Search Results - (( developing function learning algorithm ) OR ( java decision process algorithm ))

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  1. 1

    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…Studies have shown how user perception can have a strong influence on policies and decision-making processes in a place, society, and nation. …”
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    Thesis
  2. 2

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

    Published 2015
    “…In the exponentially growing material database, selection of optimal material for engineering design is Multi Criteria Decision Making (MCDM) problem as many properties of each material influence the selection process. …”
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    Thesis
  3. 3

    Mapreduce algorithm for weather dataset by Khalid Adam, Ismail Hammad

    Published 2017
    “…This original dataset is stored in Hadoop Distributed File System. Next, MapReduce Algorithm is developed using Java programming. The algorithm is tested using small and big dataset. …”
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    Thesis
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    A Reference Based Surface Defect Segmentation Algorithm For Automatic Optical Inspection System by Wong, Ze-Hao

    Published 2020
    “…This study aims to develop an algorithm for the AOI system to segment and detect surface defects, requiring low processing power and a small number of learning dataset with labelling error resistance. …”
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    Thesis
  6. 6

    MapReduce algorithm for weather dataset by Majid, Mazlina A., Romli, Awanis, Ahmad, Noraziah, Hammad, Khalid Adam Ismail

    Published 2018
    “…This original dataset is stored in Hadoop Distributed File System. Next, MapReduce Algorithm is developed using Java programming. The algorithm is tested using small and big dataset. …”
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    Research Report
  7. 7

    Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Pr... by Sammen S.S., Ehteram M., Sheikh Khozani Z., Sidek L.M.

    Published 2024
    “…In this study, we used extreme learning machine (ELM)-multi-kernel least square support vector machine (ELM-MKLSSVM), extreme learning machine (ELM)-LSSVM-polynomial kernel function (PKF) (ELM-LSSVM-PKF), ELM-LSSVM-radial basis kernel function (RBF) (ELM-LSSVM-RBF), ELM-LSSVM-Linear Kernel function (LKF), ELM, and MKLSSVM models to predict water level. …”
    Article
  8. 8

    Automated time series forecasting by Ismail, Suzilah, Zakaria, Rohaiza, Tuan Muda, Tuan Zalizam

    Published 2011
    “…Moving Average, Decomposition, Exponential Smoothing, Time Series Regressions and ARIMA) were used.The algorithm was developed in JAVA using up to date forecasting process such as data partition, several error measures and rolling process.Successfully, the results of the algorithm tally with the results of SPSS and Excel.This automatic forecasting will not just benefit forecaster but also end users who do not have in depth knowledge about forecasting techniques.…”
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    Monograph
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    Particle swarm optimization for neural network learning enhancement by Abdull Hamed, Haza Nuzly

    Published 2006
    “…Two programs have been developed; Particle Swarm Optimization Feedforward Neural Network (PSONN) and Genetic Algorithm Backpropagation Neural Network (GANN). …”
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    Thesis
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    Support directional shifting vector: A direction based machine learning classifier by Kowsher, Md., Hossen, Imran, Tahabilder, Anik, Prottasha, Nusrat Jahan, Habib, Kaiser, Zafril Rizal, M Azmi

    Published 2021
    “…The positional error of the linear function has been modelled as a loss function which is iteratively optimized using the gradient descent algorithm. …”
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    Article
  12. 12

    Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

    Published 2008
    “…These algorithms can be used successfully in many applications requiring the optimization of a certain multi-dimensional function. …”
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    Thesis
  13. 13

    E-history Malaysian secondary school textbook using TF-IDF algorithm and text visualization / Nur Hafizah Mohd Ridzuan by Mohd Ridzuan, Nur Hafizah

    Published 2020
    “…The objective of the project is to design and develop an E-History Malaysian secondary school textbook system using Term Frequency-Inverse Document Frequency (TF-IDF) algorithm with text visualization and also to test the functionality and usability of the system through a web-based system. …”
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    Thesis
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    Evaluation of optimal MLP structure for heart disease diagnosis / Salbiah Ab Hamid by Ab Hamid, Salbiah

    Published 2010
    “…A transfer function simulation model is developed by using the MATLAB software. …”
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    Thesis
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    Volunteer Management System by Muhammad Fazril Bin Mohd Amin, Muhammad Fazril

    Published 2012
    “…This will save considerable amount of man hours, as it takes the decision making process of assigning volunteers to a timeslot in the weekly roster, based on their criterion, and relegates it to the application. …”
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    Final Year Project
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    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

    Published 2019
    “…An efficient iterative algorithm is developed to optimize the objective function of the proposed algorithm since it is non-smooth and difficult to solve. …”
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    Thesis
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    Acceleration Strategies For The Backpropagation Neural Network Learning Algorithm by Zainuddin, Zarita

    Published 2001
    “…In this thesis, factors that govern the learning speed of the backpropagation algorithm are investigated and mathematically analyzed in order to develop strategies to improve the performance of this neural network learning algorithm. …”
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    Thesis
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    Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

    Published 2012
    “…In order to address the above mentioned challenges, this study is devoted towards the development of a clusterer and a clustering ensemble learning method based on incremental genetic algorithms addressing group unlabeled samples. …”
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    Thesis