Search Results - intelligence system ((tree algorithm) OR (((learning algorithm) OR (means algorithm))))

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  1. 1

    Development of an intelligent information system for financial analysis depend on supervised machine learning algorithms by Lei, X., Mohamad, U.H., Sarlan, A., Shutaywi, M., Daradkeh, Y.I., Mohammed, H.O.

    Published 2022
    “…For the objective of classifying FI in terms of fraud or not, the Intelligent Information System for Financial Institutions (IISFI) relying on Supervised ML (SML) Algorithms has been created in this work. …”
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    Article
  2. 2

    Application of machine learning algorithms to predict removal efficiency in treating produced water via gas hydrate-based desalination by Nallakukkala, Sirisha, Tackie-Otoo, Bennet Nii, Aliyu, Ruwaida, Lal, Bhajan, Nallakukkala, Jagadish Ram Deepak, Devi, Gayathri

    Published 2025
    “…In this context. ML algorithms provide powerful data driven means to model complex relationship within experimental datasets to improve process optimisation This study systematically evaluated several supervised ML models, including Random Forest (RF) Support Vector Machines (SVM), Ridge Regression, Lasso Regression, Decision Tree, Extra Tree Regression, Gradient Boost, and XGBoost, to predict removal efficiency in GHBD system. …”
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    Article
  3. 3

    Intelligent cooperative web caching policies for media objects based on J48 decision tree and naïve Bayes supervised machine learning algorithms in structured peer-to-peer systems by Ibrahim, Hamidah, Mohammed, Waheed Yasin, Udzir, Nur Izura, Abdul Hamid, Nor Asilah Wati

    Published 2016
    “…Moreover, traditional web caching policies such as Least Recently Used (LRU), Least Frequently Used (LFU), and Greedy Dual Size (GDS) suffer from caching pollution (i.e. media objects that are stored in the cache are not frequently visited which negatively affects on the performance of web proxy caching). In this work, intelligent cooperative web caching approaches based on J48 decision tree and Naïve Bayes (NB) supervised machine learning algorithms are presented. …”
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    Article
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    Linking Bayesian Network and Intensive Care Units Data: A Glycemic Control Study by Abu-Samah A., Abdul Razak N.N., Mohamad Suhaimi F., Jamaludin U.K., Chase G.

    Published 2023
    “…Decision support systems; Forecasting; Intensive care units; Medical informatics; Trees (mathematics); Accurate prediction; Causal Bayesian network; Discretization algorithms; Discretizations; Glycemic control; Intelligent mechanisms; Performance prediction; Variable selection; Bayesian networks…”
    Conference Paper
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    Ozone Concentration Forecasting Based on Artificial Intelligence Techniques: A Systematic Review by Yafouz A., Ahmed A.N., Zaini N., El-Shafie A.

    Published 2023
    “…Decision trees; Forecasting; Multilayer neural networks; Ozone; Predictive analytics; Support vector machines; Artificial intelligence techniques; Machine learning techniques; Multi layer perceptron; Optimization approach; Ozone concentration forecasting; Prediction accuracy; Stand-alone algorithm; Tropospheric ozone concentration; Learning systems; ozone; air quality; algorithm; concentration (composition); machine learning; optimization; ozone; prediction; theoretical study; air pollutant; air quality; artificial intelligence; artificial neural network; concentration (parameter); decision tree; feed forward neural network; forecasting; fuzzy system; human; measurement accuracy; multilayer perceptron; prediction; random forest; recurrent neural network; Review; support vector machine; systematic review…”
    Review
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    An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM) by Shamim, Akhtar

    Published 2024
    “…This study recommends a selection trade-off as the function of prediction efficiency and efficacy of the algorithm. Particularly, the proposed optimized Bagged Trees are the most effective algorithm for energy demand prediction applications, and the proposed optimized Medium Trees are the most efficient algorithm for real-time systems. …”
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    Thesis
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    Artificial intelligent integrated into sun-tracking system to enhance the accuracy, reliability and long-term performance in solar energy harnessing by Tan, Jun You

    Published 2022
    “…The proposed AI algorithm integrates two deep learning models which are object detection algorithm and reinforcement learning. …”
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    Final Year Project / Dissertation / Thesis
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    A Modified Hybrid Fuzzy Controller for Real-Time Mobile Robot Navigation by Hossen J., Sayeed S., Iqbal A.K.M.P.

    Published 2023
    “…Algorithms; Controllers; Fuzzy clustering; Fuzzy systems; Intelligent control; Intelligent systems; Learning algorithms; Least squares approximations; Membership functions; Mobile robots; Navigation; Robotics; Robots; Smart sensors; and ANFIS; Apriori algorithms; Fuzzy C mean; Gradient descent algorithms; Hybrid-fuzzy controllers; Mobile Robot Navigation; Subtractive clustering; Subtractive clustering algorithms; Clustering algorithms…”
    Conference Paper
  12. 12

    Intelligent cooperative web caching policies for media objects based on J48 decision tree and Naive bayes supervised machine learning algorithms in structured peer-to-peer systems by Ibrahim, Hamidah, Yasin, Waheed, Udzir, Nur Izura, Abdul Hamid, Nor Asilah Wati

    Published 2016
    “…Moreover, traditional web caching policies such as Least Recently Used (LRU), Least Frequently Used (LFU), and Greedy Dual Size (GDS) suffer from caching pollution (i.e. media objects that are stored in the cache are not frequently visited which negatively affects on the performance of web proxy caching). In this work, intelligent cooperative web caching approaches based on J48 decision tree and Naïve Bayes (NB) supervised machine learning algorithms are presented. …”
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    Article
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    An Intelligent System Approach to the Dynamic Hybrid Robot Control by Md. Yeasin, Md. Mahmud Hasan

    Published 1996
    “…This was because a robot can be seen as a physical intelligent system which interacts with the real world environment by means of its sensors and actuators. …”
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    Thesis
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