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

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A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT حسب Dhananjay Bisen (19482454)

"…This research proposed a hybrid model for energy-efficient cluster formation and a head selection (E-CFSA) algorithm based on convolutional neural networks (CNNs) and a modified k-mean clustering (MKM) method for MEC. …"

Studying cooperative multi-agent reinforcement learning in networks حسب Oudah, Mayada Mohamed

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Multi-Agent Learning of Strategies in Abstract Argumentation Mechanisms حسب Nemer, Rama

"…The importance of this kind of work lies in the fact that it combines two aspects of multi-agent systems that have been quite separate to-date: argumentation protocols and multi-agent learning in games.…"
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A neural networks algorithm for data path synthesis حسب Harmanani, Haidar M.

"…The algorithm is driven by a motion equation that determines the neurons firing conditions based on the modified Hopfield neural network model of computation. …"
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Single channel speech denoising by DDPG reinforcement learning agent حسب Sania Gul (18272227)

"…In this paper, a novel SD algorithm is presented based on the deep deterministic policy gradient (DDPG) agent; an off-policy reinforcement learning (RL) agent with a continuous action space. …"

A Parallel Neural Networks Algorithm for the Clique Partitioning Problem حسب Harmanani, Haidar M.

"…In this paper we present a parallel algorithm to solve the above problem for arbitrary graphs using a Hopfield Neural Network model of computation. …"
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A Neural Networks Algorithm for the Minimum Colouring Problem Using FPGAs† حسب Harmanani, Haidar

"…The proposed algorithm has a time complexity of O(1) for a neural network with n vertices and k colours. …"
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Estimation of the methanol loss in the gas hydrate prevention unit using the artificial neural networks: Investigating the effect of training algorithm on the model accuracy حسب Haitao Xu (435549)

"…Adjusting the weight and bias of the ANN model using an optimization algorithm is known as the training process. …"

Enhancing Breast Cancer Diagnosis With Bidirectional Recurrent Neural Networks: A Novel Approach for Histopathological Image Multi-Classification حسب Rajendra Babu Chikkala (22330876)

"…The BRNN model, refined using the Adagrad optimization algorithm, efficiently integrates the learned features from both branches. …"

Detecting COVID-19 From Lung Computed Tomography Images: A Swarm Optimized Artificial Neural Network Approach حسب S. Punitha (17945654)

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Experimental evaluation of multi-agent reinforcement learning in real-world scale-free networks حسب Al Hashimi, Rashid

"…However, the study and analysis of the state-of-the-art multi-agent reinforcement learning (MARL) algorithms have been limited to small problems involving few number of learning agents.The purpose of this project is to conduct an extensive evaluation and comparison of MARL algorithms when used in networks that exhibit the scale-free property. …"
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A systematic review of text classification research based on deep learning models in Arabic language حسب Wahdan, Ahlam

"…The evaluation criteria used in the algorithms of different neural network types and how they play a large role in the highly accurate classification of Arabic texts are discussed. …"
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NEURAL NETWORK MODEL FOR PLANNED REPLACEMENT OF BOEING 737 BRAKES حسب Al-Garni, Ahmed Z.

"…., Boeing 737, is analyzed using the Artificial Neural Network and Weibull regression models. One-layered feed-forward back-propagation algorithm for artificial neural network whereas three parameters model for Weibull are used for the analysis. …"
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Novel algorithms for accurate DNA base-calling حسب Mohammed, Omniyah Gul

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Modelling Exchange Rates during Currency Crisis using Neural Networks حسب Nasr, G. E.

"…The models are built using the feedforward ANN structure trained by the backpropagation algorithm. …"
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Machine Learning Approach for the Design of an Assessment Outcomes Recommendation System حسب Abu Zitar, Raed

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Predicting Patient ICU Readmission Using Recurrent Neural Networks With Long Short-Term Memory حسب Nadia Rasheed (22997257)

Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks حسب Najam Us Sahar Riyaz (22927843)

"…Drawing on more than fifteen harmonized datasets that span pyrimidines, ionic liquids, graphene oxides, and additional compound families, we benchmark traditional algorithms, such as artificial neural networks, support vector machines, k-nearest neighbors, random forests, against advanced graph-based and deep architectures including three-level directed message-passing neural networks, 2D3DMol-CIC, and graph convolutional networks. …"

Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms حسب Marwan Dhuheir (19170898)

"…Given the complexity of the LDTP solution for managing online requests, we propose a real-time, lightweight solution using multi-agent meta-reinforcement learning. Our approach is tested on CNN networks and benchmarked against state-of-the-art conventional reinforcement learning algorithms. …"