Variable Selection in Data Analysis: A Synthetic Data Toolkit by Mitra, Rohan

“…Variable (feature) selection plays an important role in data analysis and mathematical modeling. This paper aims to address the significant lack of formal evaluation benchmarks for feature selection algorithms (FSAs). …”
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A fast exact sequential algorithm for the partial digest problem by Mostafa M. Abbas (17058093)

“…Two types of simulated data, random and Zhang, are used to measure the efficiency of the algorithm. …”

Genetic and heuristic algorithms for regrouping service sites. (c2000) by Tabbara, Hiba

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A multi-class discriminative motif finding algorithm for autosomal genomic data. (c2015) by Wehbe, Gioia Wahib

“…Our algorithm first performs a feature selection step to define differentiable SNPs. …”
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Limiting the Collection of Ground Truth Data for Land Use and Land Cover Maps with Machine Learning Algorithms by Usman Ali (6586886)

“…The accuracy of these algorithms was assessed with standard statistical measures and ground truth data randomly collected in Prince Edward Island, Canada. …”

Using Machine Learning Algorithms to Forecast Solar Energy Power Output by Ali Jassim Lari (22597940)

“…We focused on the first 30-min, 3-h, 6-h, 12-h, and 24-h windows to gain an appreciation of the impact of forecasting duration on the accuracy of prediction using the selected machine learning algorithms. …”

Data Embedding in HEVC Video by Modifying the Partitioning of Coding Units by Shanableh, Tamer

“…The data embedding algorithm guarantees that a maximum of one partition is modified per message segment, therefore, in a given CU, either 0, 1 or 2 partitions are modified. …”
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Design of acoustic absorbing metasurfaces using a data-driven approach by Hamza Baali (14603380)

On the periodic hierarchical Chinese postman problem by Muhammed Emre Keskin (19457413)

Exam scheduling algorithms. (c1999) by Mikati, Ziad

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Graph Contraction for Mapping Data on Parallel Computers by Mansour, N.

“…Mapping data to parallel computers aims at minimizing the execution time of the associated application. …”
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Intelligent Fusion of Deep Features for Improved Waste Classification by Kashif Ahmad (12592762)

An Effective Hybrid NARX-LSTM Model for Point and Interval PV Power Forecasting by Mohamed Massaoudi (16888710)

“…Then, the stacked LSTM model, optimized by Tabu search algorithm, uses the residual error correction associated with the original data to produce a point and interval PVPF. …”

A FAMILY OF NORMALIZED LEAST MEAN FOURTH ALGORITHMS by Zerguine, Azzedine

“…In this work, a family of normalized least mean fourth algorithms is presented. Unlike the LMF algorithm, the convergence behavior of these algorithms is independent of the input data correlation statistics. …”
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Data redundancy management for leaf-edges in connected environments by Mansour, Elio

“…Although the sensed data could be useful for various applications (e.g., event detection in cities, energy management in commercial buildings), it first requires pre-processing to clean various inconsistencies (e.g., anomalies, redundancies, missing values). …”
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Correlation Clustering via s-Club Cluster Edge Deletion by Makarem, Norma

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Using genetic algorithms to optimize software quality estimation models by Azar, Danielle

“…The main contributions of this work are two evolutionary approaches to this optimization problem. In the first approach, we assume the existence of several models, and we use a genetic algorithm to combine them, and adapt them to a given data set. …”
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A hybrid heuristic approach to optimize rule based software quality estimation models. (c2008) by Korkmaz, Rita

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Novel Peak Detection Algorithms for Pileup Minimization in Gamma Ray Spectroscopy by Raad, M.W.

“…A number of parameter estimation and digital online peak localisation algorithms are being developed, including a pulse classification technique which uses a simple peak search routine based on the smoothed first derivative method, which gave a percentage error of peak amplitude of less than 1%. …”
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An image processing and genetic algorithm-based approach for the detection of melanoma in patients by Tokajian, Sima

“…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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