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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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Optimizing decentralized exam timetabling with a discrete whale optimization algorithm
Published 2025“…This problem remains an active area of research and, to the authors' knowledge, has not been adequately addressed by the WOA algorithm. …”
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Optimizing Decentralized Exam Timetabling with a Discrete Whale Optimization Algorithm
Published 2025“…This problem remains an active area of research and, to the authors’ knowledge, has not been adequately addressed by the WOA algorithm. …”
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Discretization of integrated moment invariants for writer identification
Published 2008“…Many induction algorithms found in the literature requires that training data contains only discrete features and some works better on discretized data; in particular rule based approaches like rough sets. …”
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Improving Classification Accuracy of Scikit-learn Classifiers with Discrete Fuzzy Interval Values
Published 2020“…In addition, knowledge representation is necessary to help researchers to understand better about the data during the discretization process. …”
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Predicting Accuracy of Income a Year Using Rough Set Theory
Published 2009“…In the experiments, the prediction of accuracy of the Adult dataset is developed by using rough set theory and Rosetta software while Knowledge Data Discovery (KDD) is used as the methodology. …”
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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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Logic mining method via hybrid discrete hopfield neural network
Published 2025“…To address these challenges, this paper introduces a novel logic mining approach using the Y-type Random 2 Satisfiability logical rule, combined with hybrid mechanisms within the Discrete Hopfield Neural Network. …”
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Malay continuous speech recognition using continuous density hidden Markov model
Published 2007“…With their efficient training algorithm (Baum-Welch and Viterbi/Segmental K-mean) and recognition algorithm (Viterbi), as well as it’s modeling flexibility in model topology, observation probability distribution, representation of speech unit and other knowledge sources, HMM has been successfully applied in solving various tasks in this thesis. …”
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An extended ID3 decision tree algorithm for spatial data
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Rough sets for predicting the Kuala Lumpur Stock Exchange Composite Index returns
Published 2004“…There are extensive literatures available describing attempts to use artificial intelligence techniques; in particular neural networks and genetic algorithm for analyzing stock market variations.However, drawbacks are found where neural networks have great complexity in interpreting the results; genetic algorithms create large data redundancies.A relatively new approach, the rough sets are suggested for its simple knowledge representation, ability to deal with uncertainties and lowering data redundancies.In this study, a few different discretization algorithms were used at data preprocessing. …”
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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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P300 detection of brain signals using a combination of wavelet transform techniques
Published 2012“…Wavelet transform (WT), student’s two-sample t-statistic (T-Test) and support vector machines (SVM) used in designing the algorithms. By using three level of channel reduction, three subgroups of channels with the number of 17, 9, and 5 have been chosen based on their ability in P300 pattern recognition. …”
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High performance simulation for brain tumors growth using parabolic equation on heterogeneous parallel computer systems
Published 2007“…The implementation of parallel algorithm based on parallel computing system is used to capture the growth of brain tumour. …”
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New fundamental theory in solving the royalty payment problem / Wan Noor Afifah Wan Ahmad and Suliadi Firdaus Sufahani
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High performance simulation for brain tumours growth using parabolic equation on heterogeneous parallel computer system
Published 2007“…The implementation of parallel algorithm based on parallel computing system is used to capture the growth of brain tumour. …”
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Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process
Published 2004“…The machining data available in MDH was used to train the designed network. One cutting material (medium carbide steel) with its complete set of cutting tools (High Speed Steel, Brazed Uncoated Carbide, Indexable Uncoated Carbide, and Coated Carbide) discretized into 243 data sets was used in one training session for the designed network. …”
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Implementing Station-to-Station protocol using Multi Prime RSA Cryptosystem / Muhammad Arif Musa Abdullah
Published 2023“…The study recommends to use another type of digital signature algorithm to be used in the proposed method. …”
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