Search Results - (( developing function using algorithm ) OR ( a simulation optimization algorithm ))

Simulated Kalman Filter algorithms for solving optimization problems by Nor Hidayati, Abdul Aziz

“…Its optimality has inspired the development of a metaheuristic algorithm called Heuristic Kalman Algorithm (HKA) in 2009. …”
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Convergence Analysis of the African Buffalo Optimization Algorithm by Odili, Julius Beneoluchi, M. N. M., Kahar, Noraziah, Ahmad

“…This paper presents the convergence analysis of the newly-developed African Buffalo Optimization algorithm. African Buffalo Optimization is a simulation of the organizational skills of the African buffalos using two basic sounds: /waaa/ and /maaa/ as they transverse the African landscape in search of grazing pastures. …”
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The Development Of A Robust Algorithm For Uav Path Planning In 3d Environment by Kok, Kai Yit

“…Thus, a new algorithm known as infection evolution (IE) was developed in this study. …”
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Development of a Bioinspired optimization algorithm for the automatic generation of multiple distinct behaviors in simulated mobile robots by Hanafi Ahmad Hijazi, Patricia Anthony

“…The ANN acts as a controller for radio frequency (RF)-Iocalization behavior of a Khepera robot simulated in a 3D physics-based environment. …”
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A discrete simulated kalman filter optimizer for combinatorial optimization problems by Suhazri Amrin, Rahmad

“…An example of a numerical algorithm is the simulated Kalman filter (SKF). …”
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Comparative Performance Analysis of Bat Algorithm and Bacterial Foraging Optimization Algorithm using Standard Benchmark Functions by Mazlina, Abdul Majid, Alsariera, Yazan A., Alamri, Hammoudeh S., Nasser, Abdullah M., Kamal Z., Zamli

“…Over the last 30 years, many meta-heuristic algorithms have been developed in the literature including that of Simulated Annealing (SA), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Harmony Search Algorithm (HS) to name a few. …”
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Comparison between multi-objective and single-objective optimization for the modeling of dynamic systems by Mohd Zakimi, Zakaria, Hishamuddin, Jamaluddin, Robiah, Ahmad, Sayed Mohammad Reza, Loghmanian

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Quantum-Behaved Lightning Search Algorithm to Improve Indirect Field-Oriented Fuzzy-PI Control for im Drive by Hannan M.A., Ali J.A., Mohamed A., Amirulddin U.A.U., Tan N.M.L., Uddin M.N.

Development of multi-objective load shedding optimization via back tracking search algorithm with novel reactive power tracing index by Verayiah R., Mohamed A., Shareef H., Abidin I.H.Z.

IWDSA: a hybrid Intelligent Water Drops with a Simulated Annealing for the localization improvement in wireless sensor networks by Gumaida, Bassam, Ibrahim, Adamu Abubakar

“…Additionally, simulation results confirm that the proposed algorithm IWDSA exhibits outstanding performance compared to other algorithms utilizing optimization techniques, including genetic algorithms, bat algorithms, ant colony optimization, and swarm optimization. …”
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Optimal overcurrent relay solutions for protection coordination using metaheuristics approaches with penalty function method by Noor Zaihah, Jamal, Mohd Herwan, Sulaiman, Abdul, Nasir, Jabbar, Waheb A.

“…The optimized value of the TMS and PS will be selected using the algorithms to ensure the minimize result of the objective function. …”
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A generalized laser simulator algorithm for optimal path planning in constraints environment by Aisha, Muhammad

“…This research focuses on developing a novel path planning algorithm, called Generalized Laser Simulator (GLS), to solve the path planning problem of mobile robots in a constrained environment. …”
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Ant colony optimization algorithm for dynamic scheduling of jobs in computational grid by Ku-Mahamud, Ku Ruhana, Ramli, Razamin, Yusof, Yuhanis, Mohamed Din, Aniza, Mahmuddin, Massudi

“…Job scheduling problem is classified as an NP-hard problem.Such a problem can be solved only by using approximate algorithms such as heuristic and meta-heuristic algorithms.Among different optimization algorithms for job scheduling, ant colony system algorithm is a popular meta-heuristic algorithm which has the ability to solve different types of NP-hard problems.However, ant colony system algorithm has a deficiency in its heuristic function which affects the algorithm behavior in terms of finding the shortest connection between edges.This research focuses on a new heuristic function where information about recent ants’ discoveries has been considered.The new heuristic function has been integrated into the classical ant colony system algorithm.Furthermore, the enhanced algorithm has been implemented to solve the travelling salesman problem as well as in scheduling of jobs in computational grid.A simulator with dynamic environment feature to mimic real life application has been development to validate the proposed enhanced ant colony system algorithm. …”
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Simulation of shortest path using a-star algorithm / Nurul Hani Nortaja by Nurul Hani , Nortaja

“…The steps to calculate a shortest path using A • algorithm is shown by using appropriate examples and related figures. …”
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New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems by Nor Shuhada, Ibrahim

“…In the fourth phase, the newly developed algorithm undergoes testing on the formulated ROOPs and compared to several contemporary optimizer algorithms. …”
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Levy slime mould algorithm for solving numerical and engineering optimization problems by J. J., Jui, M. A., Ahmad, M. I. M., Rashid

“…The SMA is a newly developed metaheuristic algorithm that is inspired by the slime moulds natural oscillation mode. …”
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An Optimal Scheduling Controller for Virtual Power Plant and Microgrid Integration Using the Binary Backtracking Search Algorithm by Abdolrasol M.G.M., Hannan M.A., Mohamed A., Amiruldin U.A.U., Abidin I.B.Z., Uddin M.N.

Long term energy demand forecasting based on hybrid, optimization: Comparative study by Musa, Wahab, Ku-Mahamud, Ku Ruhana, Yasin, Azman

“…The objective of this research is to develop a long term energy demand forecasting model that used hybrid optimization.To accomplish this goal, a hybrid algorithm that combined a genetic algorithm and a local search algorithm method has been developed to overcome premature convergence.Model performances of hybrid algorithm were compared with former single algorithm model in estimating parameter values of an objective function to measure the goodness-of-fit between the observed data and simulated results.Averages error between two models was adopt to select the proper model for future projection of energy demand.…”
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Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance by Allawi, Mohammed Falah, Jaafar, Othman, Mohamad Hamzah, Firdaus, Koting, Suhana, Mohd, Nuruol Syuhadaa, El-Shafie, Ahmed

“…The three different optimization algorithms used in this study are the genetic algorithm (GA), particle swarm optimization (PSO) algorithm and shark machine learning algorithm (SMLA). …”
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Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Pr... by Sammen S.S., Ehteram M., Sheikh Khozani Z., Sidek L.M.

“…For water level prediction, lagged rainfall and water level are used. In this study, we used extreme learning machine (ELM)-multi-kernel least square support vector machine (ELM-MKLSSVM), extreme learning machine (ELM)-LSSVM-polynomial kernel function (PKF) (ELM-LSSVM-PKF), ELM-LSSVM-radial basis kernel function (RBF) (ELM-LSSVM-RBF), ELM-LSSVM-Linear Kernel function (LKF), ELM, and MKLSSVM models to predict water level. …”