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Genetic and heuristic algorithms for regrouping service sites. (c2000)
Published 2000Get full text
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masterThesis -
42
Multilayer Reversible Data Hiding Based on the Difference Expansion Method Using Multilevel Thresholding of Host Images Based on the Slime Mould Algorithm
Published 2022“…Therefore, the smaller the difference between the selected pixels and the more correlation between two consecutive pixels, the less distortion can be achieved in the image after embedding the secret data. …”
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Haplotype inference by pure-parsimony using revamped delayed haplotype selection. (c2011)
Published 2011Get full text
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masterThesis -
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Data-driven robust model predictive control for greenhouse temperature control and energy utilisation assessment
Published 2023“…First, an analytical model based on mass and energy balance and a data-driven model based on an artificial neural network is developed, and their prediction performance is compared. …”
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A multi-class discriminative motif finding algorithm for autosomal genomic data. (c2015)
Published 2016“…Our algorithm first performs a feature selection step to define differentiable SNPs. …”
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masterThesis -
48
The effects of data balancing approaches: A case study
Published 2023“…In this research, classification algorithms, combined with resampling strategies and dimensionality reduction methods, were investigated to find a prediction model to correctly identify the samples of treated animals. …”
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Multi-class subarachnoid hemorrhage severity prediction: addressing challenges in predicting rare outcomes
Published 2025“…In the first stage, we performed binary classification, grouping SAH severity into “Good Outcome” (class 0), which includes MRS levels 0, 1, 2, and 3, and “Poor Outcome” (class 1), encompassing levels 4, 5, and 6. Feature selection was done using a Random Forest algorithm to identify the top 20 features for the SAH severity prediction. …”
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Energy utilization assessment of a semi-closed greenhouse using data-driven model predictive control
Published 2021“…The proposed method consists of a multilayer perceptron model representing the greenhouse system integrated with an objective function and an optimization algorithm. The multilayer perceptron model is trained using historical data from the greenhouse with solar radiation, outside temperature, humidity difference, fan speed, HVAC control as the input parameters to predict the temperature. …”
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TIDCS: A Dynamic Intrusion Detection and Classification System Based Feature Selection
Published 2020“…TIDCS reduces the number of features in the input data based on a new algorithm for feature selection. …”
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Using Educational Data Mining Techniques in Predicting Grade-4 students’ performance in TIMSS International Assessments in the UAE
Published 2018“…We examined different feature selection methods and classification algorithms to find the best prediction model with the highest accuracy. …”
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53
Intelligent Bilateral Client Selection in Federated Learning Using Game Theory
Published 2022“…Adopting a random selection strategy would entail substantial problems due to the heterogeneity in terms of data quality, and computational and communication resources across the participants. …”
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masterThesis -
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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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Comparative analysis of metaheuristic load balancing algorithms for efficient load balancing in cloud computing
Published 2023“…This paper provides a comparative analysis of various metaheuristic load balancing algorithms for cloud computing based on performance factors i.e., Makespan time, degree of imbalance, response time, data center processing time, flow time, and resource utilization. …”
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Genetic-Algorithm-Based Neural Network for Fault Detection and Diagnosis: Application to Grid-Connected Photovoltaic Systems
Published 2022“…This is addressed such that the genetic algorithm (GA) technique is used for selecting the best features and the artificial neural network (ANN) classifier is applied for fault diagnosis. …”
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An Effective Hybrid NARX-LSTM Model for Point and Interval PV Power Forecasting
Published 2021Subjects: