Search Results - (( miner classification system algorithm ) OR ( java application optimisation algorithm ))

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  1. 1
    Adaptive parameter control strategy for ant-miner classification algorithm

    Adaptive parameter control strategy for ant-miner classification algorithm by Al-Behadili, Hayder Naser Khraibet, Sagban, Rafid, Ku-Mahamud, Ku Ruhana

    Published 2020
    “…This paper presents a new hybrid Ant-Miner classification algorithm and ant colony system (ACS), called ACS-Ant Miner. …”
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  2. 2
    Predicting attackers of online shaming using ant colony optimization / Noor Shafiqa Fazlien Mohamad Fauzi

    Predicting attackers of online shaming using ant colony optimization / Noor Shafiqa Fazlien Mohamad Fauzi by Mohamad Fauzi, Noor Shafiqa Fazlien

    Published 2020
    “…The Ant Miner system plays an important role in running the Ant Colony Optimization Algorithm and making comparison in this case study.…”
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  3. 3
    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
    “…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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  4. 4
    Predicting heart disease using ant colony optimization / Siti Aisyah Ismail

    Predicting heart disease using ant colony optimization / Siti Aisyah Ismail by Ismail, Siti Aisyah

    Published 2021
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  5. 5
    Predicting breast cancer using ant colony optimisation / Siti Sarah Aqilah Che Ani

    Predicting breast cancer using ant colony optimisation / Siti Sarah Aqilah Che Ani by Che Ani, Siti Sarah Aqilah

    Published 2021
    “…Besides, in this study, the Ant-Miner system also plays an important role, which can train the data several times to achieve the highest percentage of predictive accuracy and make comparisons to achieve a good classification model. …”
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  6. 6
    Evaluation of data mining classification and clustering techniques for diabetes / Tuba Pala and Ali Yilmaz Camurcu

    Evaluation of data mining classification and clustering techniques for diabetes / Tuba Pala and Ali Yilmaz Camurcu by Pala, Tuba, Camurcu, Ali Yilmaz

    Published 2014
    “…The success evaluation of data mining classification algorithms have been realized through the data mining programs Weka and RapidMiner. …”
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  7. 7
    Adaptive method to improve web recommendation system for anonymous users

    Adaptive method to improve web recommendation system for anonymous users by Almurtadha, Yahya Mohammed

    Published 2011
    “…This research proposed two web page recommendation systems. The first is iPACT, an improved recommendation system based on PACT methodology to demonstrate the prediction accuracy of the proposed enhanced classification algorithm in this research. …”
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  8. 8
    Web-based expert system for material selection of natural fiber- reinforced polymer composites

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

    Published 2015
    “…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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  9. 9
    Machine Learning based Predictive Modelling of Cybersecurity Threats Utilising Behavioural Data

    Machine Learning based Predictive Modelling of Cybersecurity Threats Utilising Behavioural Data by Ting, Tin Tin, Khiew, Jie Xin, Ali Aitizaz, Lee, Kuok Tiung, Teoh, Chong Keat, Hasan Sarwar

    Published 2023
    “…Five supervised machine learning methods are being tested which are: Regression Logistics, K-Nearest Neighbour (KNN), Decision Tree (DT), Support Vector Machine (SVM), and Naïve Bayesian Classifier with the aid of a tool, RapidMiner. The algorithms are used to construct, test, and validate three categories of cybercrime threat (Malware, Social Engineering, and Password Attack) predictive models. …”
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