Search Results - (( java implementation phase algorithm ) OR ( knowledge improving learning algorithm ))
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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…All the algorithm for the engine has been developed by using Java script language. …”
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Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof
Published 2019“…These proves that without prior knowledge, the hybrid AI algorithm can self-learn. …”
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An Improvement on Extended Kalman Filter for Neural Network Training
Published 2005“…The inference accuracy, inference duration and training performance of this extended Kalman filter neural network were compared with the standard back-propagation algorithm and an improved version of the back-propagation neural network learning algorithm. …”
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Advancements and challenges in mobile robot navigation: a comprehensive review of algorithms and potential for self-learning approaches
Published 2024“…The findings also insinuate that in the domain of machine learning-based algorithms, integration of knowledge representation with a neuro-symbolic approach has the capacity to improve the accuracy and performance of self-robot navigation training by a significant margin.…”
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Algorithm-program visualization model : An intergrated software visualzation to support novices' programming comprehension
Published 2015“…Nevertheless, the outcome of the learning still remains poor. Through multi-methodological approach, this research aimed to improve the effectiveness of the visualization as the program comprehension tool. …”
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Adaptive learning for lemmatization in morphology analysis
Published 2014“…The method consists three layers of lemmatization process, which incorporate the used of Stanford parser API, WordNet database and adaptive learning technique. The lemmatized words yields from the proposed method are more accurate, thus it will improve the semantic knowledge represented and stored in the knowledge base.…”
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Optimal route checking using genetic algorithm for UiTM's bus services / Tengku Salman Fathi Tengku Jaafar
Published 2006“…Although from human logical thinking, the route can be generated easily but the calculation of checking the route whether it is optimal route or not is difficult and will take long time to be implemented. This research study with the development of the Optimal Route Checking Using Genetic Algorithm system should solve this scenario. …”
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An improvement of back propagation algorithm using halley third order optimisation method for classification problems
Published 2020“…Thus, the proposed methods provide significant improvement and promising result in learning Artificial Neural Networks.…”
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Reliability fuzzy clustering algorithm for wellness of elderly people
Published 2019“…Fuzzy clustering is one of the unsupervised machine learning techniques based knowledge of data analysis that automated or semi-automated analytical model building. …”
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Kernel and multi-class classifiers for multi-floor wlan localisation
Published 2016“…Unlike the classical kNN algorithm which is a regression type algorithm, the proposed localisation algorithms utilise machine learning classification for both linear and kernel types. …”
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13
Evaluations of oil palm fresh fruit bunches maturity degree using multiband spectrometer
Published 2017“…Furthermore, the Lazy-IBK algorithm have been validated to produce the best classifier model, with the machine learning algorithm performance of 65.26%, recall of 65.3%, and 65.4% F-measured as compared to other evaluated machine learning classifier algorithms proposed within the WEKA data mining algorithm. …”
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From Employees to Entrepreneurs: A Qualitative Exploration of Career Transitions in Ghana
Published 2025“…Internalisation of knowledge in KMS was represented through the learning analytics function, followed by an automatic recommendation system to improve knowledge. …”
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Industry 5.0 and Education 5.0: Transforming Vocational Education through Intelligent Technology
Published 2024“…By analyzing the research gaps in personalized learning paths, emotion-driven learning, crossdisciplinary integration, and long-term learning behavior analysis, the paper proposes four improved algorithms: the adaptive learning path generation algorithm, the emotion-driven personalized learning algorithm, the cross-disciplinary knowledge graph algorithm, and the long-term learning behavior prediction algorithm. …”
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An Artificial Intelligence-Based Knowledge Management System for Outcome-Based Education Implementing in Higher Education Institutions
Published 2025“…Internalisation of knowledge in KMS was represented through the learning analytics function, followed by an automatic recommendation system to improve knowledge. …”
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Optimisation of fed-batch fermentation process using deep reinforcement learning
Published 2023“…Fed-batch fermentation process has always been a challenge for optimisation because it is highly non-linear and complex. Deep reinforcement learning is a self-learning algorithm through trial and error and experience, without any prior knowledge. …”
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Ensemble-based machine learning algorithms for classifying breast tissue based on electrical impedance spectroscopy
Published 2020“…The application of artificial intelligence techniques (e.g., machine learning and deep learning) in medical science is becoming increasingly important for intelligently transforming all available information into valuable knowledge. …”
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Sentiment mining using immune network algorithm /Raja Muhammad Hafiz Raja Kamarudin
Published 2012“…The results obtained by utilizing Immune Network in sentiment mining are not very impressive compared to other Machine Learning algorithms. The algorithms can be improved furthermore by including other disciplines such as Natural Language Processing (NLP) or others. …”
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Image classification of Aedes mosquitoes using transfer learning / Zetty Ilham Abdullah
Published 2021“…The advancement and rapid growth of machine learning field should not overlook this issue. Transfer learning concept in machine learning has been shown to improve learning of the targeted task by extending the original algorithm with knowledge gathered from the initial training to improve the performance of new model. …”
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