Search Results - (( time optimisation swarm algorithm ) OR ( java simulation optimization algorithm ))

Optimization of multi-holes drilling path using particle swarm optimization by Najwa Wahida, Zainal Abidin

“…The performance of PSO was then compared with other meta-heuristic algorithms, including Genetic Algorithm (GA) and Ant Colony Optimisation (ACO), Whale Optimisation Algorithm (WOA), Ant Lion Optimiser (ALO), Dragonfly Algorithm (DA), Grasshopper Optimisation Algorithm (GOA), Moth Flame Optimisation (MFO) and Sine Cosine Algorithm (SCA). …”
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Intergrated multi-objective optimisation of assembly sequence planning and assembly line balancing using particle swarm optimisation by M. F. F., Ab Rashid

“…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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Multi-Objective Discrete Particle Swarm Optimisation Algorithm for Integrated Assembly Sequence Planning and Assembly Line Balancing by M. F. F., Ab Rashid, Hutabarat, Windo, Tiwari, Ashutosh

“…A statistical test of the algorithm performance indicates that the proposed multi-objective discrete particle swarm optimisation algorithm presents significant improvement in terms of the quality of the solution set towards the Pareto optimal set.…”
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Evolvable traffic signal control for intersection congestion alleviation with enhanced particle swarm optimisation by Helen Sin Ee Chuo, Min Keng Tan, Alex Chee Hoe Chong, Renee Ka Yin Chin, Kenneth Tze Kin Teo

“…This work simulates traffic system and develop an optimising algorithm to instruct the traffic signal timing plan. …”
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Optimisation of PID controller for load frequency control in two-area power system using evolutionary particle swarm optimisation by Illias, Hazlee Azil, Zahari, A.F.M., Mokhlis, Hazlie

“…Therefore, to overcome this situation, in this work, particle swarm optimization (PSO) and evolutionary particle swarm optimization (EPSO) algorithms were employed in a LFC of twoarea power system to optimise the performance of the PID controller. …”
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Hybrid firely and particle swarm optimisation algorithm for optimal dimming level and energy saving in lecturer’s room by Nik Ahmad, Nik Sahidah

“…In order to identify the optimal dimming level, energy consumption, simulation time and luminaire performance, this research work presents the comparison between light-emitting diode (LED) and fluorescent luminaires using the HFPSO algorithm and using the particle swarm optimisation (PSO) algorithm and the firefly algorithm (FA). …”
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Optimisation of vehicle routing problem with time windows using Harris Hawks optimiser by Chai, S. W., Kamaluddin, M. R., Ab Rashid, M. F. F.

“…To the best of authors’ knowledge, this is the first attempt to build HHO algorithm for VRPTW problem. Computational experiment indicated that the HHO came up with the best average fitness compared with other comparison algorithms in this study including Artificial Bee Colony (ABC), Particle Swarm Optimisation (PSO), Moth Flame Optimiser (MFO), and Whale Optimisation Algorithm (WOA). …”
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Position tracking of DC motor with PID controller utilising particle swarm optimisation algorithm with levy flight and doppler effect by Nur Iffah, Mohamed Azmi, Nafrizuan, Mat Yahya

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Combining autoregressive integrated moving average with Long Short-Term Memory neural network and optimisation algorithms for predicting ground water level by Sheikh Khozani Z., Barzegari Banadkooki F., Ehteram M., Najah Ahmed A., El-Shafie A.

“…Brain; Forecasting; Genetic algorithms; Groundwater resources; Light modulators; Long short-term memory; Soil conservation; Time series; Water conservation; Water levels; Water management; Auto regressive integrated moving average models; Auto-regressive integrated moving average model model; Ground water level; Long short-term memory model; Memory modeling; Non linear; Optimisations; Optimization algorithms; Salp swarms; Times series; Groundwater…”

A comparative evaluation of PID-based optimisation controller algorithms for DC motor by Ahamed S.R., Parumasivam P., Hossain Lipu M.S., Hannan M.A., Ker P.J.

Particle Swarm Optimised Controller for Solid-State Transfer Switch Towards Fast Power Transfer and PQ Mitigation by Sebastian G., Hannan M.A., Al-Shetwi A.Q., Ker P.J., Muttaqi K.M., Uddin M.N.

