Search Results - (( using simulation case algorithm ) OR ( simulation optimisation based algorithm ))

Modelling and optimisation of blood glucose control for type 1 diabetes using multi-parametric programming and model-based predictive control (mp-MPC) / Associate Professor Dr Ayub... by Md. Som, Ayub

“…AU simulation and optimisation works are carried out using gPROMS™. …”
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Optimisation of fed-batch fermentation process using deep reinforcement learning by Chai, Wan Ying

“…The proposed deep reinforcement learning algorithm, which integrates an artificial neural network with traditional reinforcement learning, was formulated based on the optimisation objective by manipulating only the substrate feeding rate. …”
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Optimisation of laser cutting parameters of oil palm wood / Harizam Mohd Zin by Harizam, Mohd Zin

“…In some cases, the prediction errors of Taguchi ANN model was found larger than 10% even using a Levenberg Marquardt training algorithm. …”
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Efficient task scheduling strategies using symbiotic organisms search algorithm for cloud computing environment by Sa'ad, Suleiman

“…However, the efficiency of the clouds drops as the size of the search space gets larger, like in the case of most metaheuristic optimisation algorithms. …”
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An elitist-flower pollination-based strategy for constructing sequence and sequence-less t-way test suite by Abdullah, Nasser, Kamal Z., Zamli, Alsewari, Abdulrahman A., Ahmed, Bestoun S.

“…In line with the upcoming of a new field called search-based software engineering (SBSE), many newly developed t-way strategies adopting meta-heuristic algorithms can be seen in the literature for constructing interaction test suite (such as simulated annealing (SA), genetic algorithm (GA), ant colony optimisation algorithm (ACO), particle swarm optimisation (PSO), harmony search (HS) and cuckoo search (CS). …”
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Distributed learning based energy-efficient operations in small cell networks by Mughees, Amna

“…Both user association and power allocation are solved in their respective action spaces. Simulation results demonstrate improved performance in power consumption, load, sum rate, utility, learning rate, convergence, and energy efficiency for small base stations (SBSs) and user equipment (UEs) compared to four benchmarked algorithms, including WMMSE, game theory, Q-learning, and DRL. …”
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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

“…Part of Intelligent Transportation Systems development involves advanced computation in traffic management to cope for the projecting congestion trend. This work simulates traffic system and develop an optimising algorithm to instruct the traffic signal timing plan. …”
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Application of the Whale Optimization Algorithm (WOA) in Reservoir Optimization Operation Under Investigation of Climate Change Impact: A Case Study at Klang Gate Dam, Malaysia by Lai V., Huang Y.F., Koo C.H., Ahmed A.N., El-Shafie A.

Optimisation of tilt angles for fixed PV Panel via computational algorithm by Tang, Hong Wei

“…The investigation was performed based on simulation using MATLAB® (R2021a), and the Weather Data files were all obtained from JRC Photovoltaic Geographical Information System (PVGIS). …”
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Optimising ventilation for thermal comfort and infection control in vehicles: A review on CFD applications and techniques by Tan, Kai Ying, Wong, Sien Jie, Tan, Huiyi, Kek, Hong Yee, Mohd Hafiz Dzafan, Othman, Wong, Syie Luing, Mohamad Nur Hidayat, Mat, Fong, Yi Ka, Wong, Keng Yinn

“…The review highlights that RNG k-ε and SST k-ω are among the most commonly used turbulence models in vehicle cabin simulations, based on their suitability for modelling complex airflow patterns and their validation against measured data. …”
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Ocean Colour Remote Sensing Of Case 2 Waters Using An Optimised Neural Network by Anwar, Saumi Syahreza

“…This study focused on the development of the new algorithm for retrieving ocean colour products of Case 2 water types using the neural network (NN) model and multiple types of remotely sensed data as inputs. …”
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elopment of Neural Network Model for Predicting Crucial Product Properties or Yield for Optimisation of Refinery Operation by Mohamad, Sharliza

“…Various configurations of neural network model were tested to choose the best model to represent each case study. The model selected has the smallestmean squared error when simulated using test data. …”
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Development of a particle swarm optimisation model for estimating the homogeneity of a mixture inside a newly designed CNG-H2-AIR mixer for a dual fuel engine: an experimental and... by Mahmood, Hussein Adel, Adam, Nor Mariah, Sahari, Barkawi, Masuri, Siti Ujila

“…The particle swarm optimisation (PSO) algorithm was used to solve an optimisation problem and achieve this outcome. …”
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A new optimisation framework based on Monte Carlo embedded hybrid variant mean–variance mapping considering uncertainties by Norhafidzah, Mohd Saad, Muhamad Zahim, Sujod, Mohd Ikhwan, Muhammad Ridzuan, Mohammad Fadhil, Abas, Mohd Shawal, Jadin, Mohd Fadzil, Abdul Kadir

“…Simulations were run for several scenarios in three load cases based on 288 segments: residential, commercial, and industrial urban loads. …”
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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.

A simulation based fly optimisation algorithm for swarms of mini autonomous surface vehicles application by Zainal Abidin, Zulkifli

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Single-Solution Simulated Kalman Filter Algorithm for Global Optimisation Problems by Nor Hidayati, Abdul Aziz, Zuwairie, Ibrahim, Nor Azlina, Ab. Aziz, Mohd Saberi, Mohamad, Watada, Junzo

“…In comparison, the proposed ssSKF algorithm supersedes the original population-based Simulated Kalman Filter (SKF) algorithm by operating with only a single agent, and having less parameters to be tuned. …”
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A new history matching sensitivity analysis framework with random forests and Plackett-Burman design by Aulia, A., Jeong, D., Mohd Saaid, I., Shuker, M.T., El-Khatib, N.A.

“…The proposed sensitivity analysis framework starts with generating samples/simulations using Plackett- Burman design. Here, each simulation is executed based on different combinations of the parameters' input values. …”
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Single-solution Simulated Kalman Filter algorithm for global optimisation problems by Abdul Aziz, N.H., Ibrahim, Z., Ab Aziz, N.A., Mohamad, M.S., Watada, J.

“…This paper introduces single-solution Simulated Kalman Filter (ssSKF), a new single-agent optimisation algorithm inspired by Kalman Filter, for solving real-valued numerical optimisation problems. …”
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Single-solution Simulated Kalman Filter algorithm for global optimisation problems by Abdul Aziz, N.H., Ibrahim, Z., Ab Aziz, N.A., Mohamad, M.S., Watada, J.

“…This paper introduces single-solution Simulated Kalman Filter (ssSKF), a new single-agent optimisation algorithm inspired by Kalman Filter, for solving real-valued numerical optimisation problems. …”
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