Matheuristic Fixed Set Search Applied to the Two-Stage Capacitated Facility Location Problem by Denis Alicic (23073484)

“…<p dir="ltr">This paper addresses the Two-Stage Capacitated Facility Location Problem (TSCFLP), a challenging optimization problem with significant applications in supply chain network design. …”

Enhanced Control of Single-Stage PV-STATCOM Using Hybrid MPPT and Adaptive AHLMS for Power Quality Improvement by Nagwa F. Ibrahim (17334201)

“…It employs a hybrid pelican and perturbs and observe and particle swarm optimization (PSO) based maximum power point tracking (MPPT) algorithm to consistently extract peak power from the PV array. …”

Accommodating High Penetrations of Renewable Distributed Generation Mix in Smart Grids by Khayata, Mohammad Tarek

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A combined resource allocation framework for PEVs charging stations, renewable energy resources and distributed energy storage systems by Kandil, Sarah M.

“…The formulation is decomposed into two interdependent sub-problems and solved using a combination of metaheuristic and deterministic optimization techniques. A sample case study is presented to illustrate the performance of the algorithm.…”
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Boosting the visibility of services in microservice architecture by Ahmet Vedat Tokmak (17773479)

“…We utilized parameter optimization techniques, namely Grid Search, Random Search, Bayes Search, Halvin Grid Search, and Halvin Random Search to fine-tune the hyperparameters of our classifier models. …”

A Graph Heuristic Approach for the Data Path Allocation Problem by Makhoul, Racha

“…The results show that the algorithm performs well while generating sub-optimal solutions.…”
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Multi-Objective Task Allocation Via Multi-Agent Coalition Formation by Amer, Noha Tarek

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

“…The proposed energy-efficient routing protocol is based on an enhanced genetic algorithm and data fusion technique. In the proposed energy-efficient routing protocol, an existing genetic algorithm is enhanced by adding an encoding strategy, a crossover procedure, and an improved mutation operation that helps determine the nodes. …”

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

“…In this work, we implement three approaches to tackle the 2-club clustering via edge deletion: a heuristic approach based on the influence of the edge to resolve maximum conflicts, a parameterized algorithm in which by deleting a maximum of k edges, the graph can be transformed into a 2-club cluster based on a branching algorithm, and the approach in Integer Linear Programming to find the optimized solution in an integer formulation. …”
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Experimental Investigation and Comparative Evaluation of Standard Level Shifted Multi-Carrier Modulation Schemes With a Constraint GA Based SHE Techniques for a Seven-Level PUC Inv... by Atif Iqbal (5504636)

“…Different standard multicarrier sinusoidal pulse-width modulation techniques (SPWMs) are adapted for the generation of switching gate signals for the PUC power switches, and these SPWMs are compared with novel optimization-based selective harmonic elimination (SHE) that employs genetic algorithm (GA) for solving nonlinear SHE equation with a constraint that eliminated all third-order harmonics efficiently. …”

Day-Ahead Load Demand Forecasting in Urban Community Cluster Microgrids Using Machine Learning Methods by Sivakavi Naga Venkata Bramareswara Rao (15944992)

“…The effectiveness of these optimization algorithms is verified in terms of training, test, validation, and error analysis. …”

An Ultrafast Maximum Power Point Setting Scheme for Photovoltaic Arrays Using Model Parameter Identification by Zhaohui Cen (17217391)

“…<p dir="ltr">Maximum power point tracking (MPPT) for photovoltaic (PV) arrays is essential to optimize conversion efficiency under variable and nonuniform irradiance conditions. …”

A machine learning model for early detection of diabetic foot using thermogram images by Amith Khandakar (14151981)

“…We have compared a machine learning-based scoring technique with feature selection and optimization techniques and learning classifiers to several state-of-the-art Convolutional Neural Networks (CNNs) on foot thermogram images and propose a robust solution to identify the diabetic foot. …”

An Effective Hybrid NARX-LSTM Model for Point and Interval PV Power Forecasting by Mohamed Massaoudi (16888710)

“…Then, the stacked LSTM model, optimized by Tabu search algorithm, uses the residual error correction associated with the original data to produce a point and interval PVPF. …”

The Detection of Dysarthria Severity Levels Using AI Models: A Review by Afnan Al-Ali (16888695)

A Novel Non-Invasive Estimation of Respiration Rate From Motion Corrupted Photoplethysmograph Signal Using Machine Learning Model by Md. Nazmul Islam Shuzan (16888827)

“…The best ML model and the best feature selection algorithm combination were fine-tuned to optimize its performance using hyperparameter optimization. …”

Deep Learning-Based Short-Term Load Forecasting Approach in Smart Grid With Clustering and Consumption Pattern Recognition by Dabeeruddin Syed (16864260)

“…The developed deep neural network consists of six layers and employs Adam optimization using the TensorFlow framework. The STLF is a day-ahead hourly horizon forecasting. …”

A Clinically Interpretable Approach for Early Detection of Autism Using Machine Learning With Explainable AI by Oishi Jyoti (21593819)

“…This study focuses on optimizing and comparing various machine learning models for ASD diagnosis, while incorporating explainable AI techniques to ensure model transparency and interpretability. …”

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

Modeling and thermoeconomic analysis of new polygeneration system based on geothermal energy with sea water desalination and hydrogen production by Wulaer Shaersaikai (21436652)

“…A USPC of 5.37 $/GJ and a NPV of 15.48 M$ support the system's economic performance and show that it is feasible in a market with favorable conditions. The Grey Wolf Optimization (GWO) algorithm, which directs the system's optimization process, demonstrates a competitive trade-off between exergy efficiency, freshwater production, costs, NPV, and environmental impact. …”