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  1. 1

    Abnormal Pattern Detection In Ppg Signals Using Time Series Analysis by Siti Nur Hidayah, Mazelan

    Published 2022
    “…The accuracy and coverage of rule for both training and testing process are recorded in order to determine the performance of the method used in this study. The abnormal PPG pattern detection using rule-based algorithm has produced accuracy of 87.30% in training process and 87.18% in testing process with coverage of rule for training and testing, 89.26% and 87.33%. …”
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    Undergraduates Project Papers
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    Genetic algorithm based method for optimal location placement of flexible ac transmission system devices for voltage profile improvement by Karami, Mahdi

    Published 2011
    “…The basic structure of FACTS devices and their configuration is described. A heuristic method known as genetic algorithm is used to seek the optimum location and setting of these controllers where there are some works related to this case using various techniques. …”
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    Thesis
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    Series division method based on PSO and FA to optimize Long-Term Hydro Generation Scheduling by Hammid, Ali Thaeer, M. H., Sulaiman

    Published 2018
    “…To deal with this complicated problem, Series division method (SDM) based on the practical swarm optimization and the firefly algorithm is proposed in this paper. …”
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    Article
  7. 7

    Analysis of thyristor controlled series compensator in power transmission network by using Bees Algorithm technique / Nurshuhaida Abdul Rahman by Abdul Rahman, Nurshuhaida

    Published 2011
    “…Using these methods, the location and size of TCSC are optimized simultaneously and can be used to minimize loss in power transmission network. …”
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    Thesis
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    Analysis of thyristor controlled series compensator in power transmission network by using Bees Algorithm technique: article / Nurshuhaida Abdul Rahman by Abdul Rahman, Nurshuhaida

    Published 2011
    “…Using these methods, the location and size of TCSC are optimized simultaneously and can be used to minimize loss in power transmission network. …”
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    Article
  9. 9

    Optimization of the hidden layer of a multilayer perceptron with backpropagation (bp) network using hybrid k-means-greedy algorithm (kga) for time series prediction by Tan, James Yiaw Beng

    Published 2012
    “…The evaluation results the proposed KGA model using several time series, namely the sunspot data, the Mackey-Glass time series, and electrical load forecasting using data from several econometric factors, as well as historical electricity demand data, show that the proposed KGA model is eflective in finding the optimal number ofneurons for the hidden layer of a BP network that is used to perform time series prediction.…”
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    Thesis
  10. 10

    Enhanced algorithms for three-dimensional object interpreter by Haron, Habibollah

    Published 2004
    “…The second is the modified Freeman chain code algorithm that is used to produce chain code series that represented a thinned binary image of the sketch. …”
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    Thesis
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    Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

    Published 2018
    “…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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    Thesis
  12. 12

    Weighted subsethood segmented fuzzy time series for moving holiday electricity load demand forecasting by Mansor, R., Kasim, M.M., Othman, M.

    Published 2020
    “…This paper modifies the classical fuzzy time series (FTS) algorithm by applying weighted subsethood based algorithm (WSBA) in FTS algorithm using segmented electricity load demand time series data. …”
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    Article
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    M-Factors Fuzzy Time Series for Forecasting Moving Holiday Electricity Load Demand in Malaysia (S/O 14589) by Mansor, Rosnalini, Mat Kasim, Maznah, Othman, Mahmod, Zaini, Bahtiar Jamili

    “…Therefore, the aim of this study is to modify the conventional FTS algorithm by applying weighted subsethood in FTS algorithm on 2017-2018 segmented Malaysia electricity load demand time series data. …”
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    Monograph
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    A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

    Published 2024
    “…While the firefly algorithm solution is superior, it has a higher time complexity compared to other algorithms used when there are more hidden layers and neurons. …”
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    Thesis
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    Performance of Levenberg-Marquardt neural network algorithm in air quality forecasting by Cho, Kar Mun, Nur Haizum Abd Rahman, Iszuanie Syafidza Che Ilias

    Published 2022
    “…Levenberg-Marquardt algorithm and conjugate gradient method are frequently used for optimization in multi-layer perceptron (MLP). …”
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    Article
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    Performance of Levenberg-Marquardt neural network algorithm in air quality forecasting by Cho, Kar Mun, Abd Rahman, Nur Haizum, Che Ilias, Iszuanie Syafidza

    Published 2022
    “…Levenberg-Marquardt algorithm and conjugate gradient method are frequently used for optimization in multi-layer perceptron (MLP). …”
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    Article
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    Parameter estimation in double exponential smoothing using genetic algorithm / Foo Fong Yeng, Lau Gee Choon and Zuhaimy Ismail by Foo, Fong Yeng, Lau, Gee Choon, Ismail, Zuhaimy

    Published 2014
    “…The objective of this research is to estimate the Double Exponential Smoothing by using Genetic Algorithm Mechanism. The expected result of this research is Genetic Algorithm to able search for the best parameter in Double Exponential Smoothing.…”
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    Research Reports
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    Real-time time series error-based data reduction for internet-of-things applications by Wong, Siaw Ling

    Published 2018
    “…There are many time series data reduction methods, ranging from primitive data aggregation such as Rate of Change to sophisticated compression algorithms. …”
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    Final Year Project / Dissertation / Thesis
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    Clustering of large time-series datasets using a multi-step approach / Saeed Reza Aghabozorgi Sahaf Yazdi by Yazdi, Saeed Reza Aghabozorgi Sahaf

    Published 2013
    “…Time-series clustering is not only useful as an exploratory technique but also as a subroutine in more complex data mining algorithms. …”
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    Thesis