Search Results - (( whale optimization means algorithm ) OR ( based observations tree algorithm ))

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    Enhancement of Groundwater-Level Prediction Using an Integrated Machine Learning Model Optimized by Whale Algorithm by Banadkooki F.B., Ehteram M., Ahmed A.N., Teo F.Y., Fai C.M., Afan H.A., Sapitang M., El-Shafie A.

    Published 2023
    “…For the test stage, the mean absolute error of the MLP�WA model decreased to 30% and from 31 to 38% as compared to the radial basis function�whale algorithm (RBF�WA) and GP models, respectively. …”
    Article
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    Application and evaluation of the evolutionary algorithms combined with conventional neural network to determine the building energy consumption of the residential sector by Wang G., Mukhtar A., Moayedi H., Khalilpoor N., Tt Q.

    Published 2025
    “…The primary objectives were to assess the performance of three evolutionary algorithms ? Heap-Based Optimizer (HBO), Multiverse Optimizer (MVO), and Whale Optimization Algorithm (WOA) ? …”
    Article
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    Hybrid flow shop scheduling with energy consumption in machine shop using moth flame optimization by M. F. F., Ab Rashid, Ahmad Nasser, Mohd Rose, N. M. Zuki, N. M.

    Published 2022
    “…The results were also compared with relatively recent algorithm such as Whale Optimization Algorithm and Harris Haws Optimization. …”
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    Multi-criteria optimization framework for cloudlet computing in WMANs: integrating VL-WIDE and AHP for enhanced decision-making by Muwafaq, Layth, Noordin, Nor K, Othman, Mohamed, Ismail, Alyani, Hashim, Fazirulhisyam

    Published 2026
    “…Our method employs a variable-length multi-objective whale optimization integrated with differential evolution (VL-WIDE) to tackle the optimization problem, dynamically adjusting to the WMAN environment while optimizing delay, energy consumption (both user device and cloudlet), and cloudlet deployment cost. …”
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    Improved Boosting Algorithms by Pre-Pruning and Associative Rule Mining on Decision Trees for predicting Obstructive Sleep Apnea by Doreen Ying Ying, Sim, Chee Siong, Teh, Ahmad Izuanuddin, Ismail

    Published 2017
    “…The Pruned-Associative-Rule-Mined Decision Trees (PARM-DT) developed by adopting pre-pruning techniques on tree depth, minimum leaf and/or parent node size observations and maximum number of tree splits, based on Apriori and/or Adaptive Apriori (AA) frameworks, is boosted to achieve better predictive accuracies. …”
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    Prediction of earnings manipulation on Malaysian listed firms: A comparison between linear and tree-based machine learning by Rahman, R.A., Masrom, S., Zakaria, N.B., Nurdin, E., Abd Rahman, A.S.

    Published 2021
    “…Thus, the aim of the paper is to compare the earnings manipulation prediction models developed by using two types of machine learning algorithms; linear and tree categories. The linear based machine learning are Logistic Regression and Generalized Linear Model while the tree based are Decision Tree and Random Forest. …”
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    Decision tree-based approach for online management of PEM fuel cells for residential application by Mohd Rusllim, Mohamed

    Published 2004
    “…A database is extracted from a previously-performed Genetic Algorithm (GA)-based optimization has been used to create a suitable decision tree, which was intended for generalizing the optimization results. …”
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    Algorithm of the longest commonly consecutive word for plagiarism detection in text based document by Sediyono, Agung, Ku-Mahamud, Ku Ruhana

    Published 2008
    “…Based on the experiment, the proposed algorithm outperforms the suffix tree in the length of observed paragraph below one hundred words.…”
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    Decision tree-based approach for online management of pem fuel cells for residential application by Mohamed, Mohd Rusllim

    Published 2004
    “…A database was extracted from a previously�performed Genetic Algorithm (GA)-based optimization that has been used to create a suitable decision tree, which was intended for generalizing the optimization results. …”
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    Solar maximum power point tracking based on improved incremental conductance algorithm by Mailah, Nashiren Farzilah, Boyao, Ma

    Published 2025
    “…To address these limitations, this work proposes an incremental conductance-based resilient adaptive step-size MPPT (INC-RASS-MPPT) algorithm.…”
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    Delineating mangrove forest zone using spectral reflectance by Abdul Whab @ Abdul Wahab,, Zulfa

    Published 2020
    “…Overall, the spectral reflectance measurement pairing with leaf chlorophyll measurement provides a sound basis for classifying mangrove tree species (R2>80%). Mangrove loss resulting from anthropogenic activities was observed across the study area. …”
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    Hybridization of SLIC and extra tree for object based image analysis in extracting shoreline from medium resolution satellite images by Abd Manaf, Syaifulnizam, Mustapha, Norwati, Sulaiman, Md. Nasir, Husin, Nor Azura, Mohd Shafri, Helmi Zulhaidi, Razali, Mohd Norhisham

    Published 2018
    “…Thus, the object-based approach is proposed using a combination of segmentation algorithms, namely Felzenswalb, Quickshift, and SLIC, together with 15 machine learning classifiers, to classify segmented images of Langkawi Island. …”
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    Footwear quality evaluation using decision tree and logistic regression models by Tan, Swee Choon

    Published 2022
    “…The analysis showed that Decision Tree with Gini algorithm (three branches) in the first method prevails against the other methods with misclassification rate of 0.1307. …”
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    Edge assisted crime prediction and evaluation framework for machine learning algorithms by Adhikary, Apurba, Murad, Saydul Akbar, Munir, Md Shirajum, Choong Seon, Hong Seong

    Published 2022
    “…As a result, in this paper, a strategy is provided for predicting crime occurrences in a city based on historical events and demographic observation. …”
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    Water optimization technique for precision irrigation system using IoT and machine learning by Maria Manuel Vianny, D., John, A., Kumar Mohan, S., Sarlan, A., Adimoolam, Ahmadian, A.

    Published 2022
    “…The GBT is used to predict the real values based on the observations. The LSTM is used to predict, time series prediction using different observations of the surrounding. …”
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