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An evolutionary based features construction methods for data summarization approach
Published 2015“…Here, feature construction methods are applied in order to improve the descriptive accuracy of the DARA algorithm.This research proposes novel feature construction methods, called Variable Length Feature Construction without Substitution (VLFCWOS) and Variable Length Feature Construction with Substitution(VLFCWS), in order to construct a set of relevant features in learning relational data. …”
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Research Report -
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Landslide susceptibility mapping at VAZ watershed (Iran) using an artificial neural network model: a comparison between multilayer perceptron (MLP) and radial basic function (RBF)...
Published 2013“…Finally the landslide susceptibility maps were validated using the validation data (i.e., 30 % landslide location data that was not used during the model construction) using area under the curve (AUC) method. …”
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Research on the construction of an efficient and lightweight online detection method for tiny surface defects through model compression and knowledge distillation
Published 2024“…Finally, the concept of model compression is integrated, utilizing scaling factors in the batch normalization (BN) layer, and introducing sparse factors to perform sparse training on the network. …”
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Predicting 30-day mortality after an acute coronary syndrome (ACS) using machine learning methods for feature selection, classification and visualization
Published 2021“…Hybrid combinations of feature selection, classification and visualisation using machine learning (ML) methods have the potential for enhanced understanding and 30-day mortality prediction of patients with cardiovascular disease using population-specific data. …”
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Cluster identification and separation in the growing self-organizing map: Application in protein sequence classification
Published 2010“…We used simple k-means algorithm as a method to identify clusters in the GSOM. …”
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A Stepper Motor Design Optimization Using
Published 2005“…There is a need to fill this void in the area of small-motor design, and develop a program using Genetic Algorithms (GAs) as an approach to achieve optimization. …”
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Monograph -
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Correlation model in the adoption of E-payment services: A machine learning approach
Published 2022“…This is a novel method, as we do not need to rely on statistical analysis, rather we can automate the process of identifying important features using machine learning models. …”
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Classification of stock market index based on predictive fuzzy decision tree
Published 2005“…After constructing predictive FDT, Weighted Fuzzy Production Rules (WFPRs) are extracted from predictive FDT, and then more significant WFPR’s are mined by using similarity-based fuzzy reasoning method. …”
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Prediction of river water quality based on Artificial Neural Network / Danial Mustaqim Azmi ... [et al.]
Published 2024“…In machine learning, prediction is a method that is supported by historical data and is often used in various fields. …”
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Modeling Teacher's Integrity Using Data Mining
Published 2010“…To obtain this, a dataset from a survey conducted by Pejabat Pelajaran Daerah Langkawi is taken as case study for the model construction. The dataset called teachers's integrity dataset contain 1500 records elaborates with 25 attributes including a target class were pre-processed and then mined using directed association rule mining algorithm namely Apriori. …”
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A vision-based deep learning approach for non-contact vibration measurement using (2+1)D CNN and optical flow
Published 2025“…This paper introduces a proof-of-concept vision-based deep learning approach for vibration measurement, proposing a factorized (2+1)D Convolutional Neural Network (CNN) model to predict four vibration metrics: acceleration, velocity, displacement, and frequency, with a focus on rigid body motion. …”
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Data-driven rice yield predictions and prescriptive analytics for sustainable agriculture in Malaysia
Published 2024“…Utilizing machine learning algorithms as decision-support tools, the study analyses commonly used models—Linear Regression, Support Vector Machines, Random Forest, and Artificial Neural Networks—alongside key environmental factors such as temperature, rainfall, and historical yield data. …”
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Sound quality classification of wood used for Sarawak traditional musical instrument- Sape / Wong Tee Hao
Published 2024“…To address dataset imbalances, Synthetic Minority Oversampling Technique was used, enhancing dataset quality before training 40 machine learning classification algorithms. …”
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Enhancement processing time and accuracy training via significant parameters in the batch BP algorithm
Published 2020“…We created the dynamic learning rate and dynamic momentum factor for increasing the efficiency of the algorithm. …”
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
Published 2013“…The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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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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Prediction models of heritage building based on machine learning / Nur Shahirah Ja'afar
Published 2021“…These algorithms were developed by using prewar shophouses dataset from 2004 until 2018 based on factors of heritage properties. …”
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