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modeling algorithm » scheduling algorithm (Expand Search)
method algorithm » mould algorithm (Expand Search)
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161
Approximation and heuristic algorithms for computing backbones in asymmetric ad-hoc networks
Published 2018“…We consider the problem of dominating set-based virtual backbone used for routing in asymmetric wireless ad-hoc networks. …”
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162
Wild Blueberry Harvesting Losses Predicted with Selective Machine Learning Algorithms
Published 2022“…Statistical parameters i.e., mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R<sup>2</sup>), were used to assess the prediction accuracy of the models. The results of the correlation matrices showed that the blueberry yield and losses (leaf loss, blower loss) had medium to strong correlations accessed based on the correlation coefficient (r) range 0.37–0.79. …”
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163
A method for optimizing test bus assignment and sizing for system-on-a-chip
Published 2017“…We present experimental results that demonstrate the effectiveness of our method while outperforming reported techniques.…”
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conferenceObject -
164
On the protection of power system: Transmission line fault analysis based on an optimal machine learning approach
Published 2022“…The design is carried out based on the selection of the optimal model parameters using a search optimization algorithm called GridSearchCV. …”
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Correlation Clustering via s-Club Cluster Edge Deletion
Published 2023“…In certain situations, the requirement for clusters to be cliques was deemed excessively stringent, leading to the proposal of alternative relaxed clique models for dense subgraphs, such as s-club. In this work, we implement three approaches to tackle the 2-club clustering via edge deletion: a heuristic approach based on the influence of the edge to resolve maximum conflicts, a parameterized algorithm in which by deleting a maximum of k edges, the graph can be transformed into a 2-club cluster based on a branching algorithm, and the approach in Integer Linear Programming to find the optimized solution in an integer formulation. …”
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masterThesis -
167
The unified effect of data encoding, ansatz expressibility and entanglement on the trainability of HQNNs
Published 2023“…One of the prominent challenges lies in the presence of barren plateaus (BP) in QML algorithms, particularly in quantum neural networks (QNNs). …”
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168
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169
Modeling and Guidance of an Underactuated Autonomous Underwater Vehicle
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doctoralThesis -
170
Application of Machine Learning Algorithms to Enhance Money Laundering and Financial Crime Detection
Published 2011“…In order to analyze the performance of machine learning algorithms, data was provided by a bank to be used for educational purposes and shall remain undisclosed. …”
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171
UAV Trajectory Planning for Data Collection from Time-Constrained IoT Devices
Published 2019“…This motivates the utilization of unmanned aerial vehicles (UAVs) to offload traffic from existing wireless networks by collecting data from time-constrained IoT devices with performance guarantees. …”
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172
Spectral energy balancing system with massive MIMO based hybrid beam forming for wireless 6G communication using dual deep learning model
Published 2024“…In this paper, a Dual-Deep-Network technique is described for the extraction of statistical structures from a hybrid beam forming model based on mmWave logics, as well as training logic for the network map functions. …”
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173
XBeGene: Scalable XML Documents Generator by Example Based on Real Data
Published 2012“…XML datasets of various sizes and properties are needed to evaluate the correctness and efficiency of XML-based algorithms and applications. While several downloadable datasets can be found online, these are predefined by system experts and might not be suitable to evaluate every algorithm. …”
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conferenceObject -
174
A New Hamiltonian Semi-Analytical Approach to Vibration Analysis of Piezoelectric Multi-Layered Plates
Published 2024“…The whole piezoelectric multilayered plate’s dynamic stiffness is then built, from which its circular frequencies are computed with the help of the Wittrick-Williams algorithm. A detailed discussion is provided on the implementation aspects, followed by some numerical examples to assess the robustness, accuracy and effectiveness of the proposed method. …”
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175
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A Framework for Predictive Modeling in Sustainable Projects
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doctoralThesis -
177
A new family of multi-step quasi-Newton algorithms for unconstrained optimization
Published 1999“…It concentrates on deriving a variable-metric family of minimum curvature algorithms for unconstrained optimization. The derivation is based on considering a rational model, with a certain tuning parameter, where the aim is to develop a general framework that encompasses all possible two-step minimum curvature algorithms generated by appropriate parameter choices. …”
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UAV-Aided Projection-Based Compressive Data Gathering in Wireless Sensor Networks
Published 2018“…Devices in such scenarios are normally extremely energy-constrained and often exist in large numbers and can be located in hard-to-reach areas; the fact that necessitates the design and implementation of effective energy-aware data collection mechanisms. …”
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