Search Results - (( model evaluation ((case algorithm) OR (tree algorithm)) ) OR ( _ presentation based algorithm ))
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Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan
Published 2020“…After evaluating the results of these algorithms, a hybrid Artificial Neural Network-based Imperial Competitive Algorithm (ANN-ICA) was presented in the deployment step of the proposed methodology to identify the structural damage of illustrative structures. …”
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Modeling forest fires risk using spatial decision tree
Published 2011“…This paper presents our initial work in developing a spatial decision tree using the spatial ID3 algorithm and Spatial Join Index applied in the SCART (Spatial Classification and Regression Trees) algorithm. …”
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E2IDS: an enhanced intelligent intrusion detection system based on decision tree algorithm
Published 2022“…The model design is Decision Tree (DT) algorithm-based, with an approach to data balancing since the data set used is highly unbalanced and one more approach for feature selection. …”
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A coalition model for efficient indexing in wireless sensor network with random mobility / Hazem Jihad Ali Badarneh
Published 2021“…The proposed model consists of Dynamic-Coalition framework, Static-Coalition algorithm, and Coalition-Based Index-Tree framework. …”
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Machine learning in predicting anti-money laundering compliance with protection motivation theory among professional accountants
Published 2023“…The research elaborates on the design and implementation of machine learning models based on three algorithms: Decision Tree, Gradient Boosted Tree, and Support Vector Machine. …”
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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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Reliability of bench-mark datasets for crowd analytic surveillance
Published 2015“…The main object of this paper is to assess the challenges imposed by the databases for sudden illumination variance and effect of wavering trees. 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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Field data-based mathematical modeling by Bode equations and vector fitting algorithm for renewable energy applications
Published 2018“…This paper proposes a new modified methodology presented as a parametric technique to determine the system’s modeling equations based on the Bode plot equations and the vector fitting (VF) algorithm by fitting the experimental data points. …”
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Efficient flow-based channel assignment schemes for congestion avoidance in wireless mesh networks
Published 2016“…Several simulation scenarios and analytical model have been presented in order to evaluate and compare the proposed schemes with the existing channel assignment. …”
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Evaluation of a spacecraft attitude and rate estimation algorithm
Published 2010“…Purpose: This paper aims to present the development and performance evaluation of an attitude and rate estimation algorithm using an extended Kalman filter structure based on a body‐referenced representation of the state. …”
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Greedy-assisted teaching-learning-based optimization algorithm for cost-based hybrid flow shop scheduling
Published 2025“…However, limited attention has been given to CHFS when considering holistic cost models using efficient algorithms. This paper presents a novel Greedy-Assisted Teaching-Learning-Based Optimization (GTLBO) algorithm for CHFS. …”
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Test case generation from state machine with OCL constraints using search-based techniques / Aneesa Ali Ali Saeed
Published 2017“…Case study evaluation was conducted based on three industrial open source case studies in order to evaluate empirically the significant of the performance of the proposed method. …”
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Reliability of bench-mark datasets for crowd analytic surveillance
Published 2015“…The main object of this paper is to assess the challenges imposed by the databases for sudden illumination variance and effect of wavering trees. 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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15
Reliability of bench-mark datasets for crowd analytic surveillance
Published 2015“…The main object of this paper is to assess the challenges imposed by the databases for sudden illumination variance and effect of wavering trees. 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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Flexible window-based scheduling with critical worst case latency evaluations for real time traffic in time sensitive networks
Published 2022“…In the third part, the worst-case AVB latency under overlapping-based TT windows (AVB-OBTTW) algorithm is presented to examine the OFWOS effects on AVBlatency performance, where represents an AVB queue, i.e., { }. …”
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Modified word representation vector based scalar weight for contextual text classification
Published 2024“…Overall, this thesis presents five contributions: the proposed modified word vectors algorithm, the new contextual classification dataset named QCoC, the efficient question-type classifier based on the feed-forward neural network algorithm, the potential transferability of the presented work to other domains, and the practical implications of the presented work towards cases where computational resources are limited or costly.…”
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Modelling complex features from histone modification signatures using genetic algorithm for the prediction of enhancer region
Published 2014“…Using Genetic Algorithm, this paper presents a modelling method to generate novel logical-based features from DNA sequences enriched with H3K4mel histone signatures. …”
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Application of machine learning algorithms to predict removal efficiency in treating produced water via gas hydrate-based desalination
Published 2025“…In this context. ML algorithms provide powerful data driven means to model complex relationship within experimental datasets to improve process optimisation This study systematically evaluated several supervised ML models, including Random Forest (RF) Support Vector Machines (SVM), Ridge Regression, Lasso Regression, Decision Tree, Extra Tree Regression, Gradient Boost, and XGBoost, to predict removal efficiency in GHBD system. …”
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Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm
Published 2018“…Seven performance indexes were examined to evaluate the performance of the proposed Muskingum model integrated with IBA, with other models that were also based on the Muskingum Model with three-parameters but utilized different optimization algorithms. …”
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