Search Results - (( based optimisation based algorithm ) OR ( time estimation path algorithm ))
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Analysis of Dijkstra’s and A* algorithm to find the shortest path
Published 2015“…In this study, two algorithms will be focused on. This study compares the Dijkstra’s, and A* algorithm to estimate search time and distance of algorithms to find the shortest path. …”
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Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…These algorithms are inspired by the estimation capability of the well-known Kalman filter estimation method. …”
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Optimization Of Pid Controller Using Grey Wolf Optimzer And Dragonfly Algorithm
Published 2018“…The expected result is the algorithms are able to optimise the PID controller. …”
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Intergrated multi-objective optimisation of assembly sequence planning and assembly line balancing using particle swarm optimisation
Published 2013“…The aim of this research is to establish a methodology and algorithm for integrating ASP and ALB optimisation using Particle Swarm Optimisation. …”
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Simulation of shortest path using a-star algorithm / Nurul Hani Nortaja
Published 2004“…Definitely this best first search algorithm saves the searching time and improves performance of shortest path finding.…”
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Real-Time Optimal Trajectory Correction (ROTC) for autonomous quadrotor / Noorfadzli Abdul Razak
Published 2018“…However, existing algorithm seems too complicated to be applied. Since there is no technique can enable the quadrotor to implement precision navigation application, the research proposed a Real-Time Optimal Trajectory Correction (ROTC) algorithm. …”
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Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System
Published 2020“…Many optimisation-based intrusion detection algorithms have been developed and are widely used for intrusion identification. …”
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Chaotic Immune Symbiotic Organisms Search algorithm for solving optimisation problem
Published 2023“…Heuristics-based algorithms were introduced to counter the problem faced by classical optimisation techniques. …”
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Bats echolocation-inspired algorithms for global optimisation problems
Published 2016“…The algorithm is a hybrid algorithm that operates using dual level search strategy that takes merits of a particle swarm optimisation algorithm and a modified adaptive bats sonar algorithm. …”
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Aco-based feature selection algorithm for classification
Published 2022“…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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Application of the bees algorithm for constrained mechanical design optimisation problem
Published 2019“…Nowadays, many optimisation algorithms have been introduced due to the advancement of technology such as Teaching Learning Based Optimisation (TLBO), Ant Colony Optimisation (ACO), Particle Swarm Optimisation (PSO) and the Bees Algorithm. …”
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Evaluation of Vector Evaluated Particle Swarm Optimisation Enhanced with Non-dominated Solutions and Multiple Nondominated Leaders based on WFG Test Functions
Published 2014“…The improved VEPSO algorithms have been subjected to a series of numerical experiments based on ZDT benchmark datasets. …”
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Metaheuristic algorithms applied in ANN salinity modelling
Published 2024“…The CPSOCGSA performance was evaluated by various single-based ones, including multi-verse optimiser (MVO), marine predator's optimisation algorithm (MPA), particle swarm optimiser (PSO), and the slim mould algorithm (SMA). …”
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Nonlinear adaptive algorithm for active noise control with loudspeaker nonlinearity
Published 2014“…The proposed THF-NLFXLMS algorithm models the Wiener secondary path and applies the estimated degree of nonlinearity of the nonlinear secondary path in the control algorithm design. …”
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A hyper-heuristic cost optimisation approach for Scientific Workflow Scheduling in cloud computing
Published 2018“…Thus, the main objective of this paper is to propose a Completion Time Driven Hyper-Heuristic (CTDHH) approach for cost optimisation of SWFS in a cloud environment. The CTDHH approach employs four well-known population-based meta-heuristic algorithms, which act as Low Level Heuristic (LLH) algorithms. …”
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