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Bootstrap-based Aggregations and their Stability in Feature Selection
Published 2022Get full text
doctoralThesis -
163
The Use of Microwave Tomography in Bone Healing Monitoring
Published 2019Get full text
doctoralThesis -
164
A Genetic Algorithm for Improving Accuracy of Software Quality Predictive Models
Published 2010“…In this work, we present a genetic algorithm to optimize predictive models used to estimate software quality characteristics. …”
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A Modified Oppositional Chaotic Local Search Strategy Based Aquila Optimizer to Design an Effective Controller for Vehicle Cruise Control System
Published 2023“…We construct a novel and efficient metaheuristic algorithm by improving the performance of the Aquila Optimizer via chaotic local search and modified opposition-based learning strategies and use it as an excellently performing tuning mechanism. …”
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167
Machine Learning-based X-Ray Projection Interpolation for Improved 4D-CBCT Reconstruction
Published 2024“…Respiration-correlated cone-beam computed tomography (4D-CBCT) is an X-ray-based imaging modality that uses reconstruction algorithms to produce time-varying volumetric images of moving anatomy over a cycle of respiratory motion. …”
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168
Gas Metal Arc Welding (GMAW) Process Optimization Using Machine Learning Models
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doctoralThesis -
169
Machine learning based approaches for intelligent adaptation and prediction in banking business processes. (c2018)
Published 2018“…Moreover, we propose in this thesis a Deep Learning Based Approach to Predict Non-Performing Loans. …”
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masterThesis -
170
High-Accurate Parameter Identification of PEMFC Using Advanced Multi-Trial Vector-Based Sine Cosine Meta-Heuristic Algorithm
Published 2025“…The trigonometric function-based sine cosine algorithm (SCA) may solve such problems, but it traps in local optima, making it inappropriate for larger optimization tasks. …”
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Active distribution network type identification method of high proportion new energy power system based on source-load matching
Published 2023“…Here, we report an active distribution network type identification method based on source-load matching. Firstly, the typical daily output scenarios of DG are extracted by clustering method, and the generalized load curve model is solved by the optimization algorithm to obtain the source load operation data; Secondly, calculate the source-load matching indicators (including matching performance, matching degree, and matching rate) according to the source load data of each region, and identify the distribution network type according to the range of the index values; Finally, several indicators are introduced to quantify the characteristics of different types of distribution networks. …”
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172
Decision trees
Published 2026“…An overview of the basic theory behind decision trees coupled with a summary of binary, multi-way, robust, and optimal decision tree algorithms support social scientists in the use of these supervised machine learning tools for both exploratory and predictive analytic contexts.…”
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A Novel Non-Invasive Estimation of Respiration Rate From Motion Corrupted Photoplethysmograph Signal Using Machine Learning Model
Published 2021“…Gaussian Process Regression (GPR) with Fit a Gaussian process regression model (Fitrgp) feature selection algorithm outperformed all other combinations and exhibits a root mean squared error (RMSE), mean absolute error (MAE), and two-standard deviation (2SD) of 2.63, 1.97, and 5.25 breaths per minute, respectively. …”
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Improved prairie dog optimization algorithm by dwarf mongoose optimization algorithm for optimization problems
Published 2023“…The proposed method is based on enhancing the search process of the Prairie Dog Optimization Algorithm (PDOA) by using the primary updating mechanism of the Dwarf Mongoose Optimization Algorithm (DMOA). …”
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177
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Auto-indexing Arabic texts based on association rule data mining. (c2015)
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masterThesis -
179
Blue collar laborers’ travel pattern recognition: Machine learning classifier approach
Published 2021“…The research methodology undertaken in this paper comprises a combination of different machine learning techniques, predominantly by applying clustering and classification methods. …”
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StackDPPred: Multiclass prediction of defensin peptides using stacked ensemble learning with optimized features
Published 2024“…In this paper, we aim to propose a novel multi-class ensemble-based prediction model called StackDPPred for identifying the properties of DPs. …”