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

“…<p>This paper introduces a pioneering fault diagnosis technique termed Interval Ensemble Learning based on Sine Cosine Optimization Algorithm (IEL- SCOA), tailored to tackle uncertainties prevalent in wind energy conversion (WEC) systems. …”

Nonlinear analysis of shell structures using image processing and machine learning by M.S. Nashed (16392961)

“…We show that the results of the trained network agree well with the results of the nonlinear finite element analysis. The proposed approach can quickly and accurately predict the mechanical behaviour of the structure using a fraction of the computational cost. …”

Evolutionary algorithm for protein structure prediction by Mansour, Nashat

“…In this paper, we present an improved genetic algorithm (GA) for predicting 3D structures of proteins based on the hydrophobic polar model. …”
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A Genetic Algorithm for Improving Accuracy of Software Quality Predictive Models by Azar, Danielle

“…In this work, we present a genetic algorithm to optimize predictive models used to estimate software quality characteristics. …”
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Scatter Search algorithm for Protein Structure Prediction by Mansour, Nashat

“…In this paper, we present a Scatter Search (SS) algorithm for predicting 3D structures of proteins based on torsion angles representation. …”
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A Study on Applying Data Mining in Airline Industry for Demand Forecasting by predicting Item Criticality by KARAM, ZAINAB HAMDAN

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Evolutionary algorithm for predicting all-atom protein structure by Mansour, Nashat

“…We present an improved version of a scatter search (SS) algorithm for predicting all-atoms protein structures using a recent energy model. …”
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Online Fuzzy Logic Base Algorithm for Electricity Price Prediction by Albayed, Moamin J.

“…This paper presents a web-based system to predict the electricity prices. …”
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Eye-Clustering: An Enhanced Centroids Prediction for K-means Algorithm by Nasser, Youssef

“…Hundreds of such labeled graphs were used to train the model to predict the location of centroids. The objective is to produce a model capable of predicting centroids with greater accuracy than the traditional random initialization used in K-means. …”
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Combining and adapting software quality predictive models by genetic algorithms by Azar, D.

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Prediction of pressure gradient for oil-water flow: A comprehensive analysis on the performance of machine learning algorithms by Md Ferdous Wahid (13485799)

“…This study aims to develop five robust machine learning (ML) algorithms and their fusions for a wide range of flow patterns (FP) regimes. …”

Leveraging Machine and Deep Learning Algorithms for hERG Blocker Prediction by Syed Mohammad (21075689)

“…The current study utilises state-of-the-art ML and DL models for predicting the hERG-blocking ability of chemical compounds using a dataset of 8337 molecules. …”

Wild Blueberry Harvesting Losses Predicted with Selective Machine Learning Algorithms by Humna Khan (17541972)

“…The performance of three machine learning (ML) algorithms was assessed to predict the wild blueberry harvest losses on the ground. …”

An ant colony optimization algorithm to improve software quality prediction models by Azar, D.

“…As a result, the prediction models built on one data set show a significant deterioration of their accuracy when they are used to classify new, unseen data. …”
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Nonlinear model predictive control of Hammerstein and Wiener modelsusing genetic algorithms by Al-Duwaish, H.

“…In this paper a novel approach for the implementation of nonlinear MPC is proposed using genetic algorithms (GAs). …”
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Prediction of EV Charging Behavior Using Machine Learning by Shahriar, Sakib

“…In both predictions, we demonstrate a significant improvement compared to previous work on the same dataset and we highlight the importance of traffic and weather information for charging behavior predictions.…”
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Predicting Dropouts among a Homogeneous Population using a Data Mining Approach by BILQUISE, GHAZALA

“…Our research reveals that the Gradient Boosted Trees is a robust algorithm that predicts dropouts with an accuracy of 79.31% and AUC of 88.4% using only pre-enrollment data. …”
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Cryptocurrency Exchange Market Prediction and Analysis Using Data Mining and Artificial Intelligence by Al Rayhi, Nasser

“…To which extend can we predict Cryptocurrency exchange market prices using well known prediction algorithms? …”
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Socially Motivated Approach to Simulate Negotiation Process by Hammadih, Mohammed Zaher

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Forecasting the nearly unforecastable: why aren’t airline bookings adhering to the prediction algorithm? by Saravanan Thirumuruganathan (11038038)

“…The resulting model achieves an 89% predictive accuracy using historical data. A unique aspect of the model is the incorporation of self-competence, where the model defers when it cannot reasonably make a recommendation. …”