Search Results - global optimisation method algorithm*

Bats echolocation-inspired algorithms for global optimisation problems by Nafrizuan, Mat Yahya

“…The works related to swarm intelligence algorithms include the development of the algorithm itself, its modification and improvisation as well as its application in solving global optimisation problems. …”
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An improvement of back propagation algorithm using halley third order optimisation method for classification problems by Abdul Hamid, Norhamreeza

“…This algorithm utilises first order optimisation method namely Gradient Descent (GD) method which attempts to minimise the error of network. …”
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Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse) by Jia, Xing Yeoh, Chuii, Khim Chong, Mohd Saberi, Mohamad, Yee, Wen Choon, Lian, En Chai, Safaai, Deris, Zuwairie, Ibrahim

“…The hybrid of Differential Evolution algorithm with Kalman Filtering and Bacterial Foraging algorithm is a novel global optimisation method implemented to obtain the best kinetic parameter value. …”
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An Efficient Hybrid Conjugate Gradient Method for Unconstrained Optimisation by Mamat, Prof. Dr. Mustafa

“…One of the common efficient techniques to solve large-scale unconstrained optimisation issues is the conjugate gradient method, because of its simplicity, low memory consumptions and global convergence properties. …”
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Improvement Of Stereo Matching Algorithm Based On Sum Of Gradient Magnitude Differences And Semi-Global Method With Refinement Step by Hamzah, Rostam Affendi, Ibrahim, Haidi

“…A new stereo matching algorithm which uses improved matching cost computation and optimisation using the semi-global method (SGM) is proposed.The absolute difference is sensitive to low textured regions and high noise on the stereo images with radiometric distortions. …”
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Design Of Perturbative Hyper-Heuristics For Combinatorial Optimisation by Choong, Shin Siang

“…Exact algorithm is a sub-class of techniques that is able to guarantee global optimality. …”
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Aco-based feature selection algorithm for classification by Al-mazini, Hassan Fouad Abbas

“…The modified graph clustering ant colony optimisation (MGCACO) algorithm is an effective FS method that was developed based on grouping the highly correlated features. …”
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The fusion of particle swarm optimization (PSO) and interior point method (IPM) as cooperative movement control algorithm in Swarm Robotics / Dada Emmanuel Gbenga by Dada Emmanuel, Gbenga

“…Also, many of these PSO algorithms employed hybrid methods that integrate other optimisation algorithms with the standard PSO. …”
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Optimisation of support vector machine hyperparameters using enhanced artificial bee colony variant to diagnose breast cancer by Ravindran, Nadarajan

“…Breast cancer is the leading cause of cancer-related deaths among women globally. Early detection through methods such as mammography and biopsy are crucial in reducing cancer-related mortality. …”
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Parametric modelling of a TRMS using dynamic spread factor particle swarm optimisation by Toha, Siti Fauziah, Abd Latiff, I., Mohamad, M., Tokhi, M Osman

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An enhanced computational model based on social spider optimisation algorithm for EEG- based emotion recognition by Al-Qammaz, Abdullah Yousef Awwad

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An improved particle swarm optimization algorithm for data classification by Waqas Haider Bangyal, Kashif Nisar, Tariq Rahim Soomro, Ag Asri Ag Ibrahim, Ghulam Ali Mallah, Nafees Ul Hassan, Najeeb Ur Rehman

“…Particle Swarm Optimization (PSO) is a metaheuristic algorithm based on swarm intelligence, widely used to solve global optimisation problems throughout the real world. …”
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Emission constrained economic dispatch by using stochastic optimisers by Razali N.M.M., Teh Y.Y.

“…The paper presents the solutions for ECED problem by using two stochastic optimisers; the Genetic Algorithm (GA) and Particle Swarm Optimizer (PSO). …”

Sensitivity analysis of GA parameters for ECED problem by Kamil K., Razali N.M.M., Teh Y.Y.

“…Besides the conventional method by using the Lagrange Multiplier several evolutionary computation techniques such as Genetic Algorithm, Particle Swarm Optimisation, Ant Colony and Differential Evolution have been gaining popularity in solving general economic dispatch problems due to their desirable characteristics such as non-gradient dependent and ability to search for global optima. …”

Gooseneck barnacle optimization algorithm: A novel nature inspired optimization theory and application by Ahmed, Marzia, Mohd Herwan, Sulaiman, Ahmad Johari, Mohamad, Rahman, Mostafijur

“…This paper introduces the Gooseneck Barnacle Optimisation Algorithm (GBO) as a novel evolutionary method inspired by the natural mating behaviour of gooseneck barnacles, which involves sperm casting and self-fertilization. …”
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Global warming: predicting OPEC carbon dioxide emissions from petroleum consumption using neural network and hybrid cuckoo search algorithm by Haruna, Chiroma, Abdul-Kareem, Sameem, Mohd Nawi, Nazri, Gital, Abdulsam Ya'u, Shuib, Liyana, Abubakar, Adamu, Rahman, Muhammad Zubair, Herawan, Tutut

“…To improve effectiveness of the ANN, the cuckoo search algorithm was hybridised with accelerated particle swarm optimisation for training the ANN to build a model for the prediction of OPEC CO2 emissions. …”
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Gps solution for active queue management using android platform by Liu, Yu Yao

“…Since queueing in different locations is considered as a optimisation problem, several algorithms are reviewed to tackle the problem, such as brute force method, nearest neighbour algorithm, and branch and bound algorithm. …”
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Implementation of simulated annealing for two variables non-linear function by Engku Ahmad Rafiqi, Engku Ariff, Sakinah, Zakaria, Maliki, Ibrahim

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Enhanced convergence of Bat Algorithm based on dimensional and inertia weight factor by Ramli, Mohamad Raziff, Abal Abas, Zuraida, Desa, Mohammad Ishak, Zainal Abidin, Zaheera, Al Azzam, Malik Bader Hasan

“…Heuristic optimisation method typically hinges on the efficiency in exploitation and global diverse exploration. …”
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Investigating The Performance Of Metaheuristics To Optimize The Revenue Of Semiconductor Supply Chain by Roslee, Muhammad Sharifuddin

“…Investigating the performance of metaheuristics to optimise the revenue of the semiconductor supply chain is the final year project that focuses on to identify the supply chain shortage problem related to semiconductors and to compare among the 20 metaheuristics algorithm optimization programmes capable of optimising the semiconductor supply chain. …”
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