Kernel-Ridge-Regression-Based Randomized Network for Brain Age Classification and Estimation حسب Raveendra Pilli (21633287)

Predicting the Heats of Fusion of Ionic Liquids via Group Contribution Modeling and Machine Learning حسب Zeinab, Samira Jihad

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Phased Array Technique for Brain Source Localization حسب Zarghami, Tahereh

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Optimum sensors allocation for drones multi-target tracking under complex environment using improved prairie dog optimization حسب Abu Zitar, Raed

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Data mining approach to predict student's selection of program majors حسب SIDDARTHA, SHARMILA

"…The approach includes a methodology to manage data mining projects, sampling techniques to handle imbalanced data and multiclass data, a set of classification algorithms to predict and measures to evaluate performance of models. …"
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Deep Learning in Smart Grid Technology: A Review of Recent Advancements and Future Prospects حسب Mohamed Massaoudi (16888710)

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

Sentiment Analysis of Dialectal Speech: Unveiling Emotions through Deep Learning Models حسب EZZELDIN, KHALED MOHAMED KHALED

"…These features are then classified using a range of Deep Learning Models, including convolutional neural networks (CNN), bidirectional long-short-term memory (BI-LSTM), gated recurrent units (GRU), and Artificial Neural Networks (ANNs). …"
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Investigating the Use of Machine Learning Models to Understand the Drugs Permeability Across Placenta حسب Vaisali Chandrasekar (16904526)

"…Several dataset analysis models are utilised to study the data diversity. Further, this study demonstrates the application of neural network-based models to effectively predict the permeability. …"

Random vector functional link network: Recent developments, applications, and future directions حسب A.K. Malik (16003193)

"…RVFL model has several characteristics such as fast training speed, direct links, simple architecture, and universal approximation capability, that make it a viable randomized neural network. …"

Artificial Intelligence for Skin Cancer Detection: Scoping Review حسب Abdulrahman Takiddin (14153181)

"…Hence, to aid in diagnosing skin cancer, artificial intelligence (AI) tools are being used, including shallow and deep machine learning–based methodologies that are trained to detect and classify skin cancer using computer algorithms and deep neural networks.</p><h3>Objective</h3><p dir="ltr">The aim of this study was to identify and group the different types of AI-based technologies used to detect and classify skin cancer. …"

Using artificial bee colony to optimize software quality estimation models. (c2015) حسب Abou Assi, Tatiana Antoine

"…Such models are mainly constructed by either statistical techniques such as regression, or machine learning techniques such as C4.5 and neural networks. …"
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Utilization of AI to Predict Shear Strength Parameters of Soil Based on Their Physical Properties حسب AbdulGhafour, Husaen

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PROVOKE: Toxicity trigger detection in conversations from the top 100 subreddits حسب Hind Almerekhi (7434776)

"…Before finding toxicity triggers, we built and evaluated various machine learning models to detect toxicity from Reddit comments. Subsequently, we used our best-performing model, a fine-tuned Bidirectional Encoder Representations from Transformers (BERT) model that achieved an area under the receiver operating characteristic curve (AUC) score of 0.983 to detect toxicity. …"

Multi Agent Reinforcement Learning Approach for Autonomous Fleet Management حسب Alhusin, Mohammed Omer Alamin

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Salak Image Classification Method Based Deep Learning Technique Using Two Transfer Learning Models حسب Theng, Lau Wei

"…Deep learning is the most promising algorithm compared to another Machine Learning (ML) algorithm. …"
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Novel hybrid informational model for predicting the creep and shrinkage deflection of reinforced concrete beams containing GGBFS حسب Iman Faridmehr (14150616)

"…After 150 days, the average creep deflection of RC beams containing 20, 40, and 60% GGBFS was 30, 70, and 100% higher than the ones for conventional concrete beams, respectively. A hybrid artificial neural network coupled with a metaheuristic Whale optimization algorithm has been developed to estimate the overall deflection of concrete beams due to creep and shrinkage. …"

Development of Machine Learning Models for Studying the Premixed Turbulent Combustion of Gas-To-Liquids (GTL) Fuel Blends حسب Abdellatif M. Sadeq (16931841)

"…The k-fold cross-validation technique is used for model training, and the developed neural network-based model is used to investigate the effects of operating parameters on the premixed turbulent flames. …"

An efficient claim management assurance system using EPC contract based on improved monarch butterfly optimization models حسب K. Mukilan (22224793)

"…To address these challenges, a claim management system is developed based on the Improved Monarch Butterfly Optimization Algorithm (IMBOA) and the principles of EPC. Conventional construction models typically optimize only a single objective, such as time, cost, or delay, which may not effectively enhance overall performance. …"

A depth-controlled and energy-efficient routing protocol for underwater wireless sensor networks حسب Umesh Kumar Lilhore (17727684)

"…The proposed model also utilized an enhanced back propagation neural network for data fusion operation, which is based on multi-hop system and also operates a highly optimized momentum technique, which helps to choose only optimum energy nodes and avoid duplicate selections that help to improve the overall energy and further reduce the quantity of data transmission. …"