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Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Pr...
Published 2024“…In this study, we used extreme learning machine (ELM)-multi-kernel least square support vector machine (ELM-MKLSSVM), extreme learning machine (ELM)-LSSVM-polynomial kernel function (PKF) (ELM-LSSVM-PKF), ELM-LSSVM-radial basis kernel function (RBF) (ELM-LSSVM-RBF), ELM-LSSVM-Linear Kernel function (LKF), ELM, and MKLSSVM models to predict water level. …”
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A comparative analysis of machine learning algorithms for diabetes prediction
Published 2024“…This study focuses on comparing the performance of three machine learning algorithms, namely Naive Bayes (NB), Support Vector Machines (SVM), and Random Forest (RF), in predicting diabetes using two datasets: Pima Indians Diabetes Dataset (PIDD) and the Diabetes 2019 Dataset (DD2019), and the need to identify the most accurate and effective algorithm for diabetes prediction. …”
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Stock price monitoring system
Published 2024“…Consequently, Root Mean Squared Error (RMSE) and Mean Absolute Percentage Error (MAPE) are used to evaluate the performance of the prediction algorithms. …”
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Final Year Project / Dissertation / Thesis -
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A deep reinforcement learning hybrid algorithm for the computational discovery and characterization of small proteins utilizing mycobacterium tuberculosis as a model
Published 2025“…This study presents the development and evaluation of a novel hybrid machine learning algorithm that integrates the strengths of Random Forest and Gradient Boosting models to enhance the prediction of smORFs. …”
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Adaptive model predictive control based on wavelet network and online sequential extreme learning machine for nonlinear systems
Published 2015“…The WNMPC is developed by a proposed algorithm named adaptive updating rule (AUR) used with gradient descent optimization method to minimize a constrained cost function over the prediction and control horizons and to offer a robust control performances. …”
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Pso-svr algorithm for accurate ZnO energy band gap prediction
Published 2025“…An artificial algorithm using a machine learning approach could be used to determine the energy band gap, Eg which would simply the process of synthesizing ZnO properties. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…The fitness function used is the correlation function in the SKF algorithm to optimize the cipher image produced using the Lorenz system. …”
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A study on regional GDP forecasting analysis based on radial basis function neural network with genetic algorithm (RBFNN-GA) for Shandong economy
Published 2022“…This study uses the genetic algorithm radial basis, neural network model, to make judgments on the relationships contained in this sequence and compare and analyze the prediction effect and generalization ability of the model to verify the applicability of the genetic algorithm radial basis, neural network model, based on the modeling of historical data, which may contain linear and nonlinear relationships by itself, so this study uses the genetic algorithm radial basis, neural network model, to make, compare, and analyze judgments on the relationships contained in this sequence.…”
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Prediction of Remaining Useful Life (RUL) in Refinery using Deep Learning
Published 2019“…It will significantly help the oil and gas industry to schedule a replacement or maintenance before the machines end its operation. The project is developed using Deep Learning algorithm which the functionality can be found in KNIME Analytic application. …”
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Final Year Project -
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Random forest algorithm for co2 water alternating gas incremental recovery factor prediction
Published 2020“…The aim of this paper is using an ensemble machine learning algorithm to develop a WAG incremental recovery factor predictive model that can be used by reservoir engineers to estimate WAG incremental recovery factor prior kick-off of laboratory experiments and comprehensive technical studies. …”
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Sustainable Management Of River Water Quality Using Artificial Intelligence Optimisation Algorithms
Published 2021“…Least Square Support Vector Machine (LSSVM) base models with linear kernel, polynomial kernel and Radial Basis Function (RBF) kernel and its hybrid models with integration of Hybrid of Particle Swarm Optimisation and Genetic Algorithm (HPSOGA), Whale Optimisation Algorithm based on Self-adapting Parameter Adjustment and Mix Mutation Strategy (SMWOA) and Ameliorative Moth Flame Optimisation (AMFO) were developed and used to predict the WQI at stations 1K06, 1K07 and 1K08 of the Klang River in Selangor, Malaysia. …”
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Prediction of lattice constant of pyrochlore compounds using optimized machine learning model
Published 2023“…Three different kernel functions were used in PSO-SVR (Linear, Polynomial, and RBF kernel) shows that PSO-SVR algorithm with RBF function had better accuracy than other kernel functions. …”
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Development of an intelligent system using Kernel-based learning methods for predicting oil-palm yield.
Published 2005“…The proposed algorithm can effectively handle noise, outliers and auto-correlation in the spatial data, for effective and efficient data analysis by exploring patterns and structures in the data, and thus can be used for predicting oil-palm yield by analyzing various factors affecting oil-palm yield.…”
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Age And Gender Recognition Mobile App
Published 2023“…Therefore, this study aimed to develop age and gender recognition mobile application using deep learning algorithm. …”
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Final Year Project Report / IMRAD -
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An Evaluation of Machine Learning Algorithms for Missing Values Imputation
Published 2019“…The purpose of our review article is to focus on the developments of current techniques. For scientists rather applying different or newly develop algorithms with the identical functional goal. …”
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Sentiment Analysis on COVID-19 Vaccine Tweets using Machine Learning and Deep Learning Algorithms
Published 2023“…Machine learning algorithms like Logistic Regression, Naïve Bayes, Support Vector Machine (SVM) and others, and Deep Learning algorithms like LSTM and Bert were used to train the predictive models. …”
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The predictive machine learning model of a hydrated inverse vulcanized copolymer for effective mercury sequestration from wastewater
Published 2024“…A predictive machine learning model was also developed to predict the amount of mercury removed () using GPR, ANN, Decision Tree, and SVM algorithms. …”
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Implementation of machine learning algorithms for streamflow prediction of Dokan dam
Published 2023“…This study aims at comparing the application of deep learning algorithms and conventional machine learning algorithms for predicting reservoir inflow. …”
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A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani
Published 2016“…Many researchers, who have developed methods and algorithms within the field of artificial intelligence, machine learning and data mining, have addressed extracting useful information from the data. …”
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