on the cognitive load of the learners. …”
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Bat Algorithm for Complex Event Pattern Detection in Sentiment Analysis by Kabir Ahmad, Farzana, Kamaruddin, Siti Sakira, Yusof, Yuhanis, Yusoff, Nooraini

“…For learning and predicting the event patterns, dynamic Bayesian network (DBN) with Hidden Markov Model (HMM) and heuristic search learning algorithms have been a popular technique used in which structure learning is trained to classify complex events pattern. …”
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Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

“…There are two general paradigms for pattern recognition classification which are supervised and unsupervised learning. …”
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Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation by Mat Jani H., Lee S.P.

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Mining Indirect Least Association Rule from Students’ Examination Datasets by Zailani, Abdullah, Tutut, Herawan, Noraziah, Ahmad, Rozaida, Ghazali, Mustafa, Mat Deris

“…In addition of decreasing the number of uninteresting rules, the obtained information also can be used by educators as a basis to improve their teaching and learning strategies in the future.…”
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Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

“…In the first and second phases, a threshold fuzzy c-means clustering algorithm as a clusterer and a pattern ensemble learning method based on the incremental genetic-based algorithms are proposed respectively. …”
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Mining Indirect Least Association Rule from Students' Examination Datasets by Zailani, Abdullah, Noraziah, Ahmad, Mustafa, Mat Deris, Rozaida, Ghazali, Herawan, Tutut

“…In addition of decreasing the number of uninteresting rules, the obtained information also can be used by educators as a basis to improve their teaching and learning strategies in the future.…”
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An algorithm for Elliott Waves pattern detection by Vantuch, T., Zelinka, I., Vasant, P.

“…The Random Decision Forest and the Support Vector Machine are the machine learning algorithms employed for this task. The accuracy of trend prediction above 70 proves the relevancy of EW patterns on stock market data as well as the validity of the algorithm as a tool for detection of such patterns. …”
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An algorithm for Elliott Waves pattern detection by Vantuch, T., Zelinka, I., Vasant, P.

“…The Random Decision Forest and the Support Vector Machine are the machine learning algorithms employed for this task. The accuracy of trend prediction above 70 proves the relevancy of EW patterns on stock market data as well as the validity of the algorithm as a tool for detection of such patterns. …”
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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

“…The main objective of this study is to identify the demand patterns and optimizing the lecturer’s contribution by maintaining a class sizes of maximum number of students in each class is 30 and a teaching load of up to 20 credit hours per lecturer. …”
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Medical Image Analysis Using Deep Learning and Distribution Pattern Matching Algorithm by Jaber M.M., Yussof S., Elameer A.S., Weng L.Y., Abd S.K., Nayyar A.

“…Automation; Complex networks; Computational complexity; Deep learning; Image analysis; Medical imaging; Pattern matching; Pixels; Distribution pattern-matching rule; Distribution patterns; Gray wolf-optimized deep convolution network; Gray wolves; Learning patterns; Matching rules; Medical fields; Medical image analysis; Pattern matching algorithms; Pattern-matching; Convolution…”

Financial time series predicting using machine learning algorithms by Tiong, Leslie Ching Ow *

“…Thereafter, Artificial Neural Network (ANN) and Support Vector Machine (SVM) algorithms are implemented separately to train with the trend patterns for predicting the movement direction of financial trends. …”
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Machine learning predictions of stock market pattern using Econophysics approach by Roslan, Nur Nadia Hani, Abdullah, Shahino Mah

“…Hence, this research will be using Monte Carlo Simulation and identify which machine learning algorithm is suitable for predicting stock market patterns. …”
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A Divide-and-Distribute Approach to Single-Cycle Learning HGN Network for Pattern Recognition by Muhamad Amin , Anang Hudaya, Khan, Asad I.

“…Distributed Hierarchical Graph Neuron (DHGN) is a single-cycle learning distributed pattern recognition algorithm, which reduces the computational complexity of existing pattern recognition algorithms by distributing the recognition process into smaller clusters. …”
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