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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IntruSafe: a FCNN-LSTM hybrid IoMT intrusion detection system for both string and 2D-spatial data using sandwich architecture by Moutaz Alazab (17730060)

“…The IoMT manufacturers need to offer their products at a competitive price, which forces them to use simplified architecture, leaving limited and, to some extent, no scope to employ sophisticated cybersecurity algorithms. …”

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

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The automation of the development of classification models and improvement of model quality using feature engineering techniques by Sjoerd Boeschoten (17347045)

“…We demonstrated the applicability of feature engineering techniques such as data imputation, transformation (e.g., scaling, centering, etc.), and data balancing using several case studies and the proposed semi-automated framework. …”

Performance analysis and optimization of photovoltaic-thermal system with direct contact membrane distillation using metaheuristic algorithms by Faisal Maqbool (14561804)

Effective uncertain fault diagnosis technique for wind conversion systems using improved ensemble learning algorithm by Khadija Attouri (18024307)

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)

“…One of the widely used data-driven FDD methods is the Principal Component Analysis (PCA). …”

Damage assessment and recovery from malicious transactions using data dependency for defensive information warfare by Haraty, Ramzi A.

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Wind, Solar, and Photovoltaic Renewable Energy Systems with and without Energy Storage Optimization: A Survey of Advanced Machine Learning and Deep Learning Techniques by Abu Zitar, Raed

“…This paper covered the most resent and important researchers in the domain of renewable problems using the learning-based methods. Various types of Deep Learning (DL) and Machine Learning (ML) algorithms employed in Solar and Wind energy supplies are given. …”
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TIDCS: A Dynamic Intrusion Detection and Classification System Based Feature Selection by Zina Chkirbene (16869987)

“…TIDCS reduces the number of features in the input data based on a new algorithm for feature selection. …”

Exploring the Impact of Explainable Artificial Intelligence on Decision-making in Healthcare by MOHAMMAD, AHMAD HASAN

“…The development of explainable artificial intelligence (XAI) systems, which attempt to give visible and interpretable explanations for AI algorithms' judgements, is a vital part of AI in healthcare. …”
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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. …”

Energy utilization assessment of a semi-closed greenhouse using data-driven model predictive control by Farhat Mahmood (15468854)

“…The proposed method consists of a multilayer perceptron model representing the greenhouse system integrated with an objective function and an optimization algorithm. …”

Optimal scheduling algorithm for residential building distributed energy source systems using Levy flight and chaos-assisted artificial rabbits optimizer by D., Sathish Kumar

“…The impact of various electricity prices for obtaining energy from the primary grid on the system’s operating costs is examined. The efficiency of LFCARO is compared with other algorithms, and the results show that LFCARO performs better than other algorithms. …”
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Optimum Partition of Power Networks Using Singular Value Decomposition and Affinity Propagation by Maymouna Ez Eddin (21633650)

“…The proposed framework is verified on IEEE 14, 39, 118, and 2000-bus systems and compared to nine other well-known and widely used clustering techniques, including K-Means and Gaussian Mixture models. …”

Wearable Real-Time Heart Attack Detection and Warning System to Reduce Road Accidents by Muhammad E. H. Chowdhury (14150526)

“…It was observed that the linear classification algorithm was not able to detect heart attack in noisy data, whereas the support vector machine (SVM) algorithm with polynomial kernel with extended time–frequency features using extended modified B-distribution (EMBD) showed highest accuracy and was able to detect 97.4% and 96.3% of ST-elevation myocardial infarction (STEMI) and non-ST-elevation MI (NSTEMI), respectively. …”

Optimizing Multi-Drone Flight Paths in Mountainous Terrain Using Enhanced Artificial Bee Colony and Genetic Algorithms by unknown

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Performance of artificial intelligence models in estimating blood glucose level among diabetic patients using non-invasive wearable device data by Arfan Ahmed (17541309)

“…One of the key aspects of WDs with machine learning (ML) algorithms is to find specific data signatures, called Digital biomarkers, that can be used in classification or gaging the extent of the underlying condition. …”

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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