A novel hybrid methodology for fault diagnosis of wind energy conversion systems by Khaled Dhibi (16891524)

“…The proposed technique involved two major steps: feature selection and fault classification. Feature selection pre-processing is an important step to increase the accuracy of the classification algorithm and decrease the dimensionality of a dataset. …”

A Digital DNA Sequencing Engine for Ransomware Analysis using a Machine Learning Network by KHAN, FIROZ

“…The proposed work contains three significant phases: Preprocessing and Feature Selection, DNA Sequence Generation and Ransomware Detection. …”
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An Effective Fault Diagnosis Technique for Wind Energy Conversion Systems Based on an Improved Particle Swarm Optimization by Majdi Mansouri (16869885)

“…First, an efficient feature selection algorithm based on particle swarm optimization (PSO) is proposed. …”

The Role of Artificial Intelligence in Decoding Speech from EEG Signals: A Scoping Review by Uzair Shah (15740699)

“…The most prominent ML algorithm was a support vector machine, and the DL algorithm was a convolutional neural network. …”

Electric Vehicles Charging Station Load Forecasting Integration With Renewable Energy Using Novel Deep EfficientBiLSTMNet by Vineet Dhanawat (22361395)

“…To guarantee accuracy and uniformity, the data is preprocessed by addressing missing values and ensuring consistency. A hybrid feature selection technique integrates the Boruta algorithm and SHAP (SHapley Additive exPlanations) values to ensure robust feature selection. …”

Enhanced DC Microgrid Protection: a Neural Network and Wavelet Transform Approach by El Gohary, Youssef Hesham

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A 3-D vision-based man-machine interface for hand-controlled telerobot by Al-Mouhamed, M.A.

“…Two digital cameras are used to monitor a four-ball-based feature frame that is held by the operator hand. To determine the three-dimensional (3-D) position a tracking algorithm based on uncalibrated cameras with weak perspective projection model is used. …”
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Using Educational Data Mining Techniques in Predicting Grade-4 students’ performance in TIMSS International Assessments in the UAE by SHWEDEH, FATEN

“…We examined different feature selection methods and classification algorithms to find the best prediction model with the highest accuracy. …”
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Improving multilayer perceptron neural network using two enhanced moth-flame optimizers to forecast iron ore prices by Ahmed, Basem

“…We use a large number of features to predict the iron ore price, and we select a promising set of features using two feature reduction methods: Pearson’s correlation and a newly proposed categorized correlation. …”
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Machine learning based approaches for intelligent adaptation and prediction in banking business processes. (c2018) by Tay, Bilal M.

“…Compared to the literature, the proposed model embeds a new feature selection method and offers higher detection accuracy, which helps lenders and financial institutions to better manage their lending activities and loan monitoring processes.…”
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A conjugate self-organizing migration (CSOM) and reconciliate multi-agent Markov learning (RMML) based cyborg intelligence mechanism for smart city security by S. Shitharth (12017480)

“…Then, the Conjugate Self-Organizing Migration (CSOM) optimization algorithm is deployed to select the most relevant features to train the classifier, which also supports increased detection accuracy. …”

Optimizing ADWIN for Steady Streams by Moharram, Hassan

“…Over time, several drift detection approaches have been proposed. A prominent approach is adaptive windowing (ADWIN) which can detect changes in features data distribution without explicit feedback on the correctness of the prediction. …”
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Perceived Information Assurance in Conversational Systems by Alghannam, Bareeq

“…Feature selection demonstrated that comparable performance (96.76% accuracy) could be maintained with only 19 optimally selected features, representing an 83.8% reduction in model complexity. …”
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Exploratory risk prediction of type II diabetes with isolation forests and novel biomarkers by Yousef, Hibba

“…In particular, Isolation Forest (iForest) was applied as an anomaly detection algorithm to address class imbalance. iForest was trained on the control group data to detect cases of high risk for T2DM development as outliers. …”
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Local convexity preserving rational cubic spline curves by Sarfraz, M.

“…An algorithm is presented which constructs a curve by interpolating the given data points. …”
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Learning-Based Automatic Modulation Classification by Abdelmutalab, Ameen Elsiddig

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Regression testing C# programs. (c2007) by Staitieh, Wael

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ADD. (c2002) by Varjabedian, Ralph A.

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Investigating the Impact of Skylights and Atrium Configurations on Visual Comfort and Daylight Performance in Dubai Shopping Malls by SANAD, AYMAN ADEL AHMED

“…Annual simulations are used to assess seasonal variations, while sensitivity analysis identifies key parameters. A genetic algorithm and multi-objective optimisation (MOO) simulations are used to generate optimal configurations, summarised in the form of a Pareto front selection criteria guide the choice of the optimum solution, which is then applied and analysed in a case study. …”
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Enhancing multilayer perceptron neural network using archive-based harris hawks optimizer to predict gold prices by Abu Doush, Iyad

“…This proves the viability of the proposed AHHO-NN model as well as the proper selection of the primitive input features.…”
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