Power-constrained system-on-a-chip test scheduling using a genetic algorithm by Harmanani, Haidar M.

“…We present experimental results for various SOC examples that demonstrate the effectiveness of our method. The method achieved optimal test schedules in all attempted cases in a short CPU time.…”
Get full text
Get full text
Get full text

Gene selection for microarray data classification based on Gray Wolf Optimizer enhanced with TRIZ-inspired operators by Abu Zitar, Raed

“…The support vector machine (SVM) is employed for the classification task to estimate the goodness of the selected subset of genes. The effectiveness of TRIZ optimization operators in MGWO is evaluated by investigating the convergence behavior of GWO with and without TRIZ optimization operators. …”
Get full text

A Novel BIPV Reconfiguration Algorithm for Maximum Power Generation under Partial Shading by Saoud A. Al-Janahi (18877213)

“…The system is optimised for maximum yield to determine the optimal configuration and number of modules for each string using a genetic algorithm. …”

Parameter Identification of Flexible Drive Systems using Particle Swarm Optimization by Hafez, Ishaq

Get full text

Economic load dispatch multiobjective optimization procedures usinglinear programming techniques by Farag, A.

“…The validity and effectiveness of the algorithm is verified by means of two examples: a 10-bus system and the IEEE 30-Bus, six generators system…”
Get full text
Get full text

Optimized provisioning of edge computing resources with heterogeneous workload in IoT networks by Kherraf, Nouha

Get full text
Get full text
Get full text
Get full text

A Novel Genetic Trajectory Planning Algorithm With Variable Population Size for Multi-UAV-Assisted Mobile Edge Computing System by Muhammad Asim (2235472)

“…The effectiveness of the proposed GTPA-VP is demonstrated through several experiments on a set of ten instances with up to 200 IoTDs. …”

Clustering and Stochastic Simulation Optimization for Outpatient Chemotherapy Appointment Planning and Scheduling by Majed Hadid (17148364)

“…A Stochastic Discrete Simulation-Based Multi-Objective Optimization (SDSMO) model is developed and linked to clustering algorithms using an iterative sequential approach. …”

Meta-Heuristic Algorithm-Tuned Neural Network for Breast Cancer Diagnosis Using Ultrasound Images by Ahila A (18394806)

“…The main novelty of this work is the computer-aided diagnosis scheme for detecting abnormalities in breast ultrasound images by integrating a wavelet neural network (WNN) and the grey wolf optimization (GWO) algorithm. Here, breast ultrasound (US) images are preprocessed with a sigmoid filter followed by interference-based despeckling and then by anisotropic diffusion. …”

An Incentivized and Optimized Dynamic Mechanism for Demand Response for Managing Voltage in Distribution Networks by Md Moktadir Rahman (16904751)

“…The proposed method minimizes the DR implementation cost and size, fairly incentivizes the consumers participating in the DR and priorities their consumption preferences while reduces the network power losses and DGs’ reactive power contributions to effectively manage the voltage in the MV networks. An improved hybrid particle swarm optimization algorithm (IHPSO) is proposed for the load controller to provide fast convergence and robust optimization results. …”

Multi-Agent Variational Approach for Robotics: A Bio-Inspired Perspective by Mir, Imran

“…This study proposes an adaptable, bio-inspired optimization algorithm for Multi-Agent Space Exploration. …”
Get full text

A method for optimizing test bus assignment and sizing for system-on-a-chip by Harmanani, Haidar M.

Get full text
Get full text
Get full text
Get full text

Combined cycle gas turbine system optimization for extended range electric vehicles by Barakat, Aya A.

“…This study presents a methodology for the design and optimization of the most optimal combined cycle system configuration, suitable to replace the engine in a series-hybrid extended-range electric vehicle, and investigates its potential fuel savings. …”
Get full text
Get full text
Get full text
Get full text

Multi-Objective Optimization for Food Availability under Economic and Environmental Risk Constraints by Bashar Hassna (19170940)

“…Utilizing these assessments, a multi-objective optimization model is developed and solved using MATLAB (R2018a)’s Genetic Algorithm, aiming to identify optimal suppliers to meet Qatar’s food demand, with consideration of the economic, environmental, and risk factors. …”

Enhancing e-learning through AI: advanced techniques for optimizing student performance by Rund Mahafdah (21399854)

“…This study offers a thorough examination of how AI can be utilized to enhance e-learning results by employing advanced predictive methods and performance optimization strategies. The main goals consist of creating an AI-based framework to monitor and analyze student interactions, evaluating the influence of online learning platforms on student understanding using advanced algorithms, and determining the most efficient methods for blended learning systems. …”

Optimal Planning of Distributed Generators and Shunt Capacitors in Isolated Microgrids With Nonlinear Loads by Yazdavar, Ameen H.

Get full text

Optimal Dispatch of Mobile Energy Storage Unit to Support EV Charging Stations by Elmeligy, Mohamed Mostafa Abdelazim

Get full text

Opportunistic Throughput Optimization in Energy Harvesting Dynamic Spectrum Sharing Wireless Networks by Amirhossein Taherpour (19273879)

“…Furthermore, we propose two algorithms designed to achieve optimal throughput for each scenario. …”

LOCATING DAMAGES IN THIN ALUMINIUM PLATES USING LAMB WAVES AND AGENETIC OPTIMIZATION APPROACH by A. Masurkar, Faeez

“…The damage locations are further optimized within the enclosed area using the GO algorithm. …”
Get full text

Enhancing Building Energy Management: Adaptive Edge Computing for Optimized Efficiency and Inhabitant Comfort by Sergio Márquez-Sánchez (19437985)

“…By integrating energy efficiency measures within virtual organizations, which dynamically learn from real-time inhabitant data while prioritizing comfort, our approach effectively optimizes inhabitant consumption patterns, ushering in a new era of energy efficiency in the built environment.…”