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coding algorithm » cosine algorithm (Expand Search), colony algorithm (Expand Search), scheduling algorithm (Expand Search)
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Properties of simulated annealing and genetic algorithms for mapping data to multicomputers
Published 1997“…Some user parameters are included in the objective function and are architecture- or problem-dependent parameters. The others are used in the GA and SA algorithms. The fault tolerance capability is demonstrated by mapping data to a multicomputer with some faulty processors. …”
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Performance Analysis of Artificial Neural Networks in Forecasting Financial Time Series
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doctoralThesis -
43
Scalable parallel algorithms for dynamic programming on tree decomposition. (c2017)
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masterThesis -
44
Efficient heuristic algorithms for influence propagation in social networks. (c2018)
Published 2018“…Then we introduce the notion of an influence propagation function and use it to design an efficient algorithm across all types of networks. …”
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masterThesis -
45
An enhanced k-means clustering algorithm for pattern discovery in healthcare data
Published 2015“…Mainly, we study k-means clustering algorithms on large datasets and present an enhancement to k-means clustering, which requires k or a lesser number of passes to a dataset. …”
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46
An image processing and genetic algorithm-based approach for the detection of melanoma in patients
Published 2018“…The second phase classifies lesions using a Genetic Algorithm. Our technique shows a significant improvement over other well-known algorithms and proves to be more stable on both training and testing data.…”
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Design of an innovative and self-adaptive-smart algorithm to investigate the structural integrity of a rail track using Rayleigh waves emitted and sensed by a fully non-contact las...
Published 2020“…The functioning of the algorithm was successfully tested by carrying out extensive experiments on a real rail track in the presence of different types of surface and sub-surface defects on its head and web. …”
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GIJA:Enhanced geyser‐inspired Jaya algorithm for task scheduling optimization in cloud computing
Published 2024“…To evaluate the efficacy of GIJA, extensive experiments are conducted using synthetic and real‐world datasets representative of cloud computing workloads. …”
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53
A Novel Genetic Trajectory Planning Algorithm With Variable Population Size for Multi-UAV-Assisted Mobile Edge Computing System
Published 2021“…In the first phase, a genetic algorithm (GA) with a variable population size is used to update the deployment of SPs. …”
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Integrated economic and environmental models for a multi stage cold supply chain under carbon tax regulation
Published 2017“…The structural properties for the optimal solution of the three models are identified and solution algorithms are also proposed. Upon conducting computational experiments, it turns out that the incorporation of carbon related costs, through carbon tax regulation, may call for adjusting the adopted operational policy which results in a minor increase in the operational cost. …”
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56
Evaluation of C-arm CT metal artifact reduction algorithm during intra-aneurysmal coil embolization
Published 2016“…This analysis was carried out to assess the improvements in both brain parenchyma and device visibility with MAR algorithm. Further, ground truth reference images from phantom experiments and clinical data were used for accurate assessment. …”
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Sensitivity analysis and genetic algorithm-based shear capacity model for basalt FRC one-way slabs reinforced with BFRP bars
Published 2023“…This paper aims to identify the impact of each design parameter on the shear behavior of BFRC-BFRP one-way slabs using a fractional factorial design of experiment (DOE). …”
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A dynamically turbo-charged heuristic for graph coloring. (c2018)
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masterThesis -
60
Habitat in flames: How climate change will affect fire risk across koala forests
Published 2023“…</p><p><br></p><h3>Method:</h3><p dir="ltr">The Decision Tree machine learning algorithm was applied to generate a fire susceptibility index (a measure of the potential for a given area or region to experience wildfires) using a dataset of conditioning factors, namely: altitude, aspect, rainfall, distance from rivers, distance from roads, forest type, geology, koala presence and future dietary sources, land use-land cover (LULC), normalized difference vegetation index (NDVI), slope, soil, temperature, and wind speed.…”