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modeling algorithm » scheduling algorithm (Expand Search)
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The Relation Between Respiratory & Acute Coronary Syndrome Using Data Mining Techniques
Published 2018“…In this study I’ve split one dataset of patients who have attended to emergency departments in Abu Dhabi hospitals to two datasets (Respiratory and Cardiac), then applied the data mining algorithms on each dataset and one time on the original dataset. …”
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Design and Implementation of an Advanced Control and Guidance Algorithm of a Single Rotor Helicopter
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Application of updated joint detection algorithm for the analysis of drilling parameters of roof bolters in multiple joints conditions
Published 2017“…This paper reviews testing procedures, data analysis, updated algorithms used for joint detection, and discusses the latest round of testing in samples with simulated joints at various angles along the borehole.…”
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Use data Mining Techniques to Predict Users’ Engagement on the Social Network Posts in The Period Before, During and After Ramadan
Published 2017“…In this thesis, the effectiveness of using a data mining classifier helps to predict users’ engagement with a social media post before publishing and anticipating the best type of media for the post. …”
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An enhanced k-means clustering algorithm for pattern discovery in healthcare data
Published 2015“…This paper studies data mining applications in healthcare. 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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A New Parallel Genetic Algorithm Model
Published 2020“…This paper presents an implementation of three Genetic Algorithm models for solving a reliability optimization problem for a redundancy system with several failure modes, a modification on a parallel a genetic algorithm model and a new parallel genetic algorithm model. …”
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BioNetApp: An interactive visual data analysis platform for molecular expressions
Published 2019“…An ongoing challenge is to provide better tools that can mine data patterns that could not have been discovered through simple visualization. …”
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Multilayer Reversible Data Hiding Based on the Difference Expansion Method Using Multilevel Thresholding of Host Images Based on the Slime Mould Algorithm
Published 2022“…This is because placing data in an image can cause permanent distortion after data mining. …”
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Real-Time Implementation of High Performance Control Scheme for Grid-Tied PV System for Power Quality Enhancement Based on MPPC-SVM Optimized by PSO Algorithm
Published 2018“…In addition, it can be implemented in a low-cost control platform due to its simplicity. …”
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A Data-Driven Decision-Making Framework for Fleet Management in the Government Sector of Dubai
Published 2024“…The proposed framework comprises key elements: Important Decisions derived from interviews with transportation leaders, Knowledge Management enhanced by AI algorithms, Data Mining/Analysis utilizing historical data, the Fleet Management System employing Oracle ERP, and a Data-Driven Decision Support Framework that leans towards the extended framework approach. …”
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Process Mining over Unordered Event Streams
Published 2020“…This requires online algorithms that, instead of keeping the whole history of event data, work incrementally and update analysis results upon the arrival of new events. …”
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Bird’s Eye View feature selection for high-dimensional data
Published 2023“…This approach is inspired by the natural world, where a bird searches for important features in a sparse dataset, similar to how a bird search for sustenance in a sprawling jungle. BEV incorporates elements of Evolutionary Algorithms with a Genetic Algorithm to maintain a population of top-performing agents, Dynamic Markov Chain to steer the movement of agents in the search space, and Reinforcement Learning to reward and penalize agents based on their progress. …”
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A genetic-based algorithm for fuzzy unit commitment model
Published 2000“…The genetic algorithm (GA) approach is then used to solve the proposed fuzzy UCP model. …”
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UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data
Published 2024“…<p>Feature selection (FS) is a crucial technique in machine learning and data mining, serving a variety of purposes such as simplifying model construction, facilitating knowledge discovery, improving computational efficiency, and reducing memory consumption. …”