Search Results - (( using factorization learning algorithm ) OR ( basic evaluation model algorithm ))
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1
Landslide Susceptibility Mapping with Stacking Ensemble Machine Learning
Published 2024“…One of the prominent methods to improve machine learning accuracy is by using ensemble method which basically employs multiple base models. …”
Conference Paper -
2
Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach
Published 2022“…The strategies applied showed that the final accuracy obtained through the training after implementing a modification in the algorithm is at 81% accuracy rate compared to the basic model that recorded its final accuracy at 79% accuracy rate. …”
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3
Image Splicing Detection With Constrained Convolutional Neural Network
Published 2019“…Nowadays there are many related efforts in detecting spliced images, but most of them are either feature-specific or complicated algorithms. Constrained CNN is basically a Deep Learning CNN model with its first layer weights being constrained so that it only extracts splicing manipulation features instead of object features. …”
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4
Agent-based extraction algorithm for computational problem solving
Published 2015“…Four agents have been proposed as an agent based model for CPS, which are User_Agent, PAC_Agent, IPO_Agent and Algorithm_Agent. …”
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5
Group consumers' preference recommendation algorithm model for online apparel's colour based on Kansei engineering
Published 2023“…Thus, this study took the colour design of men's plain-colour shirts as an example in China, established the basic colour calculation scale and an algorithm model of group consumers' product preferences based on Kansei Engineering and scientific mathematics, to provide new sales ideas and methods for retailers and markets online. …”
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6
Mining The Basic Reproduction Number (R0) Forecast For The Covid Outbreak
Published 2022“…Besides, the essential attributes to return the best prediction model for COVID-19 R0 remains unclear. Therefore, this study aims to identify and evaluate the attributes and parameters associated with the development of the Basic Reproduction Number, R0 models, classify the data used in existing Basic Reproduction Number R0 models, develop a predictive classification model for the Basic Reproduction Number, R0 and to assess and enhance the accuracy of the Basic Reproduction Number, R0 prediction. …”
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7
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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8
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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9
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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10
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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11
High performance hierarchical torus network
Published 2012“…The static network performances are derived from the graph model and the DCP is evaluated by using dimension-order routing and newly proposed adaptive routing algorithms under various traffic patterns. …”
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Proceeding Paper -
12
Reliability of bench-mark datasets for crowd analytic surveillance
Published 2015“…Two bench-mark databases, PETS 2010 and OTCBVS, along with our proposed dataset are evaluated using the three most popular background modelling algorithms in crowd analytic surveillance; Approximate Median Method, Gaussian Mixture Model and Codebook. …”
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13
Learning Algorithm effect on Multilayer Feed Forward Artificial Neural Network performance in image coding
Published 2007“…One of the essential factors that affect the performance of Artificial Neural Networks is the learning algorithm. …”
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14
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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15
A bayesian network approach to identify factors affecting learning of Additional Mathematics
Published 2015“…Constraint-based algorithms and score-based algorithms are used to generate the networks into several categories to compare and identify the strong relationships among the factors that affect the students’ learning of the subject. …”
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16
Reliability of bench-mark datasets for crowd analytic surveillance
Published 2015“…Two bench-mark databases, PETS 2010 and OTCBVS, along with our proposed dataset are evaluated using the three most popular background modelling algorithms in crowd analytic surveillance; Approximate Median Method, Gaussian Mixture Model and Codebook. …”
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17
Reliability of bench-mark datasets for crowd analytic surveillance
Published 2015“…Two bench-mark databases, PETS 2010 and OTCBVS, along with our proposed dataset are evaluated using the three most popular background modelling algorithms in crowd analytic surveillance; Approximate Median Method, Gaussian Mixture Model and Codebook. …”
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18
Three-term backpropagation algorithm for classification problem
Published 2006“…This algorithm utilizes two term parameters which are Learning Rate, α and Momentum Factor,β. …”
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19
Reverse migration prediction model based on machine learning / Azreen Anuar
Published 2024“…A significant way to minimize the errors is by using a machine learning approach that can predict reverse migration intelligently depending on the tested dataset. …”
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20
Multiple Objective Optimization of Green Logistics Using Cuckoo Searching Algorithm
Published 2016“…Basically, Cuckoo searching algorithm imitates the natural evolution of a population with initial solutions. …”
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