Search Results - (( variable direct learning algorithm ) OR ( java application sensor algorithm ))

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  1. 1

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…The process begins through the monitoring of plants using sensors connected to the Arduino device. Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. …”
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  2. 2

    Dynamic Bayesian networks and variable length genetic algorithm for designing cue-based model for dialogue act recognition by Yahya, Anwar Ali, Mahmod, Ramlan, Ramli, Abd Rahman

    Published 2010
    “…The model is, essentially, a dynamic Bayesian network induced from manually annotated dialogue corpus via dynamic Bayesian machine learning algorithms. Furthermore, the dynamic Bayesian network's random variables are constituted from sets of lexical cues selected automatically by means of a variable length genetic algorithm, developed specifically for this purpose. …”
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  3. 3
  4. 4

    An improved directed random walk framework for cancer classification using gene expression data by Seah, Choon Sen

    Published 2020
    “…Sub-algorithms of SDW can be further divided into data pre-processing phase, specific tuning parameter selection, weight as additional variable, and exclusion of unwanted adjacency matrix. …”
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    Thesis
  5. 5

    A bayesian network approach to identify factors affecting learning of Additional Mathematics by Ong, Hong Choon, Kumarenthiran A/L Chandrasekaran

    Published 2015
    “…Constraint-based algorithms and score-based algorithms are used to generate the networks into several categories to compare and identify the strong relationships among the factors that affect the students’ learning of the subject. …”
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  6. 6

    Enhancing wind power forecasting accuracy with hybrid deep learning and teaching-learning-based optimization by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

    Published 2024
    “…This paper presents an innovative approach that combines deep learning (DL) with Teaching-Learning-Based Optimization (TLBO) to predict wind power output accurately. …”
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  7. 7

    Human activity recognition via accelerometer and gyro sensors by Tee, Jia Lin

    Published 2023
    “…To implement the data engineering system proposed, two mobile applications, SensorData and SensorDataLogger with user-friendly interfaces and intuitive functionalities are developed using Java programming language and Android Studio. …”
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    Final Year Project / Dissertation / Thesis
  8. 8

    Feature selection for high dimensional data: An evolutionary filter approach. by Yahya, Anwar Ali, Osman, Addin, Ramli, Abdul Rahman, Balola, Adlan

    Published 2011
    “…As an example, genetic algorithm is an effective search algorithm that lends itself directly to feature selection; however this direct application is hindered by the recent increase of data dimensionality. …”
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  9. 9

    A case study on quality of sleep and health using Bayesian networks by Hong , Choon Ong, Chiew , Seng Lee, Chye , Ching Sia

    Published 2012
    “…There are several phases involved including implementation of the learning algorithms, integration of prior knowledge through the whitelist argument and arc setting to form directed acyclic graphs. …”
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  10. 10

    MCMAC–CVT: a novel on-line associative memory based CVT transmission control system by Kai, Keng Ang, Quek, Chai, Abdul Rahman, Abdul Wahab

    Published 2002
    “…Extensive simulation results are presented to evaluate the control performance of a direct digital PID control algorithm with auto-tuning (Trans. …”
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  11. 11

    Evaluating different machine learning models for predicting municipal solid waste generation: a case study of Malaysia by Latif S.D., Hazrin N.A.B., Younes M.K., Ahmed A.N., Elshafie A.

    Published 2025
    “…Therefore, one of the aims of this research was to investigate the use of machine learning algorithms and its benefits. The machine learning algorithms investigated are specifically Gaussian process regression (GPR), ensemble of trees and neural networks. …”
    Article
  12. 12

    Cross-project software defect prediction by Bala, Yahaya Zakariyau, Abdul Samat, Pathiah, Sharif, Khaironi Yatim, Manshor, Noridayu

    Published 2022
    “…This SLR was conducted after analyzing research articles published since 2013 in four digital libraries: Scopus, IEEE, Science Direct, and Google Scholar. In this work, five research questions covering the classification algorithms, dataset, independent variables, performance evaluation metrics used in CPDP studies, and as well as the performance of individual machine learning classification algorithms in predicting software defects across different software projects were addressed accordingly. …”
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  14. 14

    Hybrid Neural Network With K-Means For Forecasting Response Candidate In Direct Marketing by Ramadhan, Rakhmat Sani

    Published 2014
    “…K-means algorithm grouping process by minimizing the distance between the data and designed can handle very large dataset also continuous and categorical variable for handling imbalanced dataset. …”
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  15. 15

    Effective use of artificial intelligence by Malaysian manufacturing firms to enable sustainability 4.0 by Chong, Agnes Wen Lin

    Published 2023
    “…Variance inflation factor analysis and hypothesis testing analysisevaluated for determine variables affecting business analytics adoption for furtherresearch study about suggestions and direction of industrial sector.…”
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    Final Year Project / Dissertation / Thesis
  16. 16

    Detection of Denial of Service Attacks against Domain Name System Using Neural Networks by Rastegari, Samaneh

    Published 2009
    “…In the current research for our machine learning engine, we aimed to find the optimum machine learning algorithm to be used as an IDS. …”
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    Thesis
  17. 17

    Bayesian Network of Traffic Accidents in Malaysia by Zamzuri, Zamira Hasanah, Shabadin, Akmalia, Ishak, Siti Zaharah

    Published 2019
    “…One of the issues that could not be handled by the conventional way of statistical modelling is the interrelationships exist between the variables in the data set. With the advent of technology and the wide application of machine learning algorithm, this goal can be achieved through the Bayesian network analysis, in which it is a directed acyclic probabilistic graphical model. …”
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  18. 18

    Decision tree as knowledge management tool in image classification by Kusrini, , Harjoko, Agus

    Published 2008
    “…Expert System has been grown so fast as a science that study how to make computer capable of solving problems that typically can only be solved by expert.It has been realized that the biggest challenge of developing expert system is the process include expert’s knowledge into the system.This research tries to model expert’s knowledge management using case based reasoning method.The knowledge itself is not inputted directly by the expert, but rather the system will learn the knowledge from what the expert did to the previous cases.This research takes image classification as the problem to be solved.As the knowledge development technique, we build decision tree by using C4.5 algorithm.Variables used for building the decision tree are the image visual features.…”
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    Conference or Workshop Item
  19. 19

    Dynamics and control of underactuated systems with applications in robotics / Ahmad Azlan Mat Isa … [et al.] by Mat Isa, Ahmad Azlan

    Published 2011
    “…If all underactuated systems in a class can be transformed into a specific class of nonlinear systems, we refer to Artificial Neural Network (ANN) systems as the "normal form" of the corresponding class of underactuated systems. An adaptive learning algorithm using an artificial neural network ANN has been utilized to predict the passive joint position of underactuated robot manipulator. …”
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    Research Reports
  20. 20

    Image-based air quality estimation using convolutional neural network optimized by genetic algorithms: A multi-dataset approach by Khan, Arshad Ali, Mazlina, Abdul Majid, Dandoush, Abdulhalim

    Published 2025
    “…This paper proposes a new approach using convolutional neural networks with genetic algorithms for estimating air quality directly from images. …”
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