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

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

“…According to [13], the two best-known swarm intelligence algorithms are Particle Swarm Optimisation (PSO) and Ant Colony Optimisation (ACO). …”
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An Improved VEPSO Algorithm for Multi-objective Optimisation Problems by Kamarul Hawari, Ghazali, Zuwairie, Ibrahim, Faradila, Naim, Kian, Sheng Lim, Salinda, Buyamin, Anita, Ahmad, Sophan Wahyudi, Nawawi, Norrima, Mokhtar

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

“…One way to improve the multi-hole drilling is by optimising the tool path in the process. This research aims to model and optimise multi-hole drilling problems using Particle Swarm Optimisation (PSO) algorithm. …”
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Optimisation of two-sided assembly line balancing with resource constraints using modified particle swarm optimisation by Muhammad Razif, Abdullah Make, M. F. F., Ab Rashid

“…In the end, besides having good workload balance, the number of resources can also be optimised. For optimisation purpose, Particle Swarm Optimisation was modified to reduce the dependencies on a single best solution. …”
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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

“…Enhanced particle swarm optimisation algorithm is developed to ensure result consistency with smaller variation. …”
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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.

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…”

ANFIS modelling of a twin rotor system using particle swarm optimisation and RLS by Toha, Siti Fauziah, Tokhi, M. O.

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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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NARX modelling for steam distillation pilot plant using binary particle swarm optimisation technique / Najidah Hambali by Hambali, Najidah

“…This study proposes a system identification of SDPP using NARX model. The model structure selection of polynomial NARX had been focused on Binary Particle Swarm Optimisation (BPSO) algorithm. …”
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Metaheuristic algorithms applied in ANN salinity modelling by Khudhair, Zahraa S., Zubaidi, Salah L., Dulaimi, Anmar, Al-Bugharbee, Hussein, Muhsen, Yousif Raad, Putra Jaya, Ramadhansyah, Mohammed Ridha, Hussein, Raza, Syed Fawad, Ethaib, Saleem

“…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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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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Predicting longitudinal dispersion coefficient using ensemble models and optimized multi-layer perceptron models by Gholami M., Ghanbari-Adivi E., Ehteram M., Singh V.P., Najah Ahmed A., Mosavi A., El-Shafie A.

INTELLIGENT MODELLING OF GRADIENT FLEXIBLE PLATE STRUCTURE UTILISING HYBRID EVOLUTIONARY ALGORITHM by Muhammad Hasbollah, Hassan

“…The research utilised parametric system identification based on autoregressive with exogenous input (ARX) model structure. First, evolutionary algorithms, namely particle swarm optimisation (PSO) and grey wolf optimisation (GWO) were used in developing GFPS dynamic model and their performances were compared. …”
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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.

Optimization of two-sided assembly line balancing with resource constraints using modified particle swarm optimisation by Muhammad Razif, Abdullah Make, Mohd Fadzil Faisae, Ab Rashid

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Modelling of optimal placement and sizing of battery energy storage system using hybrid whale optimization algorithm and artificial immune system for total system losses reduct... by Wong Ling Ai

Optimisation of energy efficient hybrid flowshop scheduling problem using firefly algorithm by M. F. F., Ab Rashid, Mohd Abdul, Hadi Osman

“…The optimisation results indicated that the FA outperformed Ant Colony Optimisation, Particle Swarm Optimisation and Artificial Bee Colony algorithms in majority of the problems. …”
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Sustainable Management Of River Water Quality Using Artificial Intelligence Optimisation Algorithms by Chia, See Leng

“…Least Square Support Vector Machine (LSSVM) base models with linear kernel, polynomial kernel and Radial Basis Function (RBF) kernel and its hybrid models with integration of Hybrid of Particle Swarm Optimisation and Genetic Algorithm (HPSOGA), Whale Optimisation Algorithm based on Self-adapting Parameter Adjustment and Mix Mutation Strategy (SMWOA) and Ameliorative Moth Flame Optimisation (AMFO) were developed and used to predict the WQI at stations 1K06, 1K07 and 1K08 of the Klang River in Selangor, Malaysia. …”
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