Multi-Objective Optimisation of Injection Moulding Process for Dashboard Using Genetic Algorithm and Type-2 Fuzzy Neural Network by Mohammad Reza Chalak Qazani (13893261)

A hybrid graph representation for recursive backtracking algorithms by Abu-Khzam, Faisal N.

“…The performance of these algorithms often suffers from the increasing number of graph modifications, such as deletions, that reduce the problem instance and have to be “taken back” frequently during the search process. …”
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The effects of data balancing approaches: A case study by Paul Mooijman (4453189)

“…Our results showed that the replacement method was effective, and LogisticRegression combined with the oversampling algorithms SMOTE or ADASYN, GaussianProcessClassifier with the oversampling algorithm SMOTE, and LinearDiscriminantAnalysis were the best performing models after log transformation of the dataset was followed by Recursive Feature Elimination.…”

Nested ensemble selection: An effective hybrid feature selection method by Kamalov, Firuz

“…It has been shown that while feature selection algorithms are able to distinguish between relevant and irrelevant features, they fail to differentiate between relevant and redundant and correlated features. …”
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Artificial intelligence based anomaly detection of energy consumption in buildings: A review, current trends and new perspectives by Yassine Himeur (14158821)

“…In this regard, this paper is an in-depth review of existing anomaly detection frameworks for building energy consumption based on artificial intelligence. Specifically, an extensive survey is presented, in which a comprehensive taxonomy is introduced to classify existing algorithms based on different modules and parameters adopted, such as machine learning algorithms, feature extraction approaches, anomaly detection levels, computing platforms and application scenarios. …”

A Survey of Audio Enhancement Algorithms for Music, Speech, Bioacoustics, Biomedical, Industrial, and Environmental Sounds by Image U-Net by Sania Gul (18272227)

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

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

Spectral energy balancing system with massive MIMO based hybrid beam forming for wireless 6G communication using dual deep learning model by Ramesh Sundar (19326046)

“…The proposed approach of DDN is trained with proper data sequences used for communication and the training phase is conducted with the norms of numerous channel variants. …”

Indexing Arabic texts using association rule data mining by Haraty, Ramzi A.

“…The model denotes extracting new relevant words by relating those chosen by previous classical methods to new words using data mining rules. …”
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Software-Defined-Networking-Based One-versus-Rest Strategy for Detecting and Mitigating Distributed Denial-of-Service Attacks in Smart Home Internet of Things Devices by Neder Karmous (19743430)

“…Based on the performance metrics, such as confusion matrix, training time, prediction time, accuracy, and Area Under the Receiver Operating Characteristic curve (AUC-ROC), it was established that SDN-ML-IoT, when applied to RF, outperforms other ML algorithms, as well as similar approaches related to our work. …”

Big Data Energy Management, Analytics and Visualization for Residential Areas by Gupta, Ragini

“…A high-speed distributed computing cluster based on commodity hardware with efficient big data mathematical algorithm is employed in this work. …”
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Using genetic algorithms to optimize software quality estimation models by Azar, Danielle

“…This thesis explores the use of genetic algorithms for the problem of optimizing existing rule-based software quality estimation models. …”
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Animal migration optimization algorithm: novel optimizer, analysis, and applications by Abualigah, Laith

“…Optimization algorithms are applied to find the optimal solutions in many domains and fields such as image processing, machine learning, and others. …”
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A Modified Oppositional Chaotic Local Search Strategy Based Aquila Optimizer to Design an Effective Controller for Vehicle Cruise Control System by Ekinci, Serdar

“…CEC2019 test suite is also used to perform ablation experiments to reveal the separate contributions of chaotic local search and modified opposition-based learning strategies to the CmOBL-AO algorithm. …”
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An efficient approach for textual data classification using deep learning by Abdullah Alqahtani (7128143)

“…Textual data contains much useless information that must be pre-processed. …”

Bee colony algorithm for assigning proctors to exams. (c2013) by Taha, Mohamad Kassem

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DRL-Based UAV Path Planning for Coverage Hole Avoidance: Energy Consumption and Outage Time Minimization Trade-Offs by Bahareh Jafari (22501715)

“…By deploying a deep reinforcement learning algorithm, we find optimal UAV paths based on the two families of trajectories: spiral and oval curves, to tackle different design considerations and constraints, in terms of QoS, energy consumption and coverage hole avoidance. …”

An App for Navigating Patient Transportation and Acute Stroke Care in Northwestern Ontario Using Machine Learning: Retrospective Study by Ayman Hassan (14426412)

“…We aimed to develop an app using a comprehensive geomapping navigation and estimation system based on machine learning algorithms. This app uses key stroke-related timelines including the last time the patient was known to be well, patient location, treatment options, and imaging availability at different health care facilities.…”

Digital twin in energy industry: Proposed robust digital twin for power plant and other complex capital-intensive large engineering systems by Ahmad K. Sleiti (14778229)

“…The data-driven approach alone is not sufficient and a low-order physics based model should operate in tandem with the updated latest system parameters to allow interpretation and enhancing the results from the data-driven process. …”

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

“…A key requirement in these applications is minimizing the latency of data processing, particularly for time-sensitive tasks like image classification of IIoT device data. …”