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  1. 1

    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…In order to address the challenges that mentioned above in this study, in the first phase, a novel architecture based on ensemble feature selection techniques include Modified Binary Bat Algorithm (NBBA), Binary Quantum Particle Swarm Optimization (QBPSO) Algorithm and Binary Quantum Gravita tional Search Algorithm (QBGSA) is hybridized with the Multi-layer Perceptron (MLP) classifier in order to select relevant feature subsets and improve classification accuracy. …”
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  2. 2

    An improved algorithm for iris classification by using support vector machine and binary random machine learning by Kamarulzalis, Ahmad Haadzal

    Published 2018
    “…The first objective of this study is to improve a new algorithm technique for classification. The new algorithm come from a combination of an ideas of k-NN algorithm and ensemble concept. …”
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    Feature and Instances Selection for Nearest Neighbor Classification via Cooperative PSO by Sharifah Sakinah, Syed Ahmad

    Published 2014
    “…The proposed method is applied to 14 real world dataset from the machine learning repository. The algorithm’s performance is illustrated by the corresponding table of the classification rate. …”
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    Hydrothermal scheduling using genetic algorithm approach / Norehsan Ali by Ali, Norehsan

    Published 1998
    “…The GA developed, aim to obtained the optimized output of the Ps (steam plant) and PH (hydro plant) with minimum cost for the steam plant, since the generation cost for the hydro plant is absolutely free. …”
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  7. 7

    Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi by Atefi, Kayvan

    Published 2019
    “…Experiments demonstrate and prove that the proposed EBPSO method produces better accuracy mining data and selecting subset of relevant features comparing other algorithms. …”
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  8. 8

    Neuro-Fuzzy and Particle Swarm Optimization based Model for the Steam and Cooling sections of a Cogeneration and Cooling Plant by Alemu Lemma, Tamiru, Rangkuti, Chalillullah, Mohd Hashim, Fakhruldin

    Published 2009
    “…Neuro-fuzzy approach trained by a sequence of optimization algorithms-Particle Swarm Optimization (PSO) followed by Back-Propagation (BP)-is used to develop models for the steam drum pressure, steam drum water level, steam flow rate and chilled water supply temperature. …”
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  9. 9

    Combining Genetic Algorithm and Artificial Neural Network to optimize biomass steam power plant emission / Ahmad Razlan Yusoff and Ishak Abdul Aziz

    Published 2008
    “…Genetic Algorithm and Artificial Neural Network (GAANN) were used to analyze the real data taken from palm oil mill power plant. …”
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  10. 10

    Named entity recognition using a new fuzzy support vector machine. by Mansouri, Alireza, Affendy, Lilly Suriani, Mamat, Ali

    Published 2008
    “…The design of our method is a kind of One-Against-All multi classification technique to solve the traditional binary classifier in SVM.…”
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    Enhancement of new smooth support vector machines for classification problems by Santi Wulan, Purnami

    Published 2011
    “…Research on Smooth Support Vector Machine (SSVM) for classification problem is an active field in data mining. …”
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  13. 13

    SYSTEMATIC DESIGN ALGORITHM FOR ENERGY EFFICIENT AND COST EFFECTIVE HYDROGEN PRODUCTION FROM PALM WASTE by INAYAT, ABRAR

    Published 2012
    “…In the current study, a systematic autonomous algorithm incorporating reaction kinetics model, flowsheet calculations, heat integration analysis and economic evaluation, has been developed to calculate optimum parameters giving minimum hydrogen production cost using optimization strategies. …”
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  14. 14

    Overview of biomedical relations extraction using hybrid rule-based approaches. by Abdul Kadir, Rabiah, Bokharaeian, Behrouz

    Published 2013
    “…These huge amounts of information cause very difficult task of extraction or classification.Therefore, there is a need for knowledge discovery and text mining tools in this field. …”
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  15. 15

    Multitasking deep neural network models for Arabic dialect sentiment analysis by Alali, Muath Mohammad Oqlah

    Published 2022
    “…Therefore, a model called Multi-Tasking Learning based on Convolutional Hierarchical Attention Neural Network (MTL-CHAN) is proposed, comprising of (i) shared word encoder and word attention networks across classification tasks, (ii) task-specific layers with convolutional neural network-based attention (CNNA) on sentence-level; to handle the Arabic explicit negation words and improve the classification performance by training Arabic classification tasks (binary, ternary, and five) jointly. …”
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  16. 16

    Optimization of stiffened panel fatigue life by using finite element analysis by Mazlan, Shahan

    Published 2020
    “…The multi-objective genetic algorithm which selects the design points based on Pareto optimal design combined with the adaptive multi-objective algorithm method which uses an optimal space-filling was shown to be efficient for time limitation and budget. …”
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  17. 17

    Hybrid Neural Network With K-Means For Forecasting Response Candidate In Direct Marketing by Ramadhan, Rakhmat Sani

    Published 2014
    “…This research concerns on binary classification which is classified into two classes. …”
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    Multi-objective model optimisation using genetic algorithms for pleurotus sp. cultivation by Norazwina, Zainol, Abdul Sahli, Fakharudin, Noor Athirah, Dzulkefli, M. F., A. Bakar

    Published 2020
    “…For this type of problem, multi-objective genetic algorithm was chosen as the methodology, specifically using NSGA-II algorithm. …”
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    Temperature control of a pilot plant reactor system using a genetic algorithm model‐based control approach by Wahab, Ahmad Khairi Abdul, Hussain, Mohd Azlan, Omer, Rosli

    Published 2007
    “…The work described in this paper aims at exploring the use of an artificial intelligence technique, i.e. genetic algorithm (GA), for designing an optimal model-based controller to regulate the temperature of a reactor. …”
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