Search Results - (( java implementation bat algorithm ) OR ( program extraction machine algorithm ))

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  1. 1

    Fuzzy modeling using Bat Algorithm optimization for classification by Noor Amidah, Ahmad Sultan

    Published 2018
    “…A Sazonov Engine which is a fuzzy java engine is use to apply Bat Algorithm in the experiment. …”
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    Undergraduates Project Papers
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    Building extraction of worldview3 imagery via support vector machine using scikit-learn module / Najihah Ismail by Ismail, Najihah

    Published 2021
    “…Moreover, the capability of the programming based using python for building extraction can be assessed. …”
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    Thesis
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    Integration Of G-Code With Position Controller Via Interpreter Design Using MATLAB For Milling Machine Application by Mat Seman., Norhidayah

    Published 2019
    “…In most cases, the position controllers rarely utilize geometrical drawing such as CAD/CAM trajectory as input reference without extensive programming or trajectory generation algorithm. Thus, this thesis aims to integrate directly the trajectory in G-code form of *.txt format as input reference for the position controller algorithm designed in MATLAB/Simulink via development of a system interpreter. …”
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    Thesis
  5. 5

    A New Mobile Botnet Classification based on Permission and API Calls by Yusof, M, Saudi, MM, Ridzuan, F

    Published 2024
    “…As a result, 16 permissions and 31 API calls that are most related with mobile botnet have been extracted using feature selection and later classified and tested using machine learning algorithms. …”
    Proceedings Paper
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    Image classification using two dimensional wavelet coefficients with parallel computing by Ong, Yew Fai

    Published 2020
    “…This research algorithm demonstrated a very promising result with Support Vector Machines, this algorithm produces a 90% of accuracies whereas the decision tree algorithm gets 100% accuracies. …”
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    Final Year Project / Dissertation / Thesis
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    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

    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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    Thesis
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    A review on sentiment analysis model Chinese Weibo text by Dawei Wang, Rayner Alfred

    Published 2020
    “…In feature extraction, the Lexicon-based Model, Machine learning Model and deep learning Model usually was used. …”
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    Proceedings
  13. 13

    Predicting Student Performance in Object Oriented Programming Using Decision Tree : A Case at Kolej Poly-Tech Mara, Kuantan by Mohd Hanis, Rani, Abdullah, Embong

    Published 2013
    “…Using 10-fold cross validation for each algorithm, it was found that decision tree was the best algorithm with 83.6944% correctness. …”
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    Conference or Workshop Item
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    Assessment of crops healthiness via deep learning approach: Python / Mohamad Amirul Asyraf Mohd Ramli by Mohd Ramli, Mohamad Amirul Asyraf

    Published 2023
    “…By leveraging image processing techniques, statistical analysis and machine learning algorithms, Python enables the extraction of relevant features and patterns from data. …”
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    Student Project
  15. 15

    Chili crop segregation system design and development strategies by Wan Daud, Wan Mohd Bukhari, Abdul Aziz, Mohd Fareezuan, Ahmad Izzuddin, Tarmizi, Norasikin, Mohd Adili, Abdul Rasid, Ahmad Fuad, Wakhi Anuar, Nur Farah Bazilah, M. N. Sukhaimie

    Published 2021
    “…The image data taken from chili samples can be trained by using Learning Algorithm in the MATLAB program. The performance of the trained network then can be evaluated by using the Confusion Matrix technique. …”
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    Article
  16. 16

    Algorithms for moderating effect of emotional value from a cross-media data fusion perspective: a case study of Chinese dating reality shows by Zhang, Shasha, Dong, Qiming, Yasin, Megat Al Imran, Fang, Ng Chwee

    Published 2026
    “…During the feature extraction part, different machine-learning models are applied: Bidirectional Encoder Representations from Transformers (BERT) or Enhanced Representation through Knowledge Integration (ERNIE) for text; Convolutional Recurrent Neural Network (CRNN), and Bidirectional Long Short-Term Memory (Bi-LSTM) for audio; and Residual Neural Network (ResNet50) and Inflated 3D Convolutional Network (I3D) for video. …”
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    Article
  17. 17

    A stylometry approach for blind linguistic steganalysis model against translation-based steganography by Mohd Lokman, Syiham

    Published 2023
    “…While targeted steganalysis is designed to attack a specific embedding algorithm, blind steganalysis use features extracted or selection from the medium to detect any anomalies that indicate a possibility that a secret data has been embedded within the medium. …”
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    Thesis
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    Customer sentiment analysis through social media feedback by Siti Nur Syamimi, Mat Zain

    Published 2022
    “…The data were then split into training and testing to be tested on the three different supervised learning algorithms used in this study which are Support Vector Machine, Random Forest, and Naïve Bayes. …”
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    Undergraduates Project Papers
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    Use of hybrid classification algorithm for land use and land cover analysis in data scarce environment by Al-Doski, Jwan M. Mohammed

    Published 2013
    “…This is because the information that can be extracted from images constitutes a fundamental key in many diverse applications such as Environment, Planning and Monitoring programs and others. …”
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    Thesis
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    Framework for pedestrian walking behaviour recognition to minimize road accident by Hashim Kareem, Zahraa

    Published 2021
    “…Secondly, four different testing scenarios are chosen to acquire pedestrian walking data using the gyroscope sensor, where the essential features were extracted and selected. Thirdly, the pedestrian's behaviour is recognized using grid optimizer in machine learning. …”
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    Thesis