Search Results - (( knowledge negative selection algorithm ) OR ( java application customization algorithm ))
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1
Lexicon-based and immune system based learning methods in Twitter sentiment analysis
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2
Integrated Mobile Spain Model Using Artificial Immune System Algorithms
Published 2024Proceedings Paper -
3
Enhancing obfuscation technique for protecting source code against software reverse engineering
Published 2019“…The proposed technique can be enhanced in the future to protect games applications and mobile applications that are developed by java; it can improve the software development industry. …”
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4
Web-based expert system for material selection of natural fiber- reinforced polymer composites
Published 2015“…But, the computer oriented materials selection and knowledge-based expert systems are the robust approach in materials selection to handle huge amount of materials of choice. …”
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5
Modelling knowledge transfer of nursing students during clinical placement / Nor Azairiah Fatimah Othman
Published 2017“…This study made an attempt to incorporate knowledge transfer-related variables (articulability of knowledge, credibility of knowledge source, gap of theory-practice, embedded knowledge and environmental uncertainty) into the framework. …”
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Book Section -
6
Design & Development of a Robotic System Using LEGO Mindstorm
Published 2006“…Since the model is built using LEGO bricks, the model is fully customized, in term of its applications, to perform any relevant tasks. …”
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7
Sentiment analysis of customer review for Tina Arena Beauty
Published 2025“…Three machine learning algorithms Naive Bayes, Random Forest, and Support Vector Machine (SVM) were evaluated, and SVM achieved the highest accuracy and was selected as the final classifier. …”
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Student Project -
8
Determining malaria risk factors in Abuja, Nigeria using various statistical approaches
Published 2018“…Using BBNs, different learning strategies were explored and compared with k-fold using negative entropy loss. The optimal model based on the parsimony principles was obtained from the hill climbing algorithm with score metrics. …”
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