Search Results - (( based application ((bees algorithm) OR (means algorithms)) ) OR ( _ application use algorithm ))

Data clustering using the bees algorithm by Pham, D.T, Otri, S., Afify, A., Mahmuddin, Massudi, Al-Jabbouli, H.

Get full text
Get full text

Enhanced artificial bee colony-least squares support vector machines algorithm for time series prediction by Zuriani, Mustaffa

“…This study proposed a hybrid algorithm, based on Artificial Bee Colony (ABC) and LSSVM, that consists of three algorithms; ABC-LSSVM, lvABC-LSSVM and cmABC-LSSVM. …”
Get full text
Get full text
Get full text

A class skew-insensitive ACO-based decision tree algorithm for imbalanced data sets by Mohd Razali, Muhamad Hasbullah, Saian, Rizauddin, Yap, Bee Wah, Ku-Mahamud, Ku Ruhana

“…This study proposed an enhanced algorithm called hellingerant-tree-miner (HATM) which is inspired by ant colony optimization (ACO) metaheuristic for imbalanced learning using decision tree classification algorithm. …”
Get full text
Get full text
Get full text

Effectiveness of nature-inspired algorithms using ANFIS for blade design optimization and wind turbine efficiency by Sarkar, Md. Rasel, Julai, Sabariah, Chong, Wen Tong, Toha @ Tohara, Siti Fauziah

“…The difference between optimized and predicted is very small which implies the effectiveness of nature-inspired algorithms in this application. In addition, the value of RMSE and R2 of the ABC-ANFIS algorithm were lower (indicating that the result obtained is more accurate) than the ACO and PSO algorithms…”
Get full text
Get full text
Get full text
Get full text
Get full text

A Hybrid ANFIS-ABC Based MPPT Controller for PV System with Anti-Islanding Grid Protection: Experimental Realization by Padmanaban S., Priyadarshi N., Bhaskar M.S., Holm-Nielsen J.B., Ramachandaramurthy V.K., Hossain E.

Artificial Bee Colony-based satellite image contrast and brightness enhancement technique using DWT-SVD by Bhandari, A.K., Soni, V., Kumar, A., Singh, G.K.

Get full text
Get full text

Effectiveness of Nature-Inspired Algorithms using ANFIS for Blade Design Optimization and Wind Turbine Efficiency by Sarkar, Md Rasel, Julai, Sabariah, Chong, Wen Tong, Toha, Siti Fauziah

“…In this paper, nature-inspired algorithms, e.g., ant colony optimization (ACO), artificial bee colony (ABC), and particle swarm optimization (PSO) are used to search for the blade parameters that can give the maximum value of Cp for HAWT. …”
Get full text
Get full text

An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP by Bibi Aamirah Shafaa Emambocus, Muhammed Basheer Jasser, Muzaffar Hamzah, Aida Mustapha, Angela Amphawan

“…The Traveling Salesman Problem (TSP) is a combinatorial optimization problem that is useful in a number of applications. Since there is no known polynomial-time algorithm for solving large scale TSP, metaheuristic algorithms such as Ant Colony Optimization (ACO), Bee Colony Optimization (BCO), and Particle Swarm Optimization (PSO) have been widely used to solve TSP problems through their high quality solutions. …”
Get full text
Get full text
Get full text
Get full text
Get full text

A novel swarm-based optimisation algorithm inspired by artificial neural glial network for autonomous robots by Ismail, Amelia Ritahani, Tumian, Afidalina

“…The main idea in this algorithm is the indirect communication between the ants which is established by the means of pheromones in finding the shortest path between their nest and food [14]. …”
Get full text
Get full text

Optimizing dam and reservoir operations using machine learning by Mohammad Abdullah Adib Almubaidin

An improved artificial bee colony algorithm based on mean best-guided approach for continuous optimization problems and real brain MRI images segmentation by Alrosan, Ayat, Alomoush, Waleed, Norwawi, Norita, Alswaitti, Mohammed, Makhadmeh, Sharif Naser

Application of the bees algorithm for constrained mechanical design optimisation problem by Kamaruddin, Shafie, Abd Latif, Mohd Arif Hafizi

Get full text
Get full text
Get full text

Using the bees algorithm to optimise a support vector machine for wood defect classification by Pham, D.T, Muhammad, Zaidi, Mahmuddin, Massudi, Ghanbarzadeh, Afshin, Koc, Ebubekir, Otri, Sameh

“…The algorithm, which is a swarm-based algorithm inspired by the food foraging behavior of honey bees, was also employed to select the components making up the feature vectors to be presented to the SVM. …”
Get full text
Get full text
Get full text

Optimal design of step – cone pulley problem using the bees algorithm by Yusof, Noor Jazilah, Kamaruddin, Shafie

Get full text
Get full text
Get full text
Get full text

Bees algorithm enhanced with Nelder and Mead method for numerical function optimisation by Kamaruddin, Shafie, Bahari, Muhammad Syahril, Pham, Duc Truong, Mohd Amin Hamzas, Mohd Fidzwan, Zakaria, S

Get full text
Get full text
Get full text
Get full text

Application of Bee Colony Optimization (BCO) in NP-Hard Problems by Kamarudin, Muhammad Sariy Syazwan

Get full text
Get full text

Average concept of crossover operator in real coded genetic algorithm by Abd Rahman, Rosshairy, Ramli, Razamin

Get full text
Get full text
Get full text

Adaptive filtering of EEG/ERP through bounded range artificial Bee Colony (BR-ABC) algorithm by Ahirwal, M.K., Kumar, A., Singh, G.K.

Get full text
Get full text

Leaf lesion classification (LLC) algorithm based on artificial bee colony (ABC) by Ahmad, Faudziah, Ku-Mahamud, Ku Ruhana, Sainin, Mohd Shamrie, Airuddin, Ahmad

Get full text
Get full text
Get full text

Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm by Reza M.S., Hannan M.A., Mansor M., Ker P.J., Rahman S.A., Jang G., Mahlia T.M.I.

“…The effectiveness of the proposed LSA + LSTM model is assessed using battery aging data from the NASA dataset. In addition, to validate the prediction performance of the proposed LSA + LSTM model, extensive comparisons are performed with other popular optimization-based deep learning methods including artificial bee colony (ABC) based LSTM (ABC + LSTM), gravitational search algorithm (GSA) based LSTM (GSA + LSTM), and particle swarm optimization (PSO) based LSTM (PSO + LSTM) model using different error matrices. …”