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  1. 1
    Multi-objective Binary Clonal Selection Algorithm In The Retrieval Phase Of Discrete Hopfield Neural Network With Weighted Systematic Satisfiability

    Multi-objective Binary Clonal Selection Algorithm In The Retrieval Phase Of Discrete Hopfield Neural Network With Weighted Systematic Satisfiability by Romli, Nurul Atiqah

    Published 2024
    “…Therefore, this thesis proposes a new systematic Satisfiability logical rule namely Weighted Systematic 2 Satisfiability that uses a weighted feature to control the distribution of the negative literals. …”
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  2. 2
    Mining Of Resource Usage Using Evoc Algorithm In Grid Environment.

    Mining Of Resource Usage Using Evoc Algorithm In Grid Environment. by Kee, Sim Ee, Chan, Huah Yong, Haron, Fazilah

    Published 2007
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  3. 3
    Satisfiable Integer Programming Algorithm On Distributed Inter Process Communication (SIP-DIPC)

    Satisfiable Integer Programming Algorithm On Distributed Inter Process Communication (SIP-DIPC) by Abdul Hamid, Mohd Hakim, Abu, Nur Azman, Mohamad, Siti Nurul Mahfuzah, Idris, Aris, Zakaria, Zahriladha, Sulaiman, Zuraidah

    Published 2019
    “…Data Analytics is a superset to Data Mining. Data mining algorithm is getting popular support in recent development of Big Data. …”
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  4. 4
    Enhancement load balancing in failover web server by using HTTP-response status techniques with pfsense opensource / Muhammad Hafiz Ramli

    Enhancement load balancing in failover web server by using HTTP-response status techniques with pfsense opensource / Muhammad Hafiz Ramli by Ramli, Muhammad Hafiz

    Published 2020
    “…Meanwhile, an email notification was introduced in ICMP and HTTP based monitoring as a notification to the administrator when the failure occurs.…”
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  5. 5
    Discovery of SIP/DRIP approach in distributed inter process communication

    Discovery of SIP/DRIP approach in distributed inter process communication by Hamid H., Jais J.

    Published 2023
    Conference paper
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  6. 6
    Unsupervised logic mining with a binary clonal selection algorithm in multi-unit discrete Hopfield neural networks via weighted systematic 2 satisfiability

    Unsupervised logic mining with a binary clonal selection algorithm in multi-unit discrete Hopfield neural networks via weighted systematic 2 satisfiability by Romli, Nurul Atiqah, Zulkepli, Nur Fariha Syaqina, Kasihmuddin, Mohd Shareduwan Mohd, Zamri, Nur Ezlin, Rusdi, Nur 'Afifah, Manoharam, Gaeithry, Mansor, Mohd. Asyraf, Jamaludin, Siti Zulaikha Mohd, Malik, Amierah Abdul

    Published 2024
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  7. 7
    Study of machine learning in computer vision using Raspberry Pi

    Study of machine learning in computer vision using Raspberry Pi by Chong, Kah Luo

    Published 2024
    text::Final Year Project
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  8. 8
    Parallel execution of distributed SVM using MPI (CoDLib)

    Parallel execution of distributed SVM using MPI (CoDLib) by Salleh N.S.M., Suliman A., Ahmad A.R.

    Published 2023
    “…To reduce the computational time during the process of training the SVM, a combination of distributed and parallel computing method, CoDLib have been proposed. …”
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  9. 9
    Analysis using data mining techniques: the exploration and review data of diabetes patients / Syarifah Adilah Mohamed Yusoff ... [et al.]

