Search Results - (( pattern operation learning algorithm ) OR ( java application optimisation 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 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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    Article
  2. 2

    Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

    Published 2012
    “…In the first and second phases, a threshold fuzzy c-means clustering algorithm as a clusterer and a pattern ensemble learning method based on the incremental genetic-based algorithms are proposed respectively. …”
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    Thesis
  3. 3

    Constrained–Optimization-based Bayesian posterior probability extreme learning machine for pattern classification by Wong S.Y., Yap K.S.

    Published 2023
    “…Using random computational hidden neurons, ELM shows faster learning speed over the traditional learning algorithms. …”
    Conference Paper
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    Boundary extraction and corner point detection for map of kariah Kg. Bukit Kapar / 'Afina AmirHussin by AmirHussin, 'Afina

    Published 2019
    “…The purpose of study is to extract the boundary of image, find the corner point and compare between two algorithms. However, this study applied morphology operation to extract the boundary image by using erosion operation. …”
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    Thesis
  6. 6

    Web-based expert system for material selection of natural fiber- reinforced polymer composites by Ahmed Ali, Basheer Ahmed

    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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    Thesis
  7. 7

    DeepIoT.IDS: Hybrid deep learning for enhancing IoT network intrusion detection by A. Mostafa, Salama, Al-Azzawi, Ziadoon Kamil Maseer, Bahaman, Nazrulazhar, Yusof, Robiah, Musa, Omar, Al-rimy, Bander Ali Saleh

    Published 2021
    “…Recently, researchers have suggested deep learning (DL) algorithms to define intrusion features through training empirical data and learning anomaly patterns of attacks. …”
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    Article
  8. 8

    Application Of Multi-Layer Perceptron Technique To Detect And Locate The Base Of A Young Corn Plant by Morshidi, Malik Arman

    Published 2007
    “…Results of studying color segmentation using machine-learning algorithm and color space analysis is presented in this thesis. …”
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    Thesis
  9. 9

    Rough-Set-and-Genetic-Algorithm based data mining and Rule Quality Measure to hypothesize distance protective relay operation characteristics from relay event report by Othman, Mohammad Lutfi, Aris, Ishak, Othman, Mohammad Ridzal, Osman, Harussaleh

    Published 2011
    “…Using the area under the ROC curve measurements, the CD-decision algorithm has been verified to be able to predict as well as discriminate future unknown-trip-state relay events in unsupervised learning. …”
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    Article
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    Machine Learning in accounting: an introduction / Wan Mardyatul Miza Wan Tahir and Jaízah Abdul Jabar by Wan Tahir, Wan Mardyatul Miza, Abdul Jabar, Jaízah

    Published 2022
    “…Machine Learning is an application of Artificial Intelligence (AI) in which computers use algorithms to learn and recognise patterns. …”
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    Monograph
  12. 12

    Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance by Allawi, Mohammed Falah, Jaafar, Othman, Mohamad Hamzah, Firdaus, Koting, Suhana, Mohd, Nuruol Syuhadaa, El-Shafie, Ahmed

    Published 2019
    “…The three different optimization algorithms used in this study are the genetic algorithm (GA), particle swarm optimization (PSO) algorithm and shark machine learning algorithm (SMLA). …”
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    Article
  13. 13

    A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition by Babiker, Elsadig Ahmed Mohamed

    Published 2002
    “…Data analysis, data reduction, approxi mate classification, machine learning, and discovery of pattern in data are functions performed by a rough sets analysis. …”
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    Thesis
  14. 14

    Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms by Loo, C.K., Liew, W.S., Seera, M., Lim, Einly

    Published 2015
    “…To further augment the ARTMAP's pattern classification ability, multiple ARTMAPs were optimized via genetic algorithm and assembled into a classifier ensemble. …”
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    Article
  15. 15

    A novel hybrid photovoltaic current prediction model utilizing singular spectrum analysis, adaptive beluga whale optimization, and improved extreme learning machine by Mohammed Ridha, Hussein, Ahmadipour, Masoud, Alghrairi, Mokhalad, Hizam, Hashim, Mirjalili, Seyedali, Zubaidi, Salah L., Mohammed S, Marwa Y.

    Published 2025
    “…The precise and accurate prediction of the photovoltaic (PV) system can ensure the grid-connected system's constant operation and defect-free performance. Nonetheless, the PV current system's chaotic output is compounded by unpredictable weather patterns, which lead to poor predict stability, accuracy, and increasing costs. …”
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    Article
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    A Design Of License Plate Recognition System Using Convolutional Neural Network by Ahmad Radzi, Syafeeza, Piramli, Muhamad Marzuki, Wong, Yan Chiew, Abdul Hamid, Norihan, Ali, Nur Alisa, Mat Ibrahim, Masrullizam

    Published 2019
    “…This is achieved by validating the best parameters of the enhanced Stochastic Diagonal Levenberg Marquardt (SDLM) learning algorithm and network size of CNN. Several preprocessing algorithms such as Sobel operator edge detection, morphological operation and connected component analysis have been used to localize the license plate, isolate and segment the characters respectively before feeding the input to CNN. …”
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    Article
  19. 19

    Neuro Symbolic Integration and Agent Based Modelling by Sathasivam , Saratha, Velavan, Muraly

    Published 2018
    “…The major domain of neuro-symbolic integration is designed by the theory are usually known as deductive systems which less such elements of human reasoning as adaptation, learning and self-organisation. Meanwhile, neural networks, known as a mathematical model of neurons in the human brain, and have various abilities, and moreover, they also provide parallel computations and therefore can perform some calculations quicker than classical learning algorithms. …”
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    Conference or Workshop Item
  20. 20

    River flow prediction based on improved machine learning method: Cuckoo Search-Artificial Neural Network by Zanial W.N.C.W., Malek M.B.A., Reba M.N.M., Zaini N., Ahmed A.N., Sherif M., Elshafie A.

    Published 2024
    “…Therefore, it is necessary to precisely estimate how the river flow will alter as a result of changing rainfall patterns. Finding the best value for the hyper-parameters is one of the problems with machine learning algorithms, which have lately been adopted by many academics. …”
    Article