Scatter search for homology modeling by Mansour, Nashat

“…Homology modeling is an effective technique in protein structure prediction (PSP). …”
Get full text
Get full text
Get full text
Get full text

Scatter search metaheuristic for homology based protein structure prediction. (c2015) by Stamboulian, Mouses Hrag

“…To improve homology based PSP, we propose a scatter search (SS) metaheuristic algorithm. Our algorithm optimizes the initial poor alignments, generated by a dynamic programming method. …”
Get full text
Get full text

Estimation of power grid topology parameters through pilot signals by Hargossian, H.

“…Coupled with the adoption of open energy markets, this event has significantly complicated the powerflows on the distribution grid, urging network operators to invest in advanced control and monitoring tools in order to optimize the efficiency and reliability of the system. …”
Get full text
Get full text
Get full text

Development and Implementation of a Hybrid Intelligent Controller for Interior Permanent Magnet Synchronous Motor Drives by Nasir Uddin, M.

“…At each operating condition a genetic algorithm is used to optimize the PI controller parameters in a closed-loop vector control scheme. …”
Get full text

Definition and selection of fuzzy sets in genetic‐fuzzy systems using the concept of fuzzimetric arcs by Kouatli, Issam

“…It would also enhance the simplicity and effectiveness of optimizing the performance of such systems.…”
Get full text
Get full text
Get full text
Get full text

Morphology for Planar Hexagonal Modular Self-Reconfigurable Robotic Systems by Sadjadi, Hossein

Get full text

Fixed set search applied to the multi-objective minimum weighted vertex cover problem by Raka Jovanovic (17947838)

“…In this work, a simple and effective bi-objective GRASP algorithm for the MWVCP is developed in the first stage. …”

Logic-based Benders decomposition combined with column generation for mobile 3D printer scheduling problem by Tao Li (86810)

“…Three strategies, namely dominance rules, effective upper bounds, and tandem sequence deduplication, are constructed to accelerate the algorithm’s convergence. …”

Prediction of biogas production from chemically treated co-digested agricultural waste using artificial neural network by Fares Almomani (12585685)

“…An Artificial neural network (ANN) algorithm was developed to model and optimize the cumulative methane production (CMP) from ASWs, CM, and their mixture under mesophilic and thermophilic conditions. …”

Estimating Vehicle State by GPS/IMU Fusion with Vehicle Dynamics by Saadeddin, Kamal Mohamad

Get full text

Distributed Tree-Based Machine Learning for Short-Term Load Forecasting With Apache Spark by Ameema Zainab (16864263)

“…However, with the huge increase in data size, sophisticated models have to be created which require big data platforms. Optimal and effective use of the available computational resources can be attained by maximizing the effective utilization of the cluster nodes. …”

Improving Active Resonance Damping and Unbalanced Voltage Mitigation Based on Combined DDSRF and Washout Filter in Islanded Microgrids by Ehsan Akbari (10803914)

“…The presented control algorithm can perform optimally under dynamic changes of active and reactive power of nonlinear and imbalanced loads. …”

An Infrastructure-Assisted Workload Scheduling for Computational Resources Exploitation in the Fog-Enabled Vehicular Network by Sorkhoh, Ibrahim

“…A Dantzig–Wolfe decomposition algorithm is proposed which yields to a master program solvable by the Barrier algorithm and subproblems solve...…”
Get full text
Get full text
Get full text
Get full text

Multi-class subarachnoid hemorrhage severity prediction: addressing challenges in predicting rare outcomes by Muhammad Mohsin Khan (22150360)

“…Feature selection was done using a Random Forest algorithm to identify the top 20 features for the SAH severity prediction. …”

On-demand deployment of multiple aerial base stations for traffic offloading and network recovery by Sharafeddine, Sanaa

“…We present performance results for the proposed algorithm as a function of various system parameters and demonstrate its effectiveness compared to the close-to-optimal greedy approach and its superiority compared to recent related work from the literature.…”
Get full text
Get full text
Get full text
Get full text

A METHODOLOGY FOR NETWORK TOPOLOGY DESIGN USING FUZZY EVALUATIONS by Khan, Salman A.

“…The topology design of campus networks (CNs), a class of computer networks, is a NP-hard optimization problem. The design consists of three main steps and requires the optimization of several conflicting objectives such as minimization of cost, minimization of network delay, and minimization of maximum number of hops etc. …”
Get full text

Autonomous 3D Deployment of Aerial Base Stations in Wireless Networks with User Mobility by Islambouli, Rania

“…The simulation results demonstrate the effectiveness of the proposed algorithm compared to the optimal solution and related work in the literature for various network scenarios with user mobility.…”
Get full text
Get full text
Get full text
Get full text

Impacts of On-Grid Solar PV on Distribution Networks and Potential Solutions: A Case Study in the Region of Zahle by Korkmaz, Jessica

“…The siting and sizing methodology is conducted by considering five different optimization algorithms, namely the single-objective genetic algorithm (SOGA), the combined SOGA and loss sensitivity factor algorithm (SOGA-LSF), the multi-objective genetic algorithm (MOGA), the combined MOGA-LSF and the CAPADD algorithm of OpenDSS. …”
Get full text
Get full text
Get full text

Framework for rapid design and optimisation of immersive battery cooling system by Ali Almshahy (23544823)

“…Two key parameters are optimised, namely: battery gap spacing (3–10 mm) and inlet/outlet width (5–15 mm), via Optimal Latin Hypercube Sampling, Support Vector Regression, and GDE3 algorithm. …”

Power system output feedback stabilizer design via geneticalgorithms by Abdel-Magid, Y.L.

“…A digital simulation of the power system is then used in conjunction with the genetic algorithm to determine the output feedback gains. In the second method, the problem of selecting the output feedback gains is converted to a simple optimization problem with an eigenvalue based objective function, which is solved by a genetic algorithm. …”
Get full text
Get full text