Search Results - (( developing green learning algorithm ) OR ( java data normalization algorithm ))

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    Green building valuation based on machine learning algorithms / Thuraiya Mohd ... [et al.] by Mohd, Thuraiya, Jamil, Syafiqah, Masrom, Suraya, Ab Rahim, Norbaya

    Published 2021
    “…To our knowledge, there is still no implementation of machine learning models on green building valuation features for building price prediction compared to conventional building development. …”
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    Price prediction model of green building based on machine learning algorithms / Nur Syafiqah Jamil by Jamil, Nur Syafiqah

    Published 2021
    “…In addition, this research also develops price prediction model using Machine Learning Model based on green building datasets covering the District of Kuala Lumpur, Malaysia. …”
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    Thesis
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    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

    Published 2019
    “…Even a normal people using clustering to grouping their data. …”
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    Thesis
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    SANAsms: Secure short messaging system for secure GSM mobile communication by Anuar, N.B., Azlan, I.M., Wahid, A.W.A., Zakaria, O.

    Published 2008
    “…The system is developed using Java 2 Micro Edition (J2ME) which is written in Java. …”
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    Do CEO and chairman characteristics affect green innovation? evidence from a comparative analysis of machine learning models by Xue, Ruixiang, Ong, Tze San, Demir, Ezgi

    Published 2024
    “…Using the extreme gradient boosting (XGBoost) algorithm, which is at the forefront of machine learning algorithms, this study comprehensively examines the impact of CEO and chairman characteristics on corporate green innovation. …”
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    Article
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    Green building factor in machine learning based condominium price prediction by Masrom, S., Mohd, T., Rahman, A.S.A.

    Published 2022
    “…To predict a housing price, a robust approach is crucial, which can be effectively gained from the machine learning technique. As research on green building with machine learning techniques is rarely reported in the literature, this paper presents the fundamental design and the comparison results of three machine learning algorithms namely deep learning (DL), decision tree (DT), and random forest (RF). …”
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    Article
  8. 8

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…Electing the best set of features will help to improve the classifier predictions in terms of the normal and abnormal pattern. The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. …”
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    Utilizing RGB Imaging and Machine Learning for freshness level determination of green bell pepper (Capsicum annuum L.) throughout its shelf-life by Fatchurrahman, Danial, Hilaili, Maulidia, Nurwahyuningsih, Russo, Lucia, Jahari, Mahirah, Fathi-Najafabadi, Ayoub

    Published 2025
    “…The models demonstrated exceptional accuracy in classifying and predicting the freshness of green bell peppers on the storage day, achieving 100 % accuracy with the neural network algorithm.…”
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    Article
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    Building detection using object-based Image analysis (OBIA) and machine learning (ML) algorithms / Hanani Mohd Shahar by Mohd Shahar, Hanani

    Published 2020
    “…In order to obtain a good classification accuracy, the suitable segmentation parameters (scale, shape and compactness) and features selection have been determined and Machine learning (ML) algorithms, namely Support Vector Machine (SVM) and Decision Tree (DT) classifiers have been applied to categorized five different classes which are water, forest, green area, building, and road. …”
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    Thesis
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