An enhanced k-means clustering algorithm for pattern discovery in healthcare data by Haraty, Ramzi A.

“…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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Efficient Dynamic Cost Scheduling Algorithm for Financial Data Supply Chain by Al Sadawi, Alia

“…The primary tool used in the data supply chain is data batch processing which requires efficient scheduling. …”
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DG-Means – A Superior Greedy Algorithm for Clustering Distributed Data by Assaf, Ali

“…In this work, we present DG-means, which is a greedy algorithm that performs on distributed sets of data. …”
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Deep Learning-Based Short-Term Load Forecasting Approach in Smart Grid With Clustering and Consumption Pattern Recognition by Dabeeruddin Syed (16864260)

“…<p>Different aggregation levels of the electric grid's big data can be helpful to develop highly accurate deep learning models for Short-term Load Forecasting (STLF) in electrical networks. …”

Improved Transportation Model with Internet of Things Using Artificial Intelligence Algorithm by Ayman Khallel Al-Ani (17541447)

A Study on Applying Data Mining in Airline Industry for Demand Forecasting by predicting Item Criticality by KARAM, ZAINAB HAMDAN

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Improvement of Kernel Principal Component Analysis-Based Approach for Nonlinear Process Monitoring by Data Set Size Reduction Using Class Interval by Mohammed Tahar Habib Kaib (21633176)

“…In this paper, the proposed algorithm selects relevant observations from the original data set by utilizing a class interval technique (i.e. histogram) to maintain a bunch of representative samples from each bin. …”

Parametric Estimation From Empirical Data Using Particle Swarm Optimization Method for Different Magnetorheological Damper Models by Asan G. A. Muthalif (16888818)

Estimation of the methanol loss in the gas hydrate prevention unit using the artificial neural networks: Investigating the effect of training algorithm on the model accuracy by Haitao Xu (435549)

“…This study investigates the gradient-based, evolutionary, and Bayesian-based optimization algorithms. …”

Scalable Nonparametric Supervised Learning for Streaming and Massive Data: Applications in Healthcare Monitoring and Credit Risk by Mohamed Chaouch (17983846)

“…Additionally, an online classifier is developed for streaming data, combining online PCA with a kernel-based recursive classifier using a stochastic approximation algorithm. …”

Application of Red Deer Algorithm in Optimizing Complex functions by Zitar, Raed

“…The Red Deer algorithm (RDA), a recently developed population-based meta-heuristic algorithm, is examined in this paper with the optimization task of complex functions. …”
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Interval-Valued SVM Based ABO for Fault Detection and Diagnosis of Wind Energy Conversion Systems by Majdi Mansouri (16869885)

“…The proposed improved ABO method consists in reducing the number of samples in the training data set using the Euclidean distance and extracting the most significant features from the reduced data using ABO algorithm. …”

A Data-Driven Decision-Making Framework for Fleet Management in the Government Sector of Dubai by ALGHANEM, HANI SUBHI MOHD

“…Data-driven decision-making has become increasingly widespread and relevant across all business areas, including private and public sectors. …”
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Genetic and heuristic algorithms for regrouping service sites. (c2000) by Tabbara, Hiba

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A Survey of Data Clustering Techniques by Sobeh, Salma

“…Clustering, an unsupervised learning technique, aims to identify a specific number of clusters to effectively categorize the data through data grouping. Hence, clustering is related to many fields and is used in various applications that deal with large datasets. …”
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An Uncertainty Based Genetic Algorithm Approach for Project Resource Scheduling by ALKETBI, SAIF

“…Several nonlinear optimization models were developed for this purpose assuming uniform resource availability and sequence based project tasks. …”
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Stochastic management of hybrid AC/DC microgrids considering electric vehicles charging demands by Peng, Wang

“…In order to model the uncertainty effects, a data-driven framework based on point estimate method and support vector machine is developed. …”
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Clustering/partitioning algorithms and comparative analysis by Touma, Walid Rachid

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Detection of Depression in Arabic Social Media: A Comparison of Traditional and Modern Machine Learning Algorithms by ALSHEHHI, OMAR KHALID HAMAD

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A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT by Dhananjay Bisen (19482454)