Search Results - (( data reduction methods algorithm ) OR ( data optimization mead algorithm ))
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Optimizing the SEIRD model for COVID-19 in Malaysia using pymoo framework
Published 2025“…However, the introduction of time-dependent coefficients in both models increases the number of optimization variables. To solve this, the Nelder-Mead and Pattern Search algorithms were recommended. …”
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Fitting time-varying coefficients SEIRD model to Covid-19 cases in Malaysia
Published 2023“…Nelder-Mead outperforms the other optimization algorithm with the least error. …”
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Feature and Instances Selection for Nearest Neighbor Classification via Cooperative PSO
Published 2014“…The reduction method contains two techniques, namely features reduction and data reduction which are commonly applied to a classification problem. …”
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Real-time time series error-based data reduction for internet-of-things applications
Published 2018“…There are many time series data reduction methods, ranging from primitive data aggregation such as Rate of Change to sophisticated compression algorithms. …”
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Final Year Project / Dissertation / Thesis -
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An Alternative Algorithm for Soft Set Parameter Selection using Special Order
Published 2015“…This paper proposed a parameter reduction algorithm, known as 3C algorithm, to circumvent the false frequent object in reduction. …”
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Conference or Workshop Item -
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Numerical Integration And Data Reduction For Application In Photometry
Published 2003“…In this thesis, an algorithm based on a local interpolation scheme called the Average Angle Method was developed for numerical integration and data reduction of photometric data, and in general, for any data set sharing similar characteristics as the luminous intensity data The new interpolation scheme interpolates discrete data with piecewise cubic polynomials having a CI continuity in the interior. knots. …”
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Thesis -
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Network reconfiguration and control for loss reduction using genetic algorithm
Published 2010“…In this work a feeder reconfiguration algorithm is presented for the purpose of power loss reduction in distribution networks. …”
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Then canonical Polyadic decomposition-based attribute reduction is applied to the offload-able task to reduce the data size. …”
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Classification of basal stem rot disease in oil palm using dielectric spectroscopy
Published 2018“…An analysis was done to see the effect of implementing different data reduction algorithms in classifying BSR disease. …”
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Thesis -
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An Improve k-NN Classifier using Similarity Distance Plot-Data Reduction and Dask for Big Datasets
Published 2025“…To accommodate big-scale data, the method integrates a parallel computing framework, Dask, during both the reduction and classification processes. …”
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Thesis -
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HDRA: A Haybird Data Reduction and Routing Algorithm
Published 2024“…Consequently, this study introduces a Hybrid Data Reduction and Routing Algorithm (HDRA). The principal aim of HDRA is to prolong the lifespan of clusterbased WSNs. …”
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Modelling transmission dynamics of covid-19 during Pre-vaccination period in Malaysia: a predictive guiseird model using streamlit
Published 2023“…The mathematical model is solved using Scipy odeint function, which uses Livermore Solver for Ordinary Differential Equations with an Automatic method switching (LSODA) algorithm. The time-varying coefficients of SEIRD model that best fit the real data of COVID-19 cases are obtained using the Nelder-Mead optimization algorithm. …”
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Proceeding Paper -
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HDRA: A Haybird Data Reduction and Routing Algorithm
Published 2024“…Consequently, this study introduces a Hybrid Data Reduction and Routing Algorithm (HDRA). The principal aim of HDRA is to prolong the lifespan of clusterbased WSNs. …”
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Document classification based on kNN algorithm by term vector space reduction
Published 2023Conference Paper -
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New Learning Models for Generating Classification Rules Based on Rough Set Approach
Published 2000“…Two different models for learning in data sets were proposed based on two different reduction algorithms. …”
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Thesis -
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Utilisation of Exponential-Based Resource Allocation and Competition in Artificial Immune Recognition System
Published 2011“…The experimental results show that utilizing exponential-based resource allocation methods decreases the training time and increases the data reduction capability of Artificial Immune Recognition System. …”
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Reference-free Reduction of Ballistocardiogram Artifact from EEG Data Using EMD-PCA
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Conference or Workshop Item -
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Improved clustering using robust and classical principal component
Published 2017“…We call our propose method as k-means by principal components (pc1). In this study, the kernels that are created by using the k-means method are replaced with kernels which are created by using PCA method where the PCA method reduces the dimensionality of a data. …”
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