Search Results - (( developing function _ algorithm ) OR ( combining simulation optimization algorithm ))

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

“…The proposed algorithm, named Intelligent Water Drops with Simulated Annealing (IWDSA), combines two powerful optimization methods: Intelligent Water Drops (IWD) and Simulated Annealing (SA). …”
Get full text
Get full text
Get full text

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.…”
Get full text
Get full text
Get full text

A discrete simulated kalman filter optimizer for combinatorial optimization problems by Suhazri Amrin, Rahmad

“…However, these extensions may result in increased execution times for the algorithm. In this research, a new combinatorial algorithm named discrete simulated Kalman filter optimizer (DSKFO) is proposed to solve combinatorial optimization problem. …”
Get full text
Get full text

Simulated annealing for solving economic dispatch problem / Wan Khairulizuan Wan Ismail by Wan Ismail, Wan Khairulizuan

“…In the development of the algorithm, transmission losses are first discounted and they are subsequently incorporated in the algorithm through the use of the B-matrix loss formula. …”
Get full text
Get full text

An Application of Grey Wolf Optimizer for Solving Combined Economic Emission Dispatch Problems by Hong, Mee Song, M. H., Sulaiman, Mohd Rusllim, Mohamed

“…Grey Wolf Optimizer (GWO) is a newly proposed algorithm that developed based on inspiration of grey wolves (Canis Lupus). …”
Get full text
Get full text

An Optimized PID Parameters for LFC in Interconnected Power Systems Using MLSL Optimization Algorithm by Najeeb, Mushtaq, Shahooth, Mohammed, Mohaisen, Arrak, Ramdan, Razali, Hamdan, Daniyal

“…In order to enhance the dynamic performance, the optimal parameters of the PID scheme which optimized by the proposed MLSL algorithm are compared with that one’s obtained by GA algorithm. …”
Get full text
Get full text
Get full text
Get full text

Hybrid optimization approach to estimate random demand by Wahab, Musa, Ku-Mahamud, Ku Ruhana, Yasin, Azman

“…The main objective of this study is to develop a demand forecasting model that should reflect the characteristics of random demand patterns.To accomplish this goal, a hybrid algorithm combining a genetic algorithm and a local search algorithm method was developed to overcome premature convergence in local optima problems.The performance of the hybrid algorithm was compared with a single algorithm model in estimating parameter values that minimize objective function which was used to measure the goodness-of-fit between the observed data and simulated results.However, two problems had to be overcome in the forecasting random demand model. …”
Get full text
Get full text
Get full text

A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

“…Then, this study aims to optimize the hyperparameters of the developed DNN model using the Arithmetic Optimization Algorithm (AOA) and, lastly, to evaluate the performance of the newly proposed deep learning model with Simulated Kalman Filter (SKF) algorithm in solving image encryption application. …”
Get full text
Get full text

Collision avoidance mechanisms using artificial potential field for UAVs by Abdul Azis, Fadilah, Tan, Jie Sim, Md Ghazaly, Mariam, Mohamad Hanif, Noor Hazrin Hany

“…The APF algorithm, based on the combination of attractive and repulsive potential functions, is modeled and simulated in MATLAB to guide UAVs toward target destinations while avoiding obstacles. …”
Get full text
Get full text
Get full text

Moth Flame Optimization Algorithm including Renewable Energy for Minimization of Generation & Emission Costs in Optimal Power Flow by Alam, Mohammad Khurshed, Mohd Herwan, Sulaiman, Ferdowsi, Asma, Sayem, Md. Shaoran, Khair, Nazmus Sakib

“…This problem must be overcome to achieve the goals while keeping the system stable. Moth Flame Optimization (MFO), a recently developed metaheuristic algorithm, will be used to solve objective functions of the OPF issue for combined cost and emission reduction in IEEE 57-bus systems with thermal and stochastic wind-solar-small hydropower producing systems. …”
Get full text
Get full text
Get full text

Modelling of multi-robot system for search and rescue by Poy, Yi Ler

“…One of the key aspects in multi-robot systems is the path planning problem, which involves finding collision-free paths for each robot to reach their respective destinations while optimizing various performance metrics. This report focusses on developing a novel multi-robot path planning algorithm based on the Modified Particles Swarm Optimization (MPSO) algorithm for dynamic environments. …”
Get full text
Get full text

Neural Network Model and Finite Element Simulation of Spring back in Plane-Strain Metallic Beam Bending by Abu Khadra, Fayiz Y. M.

“…To validate the finite element model physical experiments were conducted. A neural network algorithm based on the backpropagation algorithm has been developed. …”
Get full text
Get full text

Alternative method for economic dispatch utilizing grey wolf optimizer by Wong, Lo Ing

“…Although several optimization methodologies have been developed for solving ED problems, the complexity of the task reveals the necessity for development of efficient algorithms to accurately locate the optimum solution. …”
Get full text
Get full text

Fuzzy clustering method and evaluation based on multi criteria decision making technique by Sameer, Fadhaa Othman

“…This proposed algorithm is developed based on heuristic method named modified binary particle swarm optimization (MBPSO) with kernel fuzzy clustering method as a fitness function. …”
Get full text
Get full text
Get full text

Monthly chlorophyll-a prediction using neuro-genetic algorithm for water quality management in Lakes by Lee, G., Bae, J., Lee, S., Jang, M., Park, H.

“…A genetic algorithm (GA) was combined with artificial neural networks (ANN), designated as neuro-genetic algorithm (NGA) in this study, to determine the effective number of nodes and optimal activated functions (FAs) in an ANN structure. …”
Get full text
Get full text

Optimization of the PID-PD parameters of the overhead crane control system by using PSO algorithm by Nur Iffah, Mohamed Azmi, Nafrizuan, Mat Yahya, Ho, Jun Fu, Wan Azhar, Wan Yusoff

“…New time-domain performance criterion function is used in particle swarm optimization (PSO) algorithm for the tuning of the PID-PD controller rather than the general performance criteria using error of the system. …”
Get full text
Get full text
Get full text

Nomadic people optimizer (NPO) for large-scale optimization problems by Mohamd Salih, Sinan Qahtan

“…The proposed algorithm simulates the behavior of the nomads when they are searching for life sources (water or grazing fields). …”
Get full text
Get full text

Artificial neural controller synthesis for TORCS by Shi, Jun Long

“…The results showed: (1) DE hybrid FFNN could generate optimal controllers, (2) the proposed fitness function had successfully generated the required car's racing controllers, (3) the proposed minimization algorithm had been successfully minimize the number of RF sensors used, (4) the PDE algorithm could be implemented to generate optimal solutions for car racing controllers, and (5) the combination of components for average car speed and distance between the car and track axis is very important compared to other components. …”
Get full text
Get full text

Optimal distributed generation and load shedding scheme using artificial bee colony- hill climbing algorithm considering voltage stability and losses indices by Ali Abdallah, Ali Emhemed

“…The proposed solution is based on the optimization method developed from a combination of the Artificial Bee Colony and Hill Climbing algorithms (ABC-HC) to give the optimal placement and sizing of DG units to be deployed in the system. …”
Get full text
Get full text

Combining Recursive Least Square and Principal Component Analysis for Assisted History Matching by Md. Anuar, Nurul Syaza

“…Forward model was also involved in the process of defining the objective function. Next, using simulated data together with historical data, objective function will be computed. …”
Get full text
Get full text