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    CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING by ISLAM, BADAR UL ISLAM

    Published 2017
    “…The solution set (i.e. optimized weight/bias matrix of ANN) provided by the optimized and improved genetic algorithm and modified BP based model is extracted and used in the design and development of a prototype device of the proposed model. …”
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    Thesis
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    Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm by Reza M.S., Hannan M.A., Mansor M., Ker P.J., Rahman S.A., Jang G., Mahlia T.M.I.

    Published 2025
    “…In addition, to validate the prediction performance of the proposed LSA + LSTM model, extensive comparisons are performed with other popular optimization-based deep learning methods including artificial bee colony (ABC) based LSTM (ABC + LSTM), gravitational search algorithm (GSA) based LSTM (GSA + LSTM), and particle swarm optimization (PSO) based LSTM (PSO + LSTM) model using different error matrices. …”
    Article
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    Zero root-mean-square error for single- and double-diode photovoltaic models parameter determination by Mohammed Ridha, Hussein, Hizam, Hashim, Mirjalili, Seyedali, Othman, Mohammad Lutfi, Ya’acob, Mohammad Effendy

    Published 2022
    “…In this work, a new improved arithmetic optimization method based on the adaption of Newton–Raphson and Levenberg–Marquardt damping parameter (IAOANRaLMp) is presented to globally extract the parameter of the single- and double-diode PV models. …”
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    Improved power output forecastingtechnique for effective battery management in photovoltaic system / Utpal Kumar Das by Utpal, Kumar Das

    Published 2019
    “…A PSO-based algorithm is adopted for the appropriate selection of dominated parameters of SVR-based model to achieve better performance. …”
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    Thesis
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    Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images by Adil Humayun, Khan

    Published 2024
    “…For segmentation, the first proposed algorithm is based on the boundary condition model, which is tested over the ISIC dataset and achieved 96% of accuracy. …”
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    Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…Also, self-adaptive scaling factor and crossover probability control parameters are introduced to diminish time of finding an optimal parameter to produce the best population. …”
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    Development of a multi criteria decision support system using convolutional neural network and jaya algorithm for water resources management / Chong Kai Lun by Chong , Kai Lun

    Published 2021
    “…The proposed approach can be furthered categorized into two distinct stages: forecasting modeling and optimization modeling. Artificial neural network (ANN) has been widely used in forecasting tasks. …”
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    Estimating Missing Precipitation to Optimize Parameters for Prediction of Daily Water Level Using Artificial Neural Network by Dayang Suhaila, Awang Suhaili

    Published 2006
    “…The back propagation algorithm was adopted for this study. The optimal model for predicting missing data found in this study is the network with the combination of learning rate and the number of neurons in the hidden layer of 0.2 and 60. …”
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    Final Year Project Report / IMRAD
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    Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines by Aker, Elhadi Emhemed Alhaaj Ammar

    Published 2020
    “…The BayesNet provides the best integrated MLADR fault classifier model better at a 5 % significance level than other deployed algorithms in the intelligent supervised learning model realization. …”
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    Context enrichment framework for sentiment analysis in handling word ambiguity resolution by Yusof, Nor Nadiah

    Published 2024
    “…Word prior-polarity extraction is facilitated by the utilization of dictionary lexicons with predefined sentiment scores. …”
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    Implementation of machine learning techniques with big data and IoT to create effective prediction models for health informatics by Zamani, Abu Sarwar, Hassan Abdalla Hashim, Aisha, Shatat, Abdallah Saleh Ali, Akhtar, Md. Mobin, Rizwanullah, Mohammed, Mohamed, Sara Saadeldeen Ibrahim

    Published 2024
    “…In the map phase, the statisticalfeatures and the Principal Component Analysis (PCA) features are extracted. In the reduction phase, the optimal features are selected with theaid of the developed Hybrid Flower Pollination Bumblebees Optimization Algorithm (HFPBOA). …”
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    Hybrid indoor positioning utilizing multipath- assisted fingerprint and geometric estimation for single base station systems by Manap, Zahariah

    Published 2025
    “…The key attributes that establish the classification learning sessions are the channel parameters extracted from the ray tracing generated multipath signals. …”
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    Real-time oil palm fruit bunch ripeness grading system using image processing techniques by Alfatni, Meftah Salem M.

    Published 2013
    “…These results are optimal based on the thorns model. A new approach was developed using expert rules-based system. …”
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    Individual-tree segmentation and extraction based on LiDAR point cloud data by Liu, Xiaofeng, Abdullah, Muhamad Taufik, Mustaffa, Mas Rina, Nasharuddin, Nurul Amelina

    Published 2024
    “…The objective was to identify the optimal parameters for both algorithms in terms of tree height extraction precision. …”
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    Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems by Kek, Sie Long

    Published 2011
    “…Instead of solving the original optimal control problem, the model-based optimal control problem is solved. …”
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    Modeling and optimization of cost-based hybrid flow shop scheduling problem using metaheuristics by Ullah, Wasif, Mohd Fadzil Faisae, Ab Rashid, Muhammad Ammar, Nik Mu’tasim

    Published 2023
    “…Besides this, CPU time for PSO was very high compared to other algorithms. In the future, other optimization algorithms will be tested for the CHFS model, such as Teaching Learning Based Optimization (TLBO) and the Crayfish Optimization Algorithm (COA).…”
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