Search Results - (( using optimization methods algorithm ) OR ( data optimisation based algorithm ))
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An improved particle swarm optimization algorithm for data classification
Published 2023“…Optimisation-based methods are enormously used in the field of data classification. …”
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Optimising cloud computing performance with an enhanced dynamic load balancing algorithm for superior task allocation
Published 2024“…Additionally, if a VM cannot meet a cloudlet's deadline, the algorithm redirects the cloudlet to a secondary data centre and reconfigures CPU resources among VMs to ensure optimal allocation. …”
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The development of parameter estimation method for Chinese hamster ovary model using black widow optimization algorithm
Published 2020“…Therefore, this paper proposed a Black Widow Optimisation (BWO) algorithm inspired by the bizarre mating behaviour of a spider as the method to use to solve the problem. …”
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Gravitational Search Algorithm Based LSTM Deep Neural Network for Battery Capacity and Remaining Useful Life Prediction With Uncertainty
Published 2025“…The proposed method is assessed using aging data from the NASA battery dataset. …”
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Predicting longitudinal dispersion coefficient using ensemble models and optimized multi-layer perceptron models
Published 2024“…This study proposes ensemble models for predicting LDC based on multilayer perceptron (MULP) methods and optimization algorithms. The honey badger optimization algorithm (HBOA), salp swarm algorithm (SASA), firefly algorithm (FIFA), and particle swarm optimization algorithm (PASOA) are used to adjust the MULP parameters. …”
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B-spline curve fitting with different parameterization methods
Published 2020“…Later, genetic algorithm and differential evolution optimization are used to optimise the error of the curve. …”
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Final Year Project / Dissertation / Thesis -
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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“…The importance values were used to compute the flood susceptibility, while Natural Breaks method was used to classify the results. …”
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Hybrid optimisation electromagnetic interference shielding effectiveness:mechanical and physical performance of plaster mortar containing palm oil fuel ash using taguchi grey and t...
Published 2019“…Six factors namely POFA admixture percentage, topcoat powder /binder ratio (TP/B), water/binder ratio (W/B), latex agent content (LA), the particle size of POFA and curing condition are used to control the nine responses. Pre-experiment data is optimized based on Taguchi-grey and Flower Pollination Algorithm (FPA) methods. …”
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Stock market turning points rule-based prediction / Lersak Photong … [et al.]
Published 2021“…From news classification and news sentiment, a rule-based algorithm was used to predict the stock market turning points. …”
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Leveraging transfer learning and label optimization for enhanced traditional Chinese medicine ner performance
Published 2024“…By retraining the model using the optimised training set, an optimal F1 measure of 92.7% was achieved. …”
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Rockfall source identification using a hybrid Gaussian mixture-ensemble machine learning model and LiDAR data
Published 2019“…Grid search method was adopted to optimise the hyperparameters of the investigated base models. …”
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Reliability assessment of power system generation adequacy with wind power using population-based intelligent search methods
Published 2017“…This study sought to examine the performance of three newly proposed techniques, for reliability assessment of the power systems, namely Disparity Evolution Genetic Algorithm (DEGA), Binary Particle Swarm Optimisation (BPSO), and Differential Evolution Optimization Algorithm (DEOA). …”
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Improving Patient Rehabilitation Performance In Exercise Games Using Collaborative Filtering Approach
Published 2024journal::journal article -
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Correlation analysis and predictive performance based on KNN and decision tree with augmented reality for nuclear primary cooling process / Ahmad Azhari Mohamad Nor
Published 2024“…Subsequently, predictive models employing k-nearest neighbour and decision tree algorithms are constructed and evaluated based on accuracy, precision, and recall metrics. …”
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Modelling and calibration of high-pressure direct injection compressed natural gas engine
Published 2021“…The MBC procedure was carried out by using the MBC Toolbox of Matlab. The calibration framework consists of the development of the data-driven model by using ANN and ECU parameters optimisation by using GA. …”
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Optimising acoustic features for source mobile device identification using spectral analysis techniques / Mehdi Jahanirad
Published 2016“…The proposed feature sets along with selected feature extraction methods from the literature are analyzed and compared by using supervised learning techniques (i.e. support vector machines, nearest-neighbor, naïve Bayesian, neural network, logistic regression, and ensemble trees classifier), as well as unsupervised learning techniques (i.e. probabilistic-based and nearest-neighbor-based algorithms). …”
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A performance comparison study of pattern recognition systems for volatile organic compounds detection / Emilia Noorsal, Muhammad Khusairi Osman and Norfadzilah Mokhtar
Published 2007“…The input and output neurons used for the three networks were 5 neurons. The optimum structure of the neural network was determined by trial and error method to obtain the optimized hidden neuron and weight values. …”
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Research Reports -
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Sustainable Management Of River Water Quality Using Artificial Intelligence Optimisation Algorithms
Published 2021“…Among the hybrid models, in terms of accuracy, the best optimisation algorithm at station 1K06 was the AMFO while the best optimisation algorithm at station 1K07 was the HPSOGA. …”
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Final Year Project / Dissertation / Thesis
