Search Results - (( data optimization _ algorithm ) OR ( using factorization machine algorithm ))
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Optimization of chest X-ray exposure factors using machine learning algorithm
Published 2023“…In this study, the chest X-ray exposure factors for 178 patients with different body mass index (BMI) values have been analyzed using the Python Machine Learning algorithm. …”
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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“…The study also introduces a novel optimization algorithm for selecting inputs. While the LSSVM model may not capture nonlinear components of the time series data, the extreme learning machine (ELM) model�MKLSSVM model can capture nonlinear and linear components of the time series data. …”
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Predicting longitudinal dispersion coefficient using ensemble models and optimized multi-layer perceptron models
Published 2024Subjects:Article -
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Differential Search Optimized Random Forest Regression Algorithm for State of Charge Estimation in Electric Vehicle Batteries
Published 2023Conference Paper -
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Real-Time State of Charge Estimation of Lithium-Ion Batteries Using Optimized Random Forest Regression Algorithm
Published 2024“…This paper presents an improved machine learning approach for the accurate and robust state of charge (SOC) in electric vehicle (EV) batteries using differential search optimized random forest regression (RFR) algorithm. …”
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Successor selection for Ant Colony Optimization technique algorithm / Muhammad Iskandar Isman
Published 2017“…ACO algorithm is the best solution because it included the optimization technique to optimized the result based on the data criteria needs. …”
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network
Published 2018“…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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Optimal network reconfiguration and intelligent service restoration prediction technique based on Cuckoo search spring algorithm / Mohamad Izwan Zainal
Published 2022“…These output data are analysed to present the optimal prediction output of service restoration using Cuckoo Search Spring – Least Square Support Vector Machine (CSS-LSSVM). …”
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Breast Cancer Prediction Model Using Machine Learning
Published 2021“…Modelling with machine learning is done by selecting three candidate algorithms, namely Random Forest, Support Vector Machine, and Logistic Regression. …”
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Investigating optimal smartphone placement for identifying stairs movement using machine learning
Published 2023“…The data was trained against 6 machine learning algorithms namely Decision Tree, Logistic Regression, Naive Bayes, Random Forest, Neural Networks and KNN. …”
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Malware Classification and Detection using Variations of Machine Learning Algorithm Models
Published 2025“…Types of attacks can be Ping of Death, flooding, remote-controlled attacks, UDP flooding, and Smurf Attacks. Attack data was obtained from the ClaMP dataset, which has an unbalanced data set, and has very high noise, so it is necessary to analyze data packets in network logs and optimize feature extraction which is then analyzed statistically with machine learning algorithms. …”
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Flood mapping based on novel ensemble modeling involving the deep learning, Harris Hawk optimization algorithm and stacking based machine learning
Published 2025“…In this regard 12 flood predictors, 205 flood and 205 non-flood locations were used as input data into the following 3 complex models: Deep Learning Neural Network-Harris Hawk Optimization-Index of Entropy (DLNN-HHO-IOE), Multilayer Perceptron-Harris Hawk Optimization-Index of Entropy (MLP-HHO-IOE) and Stacking ensemble-Harris Hawk Optimization-Index of Entropy (Stacking-HHO-IOE). …”
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IOT-based fertigation system / Mohamad Amir Furqan Darus
Published 2024“…Advanced algorithms and machine learning processes this data to determine the ideal irrigation and fertilization needs. …”
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Theory-guided machine learning for predicting and minimising surface settlement caused by the excavation of twin tunnels / Chia Yu Huat
Published 2024“…This is due to the data generated from the numerical model possess the pattern for the ML algorithm ease of prediction. …”
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Optimized Load Balancing based Task Scheduling in Cloud Environment
Published 2014“…In addition, the salient feature of this algorithm is to optimize node available throughput dynamically using MatLab10A software. …”
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A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification
Published 2023“…The performance of the proposed SCSO algorithm was compared with six state-of-the-art and recent wrapper-based optimization algorithms using the validation metrics of classification accuracy, optimum feature size, and computational cost in seconds. …”
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Investigation on the dynamic of computation of semi autonomous evolutionary computation for syntactic optimization of a set of programming codes
Published 2007“…In order to have a realistic characteristic of a parallel computing engine, a Rocks based computer cluster was built and used for the test. Genetic Algorithm as one of the Evolutionary Computation method improve the execution of parallel programming codes by optimizing the number of processors and the distribution of data. …”
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Development of optimized damage prediction method for health monitoring of ultra high performance fiber-reinforced concrete communication tower
Published 2018“…Therefore, this study aims to develop a new health monitoring system for communication towers based on AdaBoost, Bagging, and RUSBoost algorithms as hybrid algorithm, which can predict the damage by using noisy, random, unstable, and skewed frequency data with high accuracy. …”
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Modeling and validation of base pressure for aerodynamic vehicles based on machine learning models
Published 2023“…The data for training and testing the algorithms was derived using the regression equation developed using the Box-Behnken Design (BBD). …”
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Modelling of optimized hybrid debris flow using airborne laser scanning data in Malaysia
Published 2019“…The general objective of the study was the development of optimized hybrid debris flow models using airborne laser scanning data and Machine learning algorithms in Malaysia. …”
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