Search Results - (( variable learning based algorithm ) OR ( variable extractions mining algorithm ))

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  1. 1

    Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

    Published 2018
    “…This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through use of a robust and efficient optimization algorithm in learning process of GEP approach. To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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    Thesis
  2. 2

    A hybrid serendipity social recommender model / Ahmad Subhi Zolkafly and Rahayu Ahmad by Zolkafly, Ahmad Subhi, Ahmad, Rahayu

    Published 2020
    “…In the next stage, the classification model is used to classify the data into subclasses by using a deep learning algorithm. This algorithm aims to define the higher matching suggested attributes and used for processing massive data. …”
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    Article
  3. 3

    Machine-learning approach using thermal and synthetic aperture radar data for classification of oil palm trees with basal stem rot disease by Che Hashim, Izrahayu

    Published 2021
    “…As the ALOS PALSAR-2 image was evaluated with dual-polarization (HH and HV), each digitized point has two distinct backscatter data with four severity levels (T0 to T3). The machine learning algorithm consistently performs well when presented with a well-balanced dataset. …”
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    Thesis
  4. 4

    Exploratory analysis with association rule mining algorithms in the retail industry / Alaa Amin Hashad ... [et al.] by Hashad, Alaa Amin, Khaw, Khai Wah, Alnoor, Alhamzah, Chew, Xin Ying

    Published 2024
    “…To address this, missing customer IDs are filled with the last valid ID, assuming repeated purchases. The FP-Growth algorithm was found to be faster and more effective than the Apriori algorithm in extracting frequent item sets and generating association rules. …”
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    Article
  5. 5

    RARE: mining colossal closed itemset in high dimensional data by Md Zaki, Fatimah Audah, Zulkurnain, Nurul Fariza

    Published 2018
    “…The task of mining association rules highly relies on the efficiency of the algorithms to extract all frequent itemsets that exist in the database. …”
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    Article
  6. 6

    Analysis of Traffic Accident Patterns Using Association Rule Mining by Yudy, Pranata, Tri Basuki, Kurniawan, Edi Surya, Negara, Ahmad Haidar, Mirza

    Published 2024
    “…This study also demonstrated the practicality of the apriori algorithm in analyzing extensive datasets to extract actionable insights. …”
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    Article
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    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
    “…Therefore, it is advisable for future studies to implement robust classification algorithms, such as ensemble methods, to effectively manage and extract potential insights.…”
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    Article
  9. 9

    Ensemble-based machine learning algorithms for classifying breast tissue based on electrical impedance spectroscopy by Rahman, Sam Matiur, Ali, Md. Asraf, Altwijri, Omar, Alqahtani, Mahdi, Ahmed, Nasim, Ahamed, Nizam Uddin

    Published 2020
    “…In addition, the ranked order of the variables based on their importance differed across the ML algorithms. …”
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    Conference or Workshop Item
  10. 10

    Dynamic Bayesian Networks and Variable Length Genetic Algorithm for Dialogue Act Recognition by Ali Yahya, Anwar

    Published 2007
    “…The current dialogue act recognition models, namely cue-based models, are based on machine learning techniques, particularly statistical ones. …”
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    Thesis
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    One day ahead daily peak hour load forecasting by using invasive weed optimization learning algorithm based Artificial Neural Network by Rahim, Muhammad Fitri

    Published 2012
    “…By using 'seen' and 'unseen' of electrical energy demand data were used to test the performance of the proposed algorithm. Based on result obtained, it shows that IWO learning algorithm is capable to produce accurate prediction load demand. …”
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    Student Project
  15. 15

    Enhanced Adaptive Confidence-Based Q Routing Algorithms For Network Traffic by Yap, Soon Teck

    Published 2004
    “…These two adaptive routing algorithms enhance the existing Confidence-based Q (CQ) and Confidence-based Dual Reinforcement Q (CDRQ) Routing Algorithms. …”
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    Thesis
  16. 16

    Prediction of electronic cigarette and vape use among Malaysian: decision tree analysis by Kartiwi, Mira, Ab Rahman, Jamalludin, Nik Mohamed, Mohamad Haniki, Draman, Samsul, Ab Rahman, Norny Syafinaz

    Published 2017
    “…Results: By using the ID3 algorithm, it is possible to consider the relationship among variables and to identify the most informative variables for predicting the classification of the instance. …”
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    Article
  17. 17

    Dynamic Bayesian networks and variable length genetic algorithm for designing cue-based model for dialogue act recognition by Yahya, Anwar Ali, Mahmod, Ramlan, Ramli, Abd Rahman

    Published 2010
    “…The model is, essentially, a dynamic Bayesian network induced from manually annotated dialogue corpus via dynamic Bayesian machine learning algorithms. Furthermore, the dynamic Bayesian network's random variables are constituted from sets of lexical cues selected automatically by means of a variable length genetic algorithm, developed specifically for this purpose. …”
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    Article
  18. 18

    Weather prediction in Kota Kinabalu using linear regressions with multiple variables by Teong, Khan Vun, Chung, Gwo Chin, Jedol Dayou

    Published 2021
    “…Numerical weather prediction is the process of using existing numerical data on weather conditions to forecast the weather using machine learning algorithms. This study employs machine learning algorithms, a linear regression model using statistics, and two optimization approaches, the normal equation approach, and gradient descent approach to predict the weather based on a few variables. …”
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    Proceedings
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    Assessment of forest aboveground biomass estimation from superview-1 satellite image using machine learning approaches / Azinuddin Mohd Asri by Mohd Asri, Azinuddin

    Published 2022
    “…In contrast, machine learning is used to calculate the accuracy assessment of dependent between independent variables. …”
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    Thesis