    Analysis using data mining techniques: the exploration and review data of diabetes patients / Syarifah Adilah Mohamed Yusoff ... [et al.] by Mohamed Yusoff, Syarifah Adilah, Othman, Jamal, Johan, Elly Johana, Mohd Mydin, Azlina, Wan Mohamad, Wan Anisha

    Published 2025
    “…Data mining is undergoing a transformative phase driven by advancements in Artificial Intelligence, statistics, database technology, real-time processing and integration of diverse data sources. …”
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  10. 10
    Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets

    Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets by Saeed, Sana

    Published 2019
    “…A new self-adaptive hybrid algorithm (CSCMAES) is introduced for optimization. …”
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  11. 11
    Traffic monitoring system with emergency support using SOM

    Traffic monitoring system with emergency support using SOM by Tan, Hoai Thang

    Published 2020
    “…This paper proposed a system of emergency notification to alert the driver. …”
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  12. 12
    Algorithm Development of Bidirectional Agglomerative Hierarchical Clustering Using AVL Tree with Visualization

    Algorithm Development of Bidirectional Agglomerative Hierarchical Clustering Using AVL Tree with Visualization by Hussain Mohammad Yousef Abu Dalbouh

    Published 2024
    thesis::doctoral thesis
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  13. 13
    Predicting Customer Buying Decisions for Online Shopping with Unbalanced Data Set

    Predicting Customer Buying Decisions for Online Shopping with Unbalanced Data Set by Yap, Chau Tean

    Published 2022
    “…The data set is unbalanced as it consists of 15.5% of the positive class and 84.5% of the negative class. Weka, a data mining tool, provides the facility to classify the data set with different machine learning algorithms. …”
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  14. 14
    Development of a new algorithm for segmentation of flotation froth images

    Development of a new algorithm for segmentation of flotation froth images by Jahedsaravani, Ali, Marhaban, Mohammad Hamiruce, Massinaei, Mohammad, Saripan, M. Iqbal, Mehrshad, Naser, Mohd Noor, Samsul Bahari

    Published 2014
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  15. 15
    A novel approach to data mining using simplified swarm optimization

    A novel approach to data mining using simplified swarm optimization by Wahid, Noorhaniza

    Published 2011
    “…In this thesis, a novel Simplified Swarm Optimization (SSO) algorithm is proposed as a rule-based classifier and for feature selection. …”
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  16. 16
    Binary vote assignment on grid quorum replication technique with association rule

    Binary vote assignment on grid quorum replication technique with association rule by Ainul Azila, Che Fauzi

    Published 2018
    “…Organizations need to provide current data to users who may be geographically remote and to handle a volume of requests of data distributed around multiple sites in distributed environment. …”
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  17. 17
    Building classification models from imbalanced fraud detection data / Terence Yong Koon Beh, Swee Chuan Tan and Hwee Theng Yeo

    Building classification models from imbalanced fraud detection data / Terence Yong Koon Beh, Swee Chuan Tan and Hwee Theng Yeo by Terence, Yong Koon Beh, Swee, Chuan Tan, Hwee, Theng Yeo

    Published 2014
    “…Building classification models from such imbalanced data sets is a relatively new challenge in the machine learning and data mining community because many traditional classification algorithms assume similar proportions of majority and minority classes. …”
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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
    “…However, frequent pattern mining (FPM) using Apriori-like algorithms and support-confidence framework suffers from the myth of rare item problem in nature. …”
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  19. 19
    Distribution and health risk assessment of trace metals in freshwater tilapia from three different aquaculture sites in Jelebu Region (Malaysia)

    Distribution and health risk assessment of trace metals in freshwater tilapia from three different aquaculture sites in Jelebu Region (Malaysia) by Low, K.H., Zain, S.M., Abas, R., Salleh, K.M., Teo, Y.Y.

    Published 2015
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  20. 20
    Sequential pattern mining using personalized minimum support threshold with minimum items

    Sequential pattern mining using personalized minimum support threshold with minimum items by Alias, Suraya, Razali, Mohd Norhisham, Tan, Soo Fun, Sainin, Mohd Shamrie

    Published 2011
    “…One of the challenges of Sequential Pattern Mining is finding frequent sequential patterns in a huge click stream data (web logs) since the data has the issue of a very low support distribution.By applying a Frequent Pattern Discovery technique, a sequence is considered as frequent if it occurs more than the minimum support (min sup) threshold value.The conventional method of assuming one min sup value is valid for all levels of k-sequence, may have an impact on the overall results or pattern generation. …”
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