Search Results - (( java application optimisation algorithm ) OR ( based learning from algorithm ))
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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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Web-based expert system for material selection of natural fiber- reinforced polymer composites
Published 2015“…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems
Published 2022“…Teaching learning-based optimization is one of the widely accepted metaheuristic algorithms inspired by teaching and learning within classrooms. …”
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Propose a New Machine Learning Algorithm based on Cancer Diagnosis
Published 2018“…In this review, we focus on the current status of machine learning applications in cancer research, also propose a new algorithm Fast Learning Network to work based on cancer research.…”
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E4ML: Educational Tool for Machine Learning
Published 2003“…There are various types of machine learning algorithms with certain processes taken by the algorithm.In teaching of the machine learning algorithms, such processes need to be explained especially to the beginner in introductory level.This paper discusses the development the tool that addresses the process by certain algorithm to produce a hypothesis or output based on given data.This tool can also be used in teaching and learning purposes.The explanation of processes by the algorithms is demonstrated through simple simulation.The source of the algorithms was adapted from Mitchell book [1] that cover popular algorithms in machine learning for teaching and learning such as Concept Learning, Decision Tree, Bayesian Learning, Neural Networks, and Instance based Learning.The tool also used several classes of Weka (Waikato Environment for Knowledge Analysis) as a basis for the design and implementation of the new tool that focuses on explaining the processes taken by certain algorithm.…”
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A harmony search-based learning algorithm for epileptic seizure prediction
Published 2016“…The proposed harmony search-based learning algorithm is used in the task of epileptic seizure prediction. …”
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Performance of correlational filtering and deep learning based single target tracking algorithms / ZhongMing Liao and Azlan Ismail
Published 2023“…Therefore, reviewing the visual target tracking algorithms based on deep learning from different perspectives is important. …”
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A Reference Based Surface Defect Segmentation Algorithm For Automatic Optical Inspection System
Published 2020“…Results show that the proposed algorithm required a learning dataset size as small as 5 samples and was resistant to learning labelling error up to 50%.…”
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Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection
Published 2020“…The first improvement includes the use of Opposition Based Learning (OBL) at initialization phase of SSA to improve its population diversity in the search space. …”
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Impact learning: A learning method from feature's impact and competition
Published 2023“…Machine learning is the study of computer algorithms that can automatically improve based on data and experience. …”
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Case Slicing Technique for Feature Selection
Published 2004“…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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Impact learning : A learning method from feature’s impact and competition
Published 2023“…Machine learning is the study of computer algorithms that can automatically improve based on data and experience. …”
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Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation
Published 2023“…The main objective of this paper is to propose and implement an intelligent framework documentation approach that integrates case-based learning (CBL) with genetic algorithm (GA) and Knuth-Morris-Pratt (KMP) pattern matching algorithm with the intention of making learning a framework more effective. …”
Conference paper -
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Ensemble-based machine learning algorithms for classifying breast tissue based on electrical impedance spectroscopy
Published 2020“…Therefore, we aimed to classify six classes of freshly excised tissues from a set of electrical impedance measurement variables using five ensemble-based machine learning (ML) algorithms, namely, the random forest (RF), extremely randomized trees (ERT), decision tree (DT), gradient boosting tree (GBT) and AdaBoost (Adaptive Boosting) (ADB) algorithms, which can be subcategorized as bagging and boosting methods. …”
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A modified generalized RBF model with EM-based learning algorithm for medical applications
Published 2006“…In this paper, we propose a generalized RBF (GRBF) model to reduce the number of basis functions and thus alleviate curse of dimensionality. An EM-based training algorithm is also introduced, which uses fewer parameters compared to some classical supervised learning methods. …”
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Proceeding Paper -
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Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems
Published 2022“…To achieve this goal, an improved Teaching Learning-Based Optimization (ITLBO) algorithm was proposed in dealing with subset feature selection. …”
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Impact learning: A learning method from feature’s impact and competition
Published 2023“…Machine learning is the study of computer algorithms that can automatically improve based on data and experience. …”
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Opposition-Based Learning Binary Bat Algorithm as Feature Selection Approach in Taguchi's T-Method
Published 2024“…Thus, this study proposed an Opposition-based Learning Binary Bat Algorithm as the feature selection technique in the T-method. …”
Conference Paper -
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A new SMS spam detection method using both Content-Based and non Content-Based features
Published 2024Conference Paper
