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  1. 1
    Study and Implementation of Data Mining in Urban Gardening

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

    Published 2019
    “…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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  2. 2
    NIS-Apriori-based rule generation with three-way decisions and its application system in SQL

    NIS-Apriori-based rule generation with three-way decisions and its application system in SQL by Sakai, H., Nakata, M., Watada, J.

    Published 2020
    “…Subsequently, the implementation of the NIS-Apriori algorithm in SQL is described and a few new topics induced by effects of NIS-Apriori-based rule generation are confirmed. …”
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  3. 3
    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde

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

    Published 2022
    “…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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  4. 4
    A test case generation framework based on UML statechart diagram

    A test case generation framework based on UML statechart diagram by Salman, Yasir Dawood

    Published 2018
    “…The results of the experts’ review show that the framework is practical, easy to implement due to it is suitability to generate the test cases. …”
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  5. 5
    A wireless interference-aware internet-of-things gateway placement framework with genetic algorithm approach

    A wireless interference-aware internet-of-things gateway placement framework with genetic algorithm approach by Kong, Zan Wai

    Published 2022
    “…The framework generates the solution using genetic algorithm. …”
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  6. 6
    Design and Implementation of Intelligent Interoperability Framework for Heterogeneous Subsystems in Smart Home Environment

    Design and Implementation of Intelligent Interoperability Framework for Heterogeneous Subsystems in Smart Home Environment by Perumal, Thinagaran

    Published 2011
    “…The first algorithm, named as Framework Initialization algorithm, is developed to initialize the framework and discovering the subsystems configured in order to derive the interoperation tasks. …”
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  7. 7
    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization

    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

    Published 2019
    “…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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  8. 8
    Development of a task-oriented, auction-based task allocation framework for a heterogeneous multirobot system

    Development of a task-oriented, auction-based task allocation framework for a heterogeneous multirobot system by Tan, Eijyne, Rishwaraj, G., Ponnambalam, S. G.

    Published 2020
    “…The framework involved a task allocation algorithm, which consists of bid generation and bid selection process, and a TCP/IP-based client-server communication module. …”
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  9. 9
    Implementing artificial neural networks and genetic algorithms to solve modeling and optimisation of biogas production

    Implementing artificial neural networks and genetic algorithms to solve modeling and optimisation of biogas production by Abdul Sahli, Fakharudin, Md Nasir, Sulaiman, Jailani, Salihon, Norazwina, Zainol

    Published 2013
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  10. 10
    Cloud-Mobi Framework using hybrid AHP-ACO method for Social Interaction and Travel Planning

    Cloud-Mobi Framework using hybrid AHP-ACO method for Social Interaction and Travel Planning by Peh, Perly Thai Ee, Choo, Yun Huoy, Mohd Aboobaider, Burhanuddin

    Published 2013
    “…Our future work will focus on developing the travel recommendation system prototype to implement the proposed framework.…”
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  11. 11
    Implementing artificial neural networks and genetic algorithms to solve modeling and optimisation of biogas production

    Implementing artificial neural networks and genetic algorithms to solve modeling and optimisation of biogas production by Fakharudin, Abdul Sahli, Sulaiman, Md Nasir, Salihon, Jailani, Zainol, Norazwina

    Published 2013
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  12. 12
    Implementing artificial neural networks and genetic algorithms to solve modeling and optimisation of blogas production

    Implementing artificial neural networks and genetic algorithms to solve modeling and optimisation of blogas production by Fakharudin, Abdul Sahli, Sulaiman, Md Nasir, Salihon, Jailani, Zainol, Norazwina

    Published 2013
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  13. 13
    Multi leader particle swarm optimization for optimal placement and sizing of multiple distributed generation for a micro grid

    Multi leader particle swarm optimization for optimal placement and sizing of multiple distributed generation for a micro grid by Ariya Sinhalage Buddhika Eshan Karunarathne

    Published 2023
    “…Initially, the Particle Swarm Optimization was implemented to establish the optimal sizes of DGs and the performance of the implemented algorithm was analyzed and quantified. …”
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  14. 14
    A robust, scalable multi-robot control and coordination framework achieving high throughput for parcel sorting centers

    A robust, scalable multi-robot control and coordination framework achieving high throughput for parcel sorting centers by Ch'ng, Chee Henn

    Published 2025
    “…Due to its assumption of a non perfect environment, unlike traditional algorithms, the framework is easier to implement. By balancing reactive and deliberative strategies, this framework bridges the gap between theoretical models and practical applications in robotics and automation. …”
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  15. 15
    Real-time anomaly detection using clustering in big data technologies / Riyaz Ahamed Ariyaluran Habeeb

    Real-time anomaly detection using clustering in big data technologies / Riyaz Ahamed Ariyaluran Habeeb by Riyaz Ahamed , Ariyaluran Habeeb

    Published 2019
    “…Based on the outcome of the analysis, this research proposed a novel framework namely real-time anomaly detection based on big data technologies (RTADBDT), along with supporting implementation algorithms. …”
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  16. 16
    A framework for malware identification based on behavior

    A framework for malware identification based on behavior by Mohamad Fadli, Zolkipli

    Published 2012
    “…The IF-THEN Prediction Rules which is generated using the data mining technique, ID3 Algorithm is used. …”
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  17. 17
    Estimation-based Metaheuristics: A New Branch of Computational Intelligence

    Estimation-based Metaheuristics: A New Branch of Computational Intelligence by Nor Hidayati, Abd Aziz, Zuwairie, Ibrahim, Saifudin, Razali, Nor Azlina, Ab. Aziz

    Published 2016
    “…Heuristic Kalman Algorithm (HKA) also is inspired by the Kalman Filter framework. …”
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  18. 18
    An Integrated Principal Component Analysis And Weighted Apriori-T Algorithm For Imbalanced Data Root Cause Analysis

    An Integrated Principal Component Analysis And Weighted Apriori-T Algorithm For Imbalanced Data Root Cause Analysis by Ong, Phaik Ling

    Published 2016
    “…In conclusion, the proposed algorithm is able to overcome the rare item issue by implementing covariance based support value normalization and high computational costs issue by implementing indexing enumeration tree structure.Future work of this study should focus on rule interpretation to generate more human understandable rule by novice in data mining. …”
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  19. 19
    A COLLABORATIVE FRAMEWORK FOR ANDROID MALWARE IDENTIFICATION USING DYNAMIC ANALYSIS

    A COLLABORATIVE FRAMEWORK FOR ANDROID MALWARE IDENTIFICATION USING DYNAMIC ANALYSIS by Thayaaleni, Rajandran

    Published 2019
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  20. 20
    A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition

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

    Published 2002
    “…A vector quantization model that incorporate rough sets attribute reduction and rules generation with a modified version of the K-means clustering algorithm was developed, implemented and tested as a part of a speech recognition framework, in which the Learning Vector Quantization (LVQ) neural network model was used in the pattern matching stage. …”
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