Identification of transformer fault based on dissolved gas analysis using hybrid support vector machine-modified evolutionary particle swarm optimisation by Illias, Hazlee Azil, Wee, Zhao Liang

“…Dissolved Gas Analysis (DGA) technique is commonly used to identify oil-filled power transformer fault type but utilisation of artificial intelligence method with optimisation methods has shown convincing results. In this work, a hybrid support vector machine (SVM) with modified evolutionary particle swarm optimisation (EPSO) algorithm was proposed to determine the transformer fault type. …”
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An improved fair nurse scheduling optimisation using particle swarm intelligent technique by Ramli, Mohamad Raziff

“…Nurse schedule is a list showing the arrangement such as dates and times of each employee must work at a particular period of time. …”
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A modified artificial bee colony algorithm to optimise integrated assembly sequence planning and assembly line balancing by M. F. F., Ab Rashid, N. M. Z., Nik Mohamed, A. N. M., Rose

“…Despite many optimisation algorithms that were proposed to optimise this problem, the existing researches on this problem were limited to Evolutionary Algorithm (EA), Ant Colony Optimisation (ACO), and Particle Swarm Optimisation (PSO). …”
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Time-varying water temperature modelling of steam distillation pilot plant using NARX-based binary particle swarm optimisation structure selection / Najidah Hambali … [et al.] by Hambali, Najidah, Taib, Mohd Nasir, Mohd Yassin, Ahmad Ihsan, Rahiman, Mohd Hezri Fazalul

“…This study reports a nonlinear modelling for a time-varying process of water temperature by utilising a Binary Particle Swarm Optimisation (BPSO) algorithm based on Nonlinear Auto-Regressive with eXogenous input (NARX) structure. …”
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Fruit-Fly Based Searching Algorithm For Cooperative Swarming Robotic System by Abidin, Zulkifli Zainal

“…A number of benchmark function processes were conducted to assess the performance of proposed FOA (Fly Optimisation Algorithm).…”
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Optimization Of Pid Controller Using Grey Wolf Optimzer And Dragonfly Algorithm by Nik Mohamed Hazli, Nik Muhammad Aiman

“…In this research, swarming intelligence is used to solve optimisation problem. …”
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Predicting municipal solid waste using a coupled artificial neural network with archimedes optimisation algorithm and socioeconomic components by Liang G., Panahi F., Ahmed A.N., Ehteram M., Band S.S., Elshafie A.

Optimisation of automatic generation control performance in two-area power system with pid controllers using mepso / Lu Li by Lu , Li

“…Also, using MEPSO-TVAC algorithm, the performance of AGC by using two PID controllers is better in terms of rise time and settling time than using one PID controller. …”
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Performance evaluation of load balancing algorithm for virtual machine in data centre in cloud computing by Parmesivan, Yuganes, Hasan, Sazlinah, Muhammed, Abdullah

“…Cloud computing has become biggest buzz in the computer era these days.It runs entire operating systems on the cloud and doeverything on cloud to store data off-site.Cloud computing is primarily based on grid computing, but it’s a new computational model.Cloud computing has emerged into a new opportunity to further enhance way of hosting data centre and provide services.The primary substance of cloud computing is to deal the computing power,storage,different sort of stages and services which assigned tothe external users on demand through the internet.Task scheduling in cloud computing is vital role optimisation and effective dynamic resource allocation for load balancing.In cloud, the issue focused is under utilisation and over utilisation of the resources to distribute workload of multiple network links for example,when cloud clients try to access and send request tothe same cloud server while the other cloud server remain idle at that moment, leads to the unbalanced of workload on cloud data centers.Thus, load balancing is to assign tasks to the individual cloud data centers of the shared system so that no single cloud data centers is overloaded or under loaded.A Hybrid approach of Honey Bee (HB) and Particle Swarm Optimisation (PSO) load balancing algorithm is combined in order to get effective response time.The proposed hybrid algorithm has been experimented by using CloudSim simulator.The result shows that the hybrid load balancing algorithm improves the cloud system performance by reducing the response time compared to the Honey Bee (HB) and Particle Swarm Optimisation (PSO) load balancing algorithm.…”
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