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1
Identification Of Flow Blockage Levels In Centrifugal Pump By Machine Learning
Published 2021“…SVM model with cubic kernel is preferable as the training time taken is relatively lower than Ensemble Bagged Tree due to the ensemble algorithms are more complex. …”
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2
Photogrammetric unmanned aerial vehicle for digital terrain model estimation under oil palm tree canopy area / Suzanah Abdullah
Published 2021“…Following the application of a new methodology on the real site, the result indicated the consistency of DTM values of all the algorithms at different flying heights but there were relatively small differences between all the algorithms used. …”
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3
Landslide susceptibility mapping: machine and ensemble learning based on remote sensing big data
Published 2020“…Firstly, the Flexible Discriminant Analysis (FDA) supervised learning algorithm is trained for LSM and compared against other algorithms that have been widely used for the same purpose, namely Generalized Logistic Models (GLM), Boosted Regression Trees (BRT or GBM), and Random Forest (RF). …”
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Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam
Published 2017“…In the preliminary study, the algorithm is evaluated on the four different peak models of the three EEG signals using the artificial neural network (ANN) with particle swarm optimization (PSO) as learning algorithm. …”
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5
Identification of heavy-flavour jets with the CMS detector in pp collisions at 13 TeV
Published 2018“…Heavy-flavour jet identification algorithms have been improved compared to those used previously at centre-of-mass energies of 7 and 8 TeV. …”
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6
Optimizing tree planting areas through integer programming and improved genetic algorithm
Published 2012“…Therefore, a hybrid algorithm through an incorporation of Integer Programming and Improved Genetic Algorithm was proposed for planting lining design. …”
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7
Reverse migration prediction model based on machine learning / Azreen Anuar
Published 2024“…And the third objective is to evaluate reverse migration prediction model based on machine learning analysis. For this purpose, three (3) algorithms have been assessed, namely, the Random Forest, Decision Tree, and Gradient Boosted Tree. …”
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8
A comparative analysis of four classification algorithms for university students performance detection
Published 2019“…And showing the comparison of feature selections result through decision tree, Naive Bayes, K-nearest neighbor and Artificial Neural Network classifiers algorithm. …”
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Predictive Modelling of Stroke Occurrence among Patients using Machine Learning
Published 2023“…Advanced machine learning algorithms, including logistic regression, decision trees, random forests, and support vector machines, were utilized to analyses the dataset and develop a predictive model. …”
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Fraud detection in shipping industry based on location using machine learning comparison techniques
Published 2023“…A number of popular existing algorithms were used to execute the model developed in Rapid tool such as Naïve Bayes , Neural Net , Deep Learning, Decision Tree, Logistic Regression, SVM and k-NN. …”
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Dyslexia handwriting detection using Convolutional Neural Network (CNN) algorithm / Sofea Najihah Mohd Zaki
Published 2024“…This is because CNN can automatically extract new image data from written material. The CNN model is trained and evaluated on a wide range of handwritten sample datasets. …”
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12
Recommendation System Model For Decision Making in the E-Commerce Application
Published 2024thesis::doctoral thesis -
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Vibration-based structural damage detection and system identification using wavelet multiresolution analysis / Seyed Alireza Ravanfar
Published 2017“…The location of the crack is identified by defining the damage index called relative wavelet packet entropy (RWPE). Then, the damage severities at the identified locations are assessed using genetic algorithm (GA), through defining a database to reveal the relationships between the energies obtained and damage severities. …”
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14
Area-based vs tree-centric approaches to mapping forest carbon in Southeast Asian forests from airborne laser scanning data
Published 2017“…Tree-centric modelling is appealing because it is based on summing the biomass of individual trees, but until algorithms can detect understory trees reliably and estimate biomass from crown dimensions precisely, areas-based modelling will remain the method of choice.…”
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15
An Illustration of Generalised ARMA (GARMA) Time Series Modelling of Forest Area in Malaysia.
Published 2012“…The estimation of the model was done using Hannan-Rissanen Algorithm, Whittle's Estimation and Maximum Likelihood Estimation. …”
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A hybrid deep CNN model for fast class-incremental food classification / Aymen Taher Ahmed al-Ashwal
Published 2019“…Moreover, adding new classes or new food images features has no significant consequence on the model knowledge. …”
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Prediction models of heritage building based on machine learning / Nur Shahirah Ja'afar
Published 2021“…To overcome these limitations, this research has proposed five machine learning algorithms namely Linear Regression, Lasso, Ridge, Random Forest and Decision Tree. …”
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18
Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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19
Advanced data mining techniques for landslide susceptibility mapping
Published 2021“…The indices indicated that the SVM model performed better than the other two algorithms in both training and validation datasets. …”
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Power line corridor vegetation encroachment detection from satellite images using retinanet and support vector machine
Published 2023“…In this dissertation, a new vegetation encroachment detection method was proposed by studying the feasibility of using the visible-light band of highresolution satellite images using the RetinaNet deep learning model and Support Vector Machine algorithm (SVM). …”
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