Search Results - (( variable simulation based algorithm ) OR ( parameter optimization search algorithm ))

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.

Dynamic probability selection for flower pollination algorithm based on metropolis-hastings criteria by Zamli, Kamal Zuhairi, Din, Fakhrud, Nasser, Abdullah, Ramli, Nazirah, Mohamed, Noraini

“…Having only one parameter control (i.e. the switch probability, pa) to choose from the global search (i.e. exploration) and local search (i.e. exploitation) is the main strength of FPA as compared to other meta-heuristic algorithms. …”
Get full text
Get full text
Get full text

Cloudlet deployment and task offloading in mobile edge computing using variable-length whale and differential evolution optimization and analytical hierarchical process for decisio... by Daba, Layth Muwafaq Abdulhussein

“…Unlike the existing optimization algorithm, VL-WIDE features the capability of searching different lengths of solutions to cover the variable number of cloudlets for deployment. …”
Get full text
Get full text

A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments by Khaksar, Weria

“…Afterward, a genetic algorithm-based optimization framework was designed to improve the interpretability and accuracy of the proposed fuzzy-tabu controller by optimizing the parameters of the FLC and also some of the planner’s parameters in order to improve the quality of the generated paths and runtimes of the planner and also to decrease the variation of the results in different runs of the planner. …”
Get full text
Get full text

Adaptive Step Size Based Hill-Climb Search Algorithm for MPPT Control of DFIG-WECS With Reduced Power Fluctuation and Improved Tracking Performance by Uddin M.N., Amin I.K.

Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques by Hammid, Ali Thaeer

“…To deal with these problems, this thesis introduces three approved intelligent controllers for hydropower generation. Firstly, a hybrid algorithm namely firefly particle swarm optimization (FPSO) and series division method (SDM) based on the practical swarm optimization and the firefly algorithm is proposed. …”
Get full text
Get full text

Mobile data gathering algorithms for wireless sensor networks by Ghaleb, Mukhtar Mahmoud Yahya

“…In this research, a Mobile Data Gathering based Network Layout (MDG-NL) algorithm is proposed. …”
Get full text
Get full text

Enhanced stability and performance of the tidal energy conversion system using adaptive optimum relation-based MPPT algorithms by Noor Lina, Ramli, Mohd Rusllim, Mohamed, Wan Ismail, Ibrahim, Kurukuri, Peddakapu

“…The A-ORB algorithm integrates the optimum relation-based (ORB) approach with Hill Climb Search (HCS), along with an adaptive gain adjustment mechanism that dynamically tunes the parameter K based on power variation (ΔP). …”
Get full text
Get full text
Get full text

Information Theoretic-based Feature Selection for Machine Learning by Muhammad Aliyu, Sulaiman

“…Three major factors that determine the performance of a machine learning are the choice of a representative set of features, choosing a suitable machine learning algorithm and the right selection of the training parameters for a specified machine learning algorithm. …”
Get full text
Get full text
Get full text
Get full text

A Study On The Application Of Gravitational Search Algorithm In Optimizing Stereo Matching Algorithm’s Parameters For Star Fruit Inspection System by Zainal Abidin, Amar Faiz, Mohd Ali, Nursabillilah, Mat Zain, Norlina, Abdul Majid, Masmaria, Rifin, Rozi, Kadiran, Kamaru Adzha, Mohd Mokji, Ahmad Musa, Tan, Kok, Amirulah, Rahman

“…Benchmarking has done by comparing the result obtained with the previous literature that implements Particle Swarm Optimization. The result indicates that the application of Gravitational Search Algorithm as parameters tuner for stereo matching’s parameters tuning is essentially on par with the Particle Swarm Optimization Algorithm.…”
Get full text
Get full text
Get full text

Heterogenous adaptive ant colony optimization with 3-opt local search for the travelling salesman problem by Tuani Ibrahim, Ahamed Fayeez, Keedwell, Edward, Collett, Matthew

“…The majority of optimization algorithms require proper parameter tuning to achieve the best performance. …”
Get full text
Get full text
Get full text
Get full text

A Hybrid Least Squares Support Vector Machine with Bat and Cuckoo Search Algorithms for Time Series Forecasting by Mohammed, Athraa Jasim, Ghathwan, Khalil Ibrahim, Yusof, Yuhanis

“…However, its operation relies on two important parameters (regularization and kernel). Pre-determining the values of parameters will affect the results of the forecasting model; hence, to find the optimal value of these parameters, this study investigates the adaptation of Bat and Cuckoo Search algorithms to optimize LSSVM parameters. …”
Get full text
Get full text

Development of optimized maintenance scheduling model for coal-fired power plant boiler by Noor Fazreen Binti Ahmad Fuzi, Ms.

“…The optimal schedules obtained were compared with the actual based on parameters and judgement from power plant planning team. …”

An Improved Hybrid of Particle Swarm Optimization and the Gravitational Search Algorithm to Produce a Kinetic Parameter Estimation of Aspartate Biochemical Pathways by Ahmad Muhaimin, Ismail, Mohd Saberi, Mohamad, Hairudin, Abdul Majid, Khairul Hamimah, Abas, Safaai, Deris, Zaki, Nazar, Siti Zaiton, Mohd Hashim, Zuwairie, Ibrahim, Muhammad Akmal, Remli

“…The results show that the proposed algorithm outperformed other standard optimization algorithms in terms of accuracy and near-optimal kinetic parameter estimation. …”
Get full text
Get full text
Get full text

Parameters optimization of surface grinding process with particles swarm optimization, gravitational search, and sine cosine algorithms: a comparative analysis by Asrul, Adam

“…In this paper, three optimization algorithms which are particle swarm optimization (PSO), gravitational search, and Sine Cosine algorithms are employed to optimize the grinding process parameters that may either reduce the cost, increase the productivity or obtain the finest surface finish and resulting a higher grinding process performance. …”
Get full text
Get full text
Get full text

Vehicular traffic noise prediction and propagation modelling using artificial neural network by Ahmed, Ahmed Abdulkareem

“…The neural network and its hyperparameters were optimized through a systematic optimization procedure based on a grid search approach. …”
Get full text
Get full text
Get full text

A new HMCR parameter of harmony search for better exploration by Mansor, N.F., Abas, Z.A, Rahman, A.F.N.A, Shibghatullah, A.S., Sidek, S.

“…As a meta-heuristic algorithm, Harmony Search (HS) algorithm is a population-based meta-heuristics approach that is superior in solving diversified large scale optimization problems. …”
Get full text
Get full text

A new HMCR parameter of harmony search for better exploration by Nur Farraliza, Mansor, Abas, Z.A, Rahman, A.F.N.A, Shibghatullah, A.S., Sidek, S

“…As a meta-heuristic algorithm, Harmony Search (HS) algorithm is a population-based meta-heuristics approach that is superior in solving diversified large scale optimization problems. …”
Get full text
Get full text

Bouc-Wen hysteresis parameter optimization for magnetorheological damper using Cuckoo search algorithm by Rosmazi, Rosli, Zamri, Mohamed, G., Priyandoko, M. F. F., Ab Rashid

“…Cuckoo search algorithm is used to optimize the parameters in phenomenological Bouc-Wen model. …”
Get full text
Get full text
Get full text

Review on the parameter settings in harmony search algorithm applied to combinatorial optimization problems by Ahmed, Bilal, Hamdan, Hazlina, Muhammed, Abdullah, Husin, Nor Azura

“…Harmony search algorithm (HSA) is relatively considered as one of the most recent metaheuristic algorithms. …”
Get full text
Get full text