Predictive Model of Psychoactive Drugs Consumption using Classification Machine Learning Algorithms حسب Almahmood, Mothanna

"…The final model is a combination of 18 models for 18 critical psychoactive drugs: Alcohol, Amphet, Amyl, Benzos, Caff, Cannabis, Choc, Coke, Crack, Ecstasy, Heroin, Ketamine, Legalh, LSD, Meth, Mushrooms, Nicotine and VSA. …"
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Machine Learning Model for a Sustainable Drilling Process حسب Alsaidi, Ola

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A novel IoT intrusion detection framework using Decisive Red Fox optimization and descriptive back propagated radial basis function models حسب Osama Bassam J. Rabie (21323741)

"…Moreover, the DBRF classification model is deployed to categorize the normal and attacking data flows using optimized features. …"

Correlation Clustering via s-Club Cluster Edge Deletion حسب Makarem, Norma

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On-site workshop investment problem: A novel mathematical approach and solution procedure حسب Nima Moradi (19418821)

Auto-NAHL: A Neural Network Approach for Condition-Based Maintenance of Complex Industrial Systems حسب Tarek Berghout (16905132)

Convergence of Photovoltaic Power Forecasting and Deep Learning: State-of-Art Review حسب Mohamed Massaoudi (16888710)

"…With the massive smart meter integration, DL takes advantage of the large-scale and multi-source data representations to achieve a spectacular performance and high PV forecastability potential compared to classical models. …"

Enhanced PSO-Based NN for Failures Detection in Uncertain Wind Energy Systems حسب Khaled Dhibi (16891524)

"…First, a feature selection tool using PSO Algorithm is developed. Then, in order to maximize the diversity between data samples and improve the effectiveness of using PSO algorithm for feature selection, the Euclidean distance metric is used in order to reduce the data and maximize the diversity between data samples. …"

Enhanced Deep Belief Network Based on Ensemble Learning and Tree-Structured of Parzen Estimators: An Optimal Photovoltaic Power Forecasting Method حسب Mohamed Massaoudi (16888710)

Artificial intelligence-based methods for fusion of electronic health records and imaging data حسب Farida Mohsen (16994682)

"…In our analysis, a typical workflow was observed: feeding raw data, fusing different data modalities by applying conventional machine learning (ML) or deep learning (DL) algorithms, and finally, evaluating the multimodal fusion through clinical outcome predictions. …"

Interval-Valued Reduced Ensemble Learning Based Fault Detection and Diagnosis Techniques for Uncertain Grid-Connected PV Systems حسب Khaled Dhibi (16891524)

Active distribution network type identification method of high proportion new energy power system based on source-load matching حسب Qinlin, Shi

"…Firstly, the typical daily output scenarios of DG are extracted by clustering method, and the generalized load curve model is solved by the optimization algorithm to obtain the source load operation data; Secondly, calculate the source-load matching indicators (including matching performance, matching degree, and matching rate) according to the source load data of each region, and identify the distribution network type according to the range of the index values; Finally, several indicators are introduced to quantify the characteristics of different types of distribution networks. …"
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Student advising decision to predict student's future GPA based on Genetic Fuzzimetric Technique (GFT) حسب Kouatli, Issam

"…Genetic Algorithm would be used to optimize the performance of the system.…"
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Digital Image Watermarking Using Balanced Multiwavelets حسب Ghouti, L.

"…This increase could also be exploited as a side channel for embedding watermark synchronization recovery data. Finally, the analytical expressions are contrasted with experimental results where the robustness of the proposed watermarking system is evaluated against standard watermarking attacks.…"
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Development of a deep learning-based group contribution framework for targeted design of ionic liquids حسب Sadah Mohammed (18192859)

"…This computational framework can expedite and improve the process of finding desirable molecular structures of IL via accurate property predictions in a data-driven manner. Our proposed framework consists of two essential steps: establishing a correlation between IL viscosity and CO₂ solubility by merging two deep learning models (DNN-GC and ANN-GC) and utilizing this correlation to identify the optimal IL structure with maximal CO₂ absorption capacity. …"