Search Results - (( parameter simulation model algorithm ) OR ( user optimization path algorithm ))

Railway shortest path planner application using ant colony optimization algorithm / Muhammad Hassan Firdaus Ruslan by Ruslan, Muhammad Hassan Firdaus

“…For the process module, Ant Colony Optimization (ACO) algorithm was used to find the shortest path. …”
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

“…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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Particle swarm optimization (PSO) for CNC route problem by Nur Azia Azwani, Ismail

“…The algorithm used in this project is the Global Best (gbest) algorithm where it is a basic algorithm of Particle Swarm Optimization which applicable the shortest time and path of CNC machine to complete the process of drilling. …”
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Ant colony optimization (ACO) algorithm for CNC route problem by Wan Nur Farhanah , Wan Zakaria

“…The GUT will be display the shortest path that should be taken by user and give user authority to manipulate the coordinate based on the requirement.…”
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An efficient virtual tour : a merging of path planning and optimization by Abd Latiff, Muhammad Shafie, Hassan, Rohayanti

“…This paper describes the result of a research project aimed to integrate a path-planning optimization-algorithm and produce an efficient tour in a virtual environment. …”
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Providing wireless coverage in massively crowded events using UAVs by Sawalmeh A., Othman N.S., Shakhatreh H., Khreishah A.

Shortest Path Routing Using Heuristic Search by Alaiwan, Ahmed Omran A.

“…To achieve the best path, there are many algorithms which are more or less effective, depending on the particular case. …”
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Path planning for visually impaired people in an unfamiliar environment using particle swarm optimization by Yusof, T. S. T., Toha, Siti Fauziah, Md. Yusof, Hazlina

“…Here, in this paper, we propose a path planning with predetermined waypoints method using Particle Swarm Optimization (PSO) algorithm. …”
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AUTOMATIC ROUTE FINDER FOR NEW VISITORS by ADNAN, MOHD SHIHAM

“…This project proposes a new visitor route model that is based on shortest path algorithms for road networks. Shortest path problems are among the best studied network flow optimization problems, with interesting applications in a range of fields. …”
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Robotic path planning using rapidly-exploring random trees by Sherwani, Fahad

“…However, the planned path by using basic RRT structure might not always be optimal in terms of path length. …”
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PLANNING OF MULTIPLE FEEDERS ELECTRICAL DISTRIBUTION SYSTEM by NORDIN, AHMAD SOLLEHIN

“…In this project, several algorithms are implemented to design an electrical distribution system which are (1) Optimal Feeder Path Algorithm, (2) Modified Load Flow Algorithm, (3) Optimal Branch Conductor Selection Algorithm, and ( 4) Optimal Location of Substation Algorithm. …”
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Systematic design of chemical reactors with multiple stages via multi-objective optimization approach by Mohd Fuad, Mohd Nazri, Hussain, Mohd Azlan

“…By using reference-point based multi-objective evolutionary algorithm (R-NSGA-II), Pareto-optimal solutions are successfully generated within the region of user-specified reference points, thus facilitating in the selection of final optimal designs. …”
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The Effect of Rainfall on the UAV Placement for 5G Spectrum in Malaysia by Shalaby A.M., Othman N.S.

“…The problem of finding the UAV 3D placement is formulated with the objective to minimize the total path loss between the UAV and all users. The problem is solved by invoking two algorithms, namely Particle Swarm Optimization (PSO) and Gradient Descent (GD) algorithms. …”

Artificial Bee Colony algorithm in estimating kinetic parameters for yeast fermentation pathway by Ahmad Muhaimin, Ismail, Muhammad Akmal, Remli, Yee Wen, Choon, Nurul Athirah, Nasarudin, Norsyahidatul Nazirah, Ismail, Mohd Arfian, Ismail, Mohd Saberi, Mohamad

“…Fitting the simulated model into the experimental data is categorized under the parameter estimation problem. …”
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GENETIC ALGORITHM WITH DEEP NEURAL NETWORK SURROGATE FOR THE OPTIMIZATION OF ELECTROMAGNETIC STRUCTURE by MOHAMMED SHARIFF, NUR ATIQAH

“…The behavior of Genetic Algorithm (GA) where it generates and evolves the parameters towards a high-quality solution gives an advantage in obtaining ideal combination of parameters to fit in with the simulation. …”
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Efficient 3D placement of a UAV using particle swarm optimization by Shakhatreh H., Khreishah A., Alsarhan A., Khalil I., Sawalmeh A., Othman N.S.

Estimation in spot welding parameters using genetic algorithm by Lukman, Hafizi

“…The application has widespread in many areas especially in system and control engineering. Genetic algorithm (GA) used as parameter estimation method for a model structure. …”
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Simultaneous computation of model order and parameter estimation for ARX model based on single swarm and multi swarm simulated Kalman filter by Kamil Zakwan, Mohd Azmi, Zuwairie, Ibrahim, Pebrianti, Dwi, Mohd Saberi, Mohamad

“…Simultaneous Model Order and Parameter Estimation (SMOPE) and Simultaneous Model Order and Parameter Estimation based on Multi Swarm (SMOPE-MS) are two techniques of implementing meta-heuristic algorithm to iteratively establish an optimal model order and parameters simultaneously for an unknown system. …”
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Simulation algorithm of bayesian approach for choice-conjoint model by Zulhanif

“…Therefore this research propose simulation algorithm of Bayesian approach for estimating parameter in MPM by Bayesian analysis to avoid computational difficulties in computing the maximum likelihood estimates (MLE).…”
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Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm by Manoharan P., Ravichandran S., Kavitha S., Tengku Hashim T.J., Alsoud A.R., Sin T.C.

“…The orthogonal learning mechanism improves the performance of the original GOOSE algorithm. This FC model uses the root mean squared error as the objective function for optimizing the unknown parameters. …”