Search Results - (( parameter optimization based algorithm ) OR ( changes optimisation _ algorithm ))

Design of low order quantitative feedback theory and H-infinity-based controllers using particle swarm optimisation for a pneumatic actuator system by Ali, Hazem I.

“…These algorithms are designed to achieve the robustness over a wide range of system parameters change and disturbances. …”
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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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Optimised multi-robot path planning via smooth trajectory generation by Loke, Zhi Yu

“…Particle swarm optimization (PSO) outperforms conventional methods like artificial potential fields (APF), the Dijkstra algorithm, and the A* algorithm in path planning for mobile robots. …”
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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things by Hadi, Ahmed Adnan

“…Hence, the algorithm must overcome the problem of dynamic updates in the internal parameters or counter the concept drift. …”
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Optimisation and control of fed-batch yeast production using q-learning by Helen, Chuo Sin Ee

“…To cater for the process disturbance, Q-learning with exploration (QLE) has been included in this work for online optimisation. QLE signifies the importance of exploration from time to time based on the developed “past experience” in Q-table to optimise the process. …”
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Forecasting of fine particulate matter based on LSTM and optimization algorithm by Zaini N., Ahmed A.N., Ean L.W., Chow M.F., Malek M.A.

“…Long short-term memory based on metaheuristic algorithms, namely particle swarm optimization and sparrow search algorithm (PSO-LSTM and SSA-LSTM), are first developed and applied to determine the significance input combination to the changes of PM2.5 concentration at respective target stations. …”

Cuckoo optimised 2DOF controllers for stabilising the frequency changes in restructured power system with wind-hydro units by Peddakapu, K., M. R., Mohamed, M. H., Sulaiman, Srinivasarao, P., Kishore, D. J. K., P. K., Leung

“…In this work, proportional-integral (PI), proportional-integral derivative (PID), and 2-degree of freedom PID (2-DOF-PID) controllers are proposed to stabilise the variations in the system parameters at distinct loading conditions. Different types of metaheuristic optimisation methods like teaching–learning-based optimisation (TLBO) and cuckoo search algorithms are suggested to acquire the optimal gain values of the proposed controllers. …”
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Optimisation of support vector machine hyperparameters using enhanced artificial bee colony variant to diagnose breast cancer by Ravindran, Nadarajan

“…The performance of SVM can be affected by hyperparameters, which are kernel scale and known as gamma and regularization parameters (C). A metaheuristic algorithm is introduced to optimise the hyperparameters. …”
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Optimal PI controller based PSO optimization for PV inverter using SPWM techniques by Abdolrasol M.G.M., Hannan M.A., Hussain S.M.S., Ustun T.S.

Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems by Kek, Sie Long

“…The main idea is the integration of optimal control and parameter estimation. In this work, a simplified model-based optimal control model with adjustable parameters is constructed. …”
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On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing by Kamal Z., Zamli, Alsariera, Yazan A., Nasser, Abdullah B., Alsewari, Abdulrahman A.

“…In doing so, this paper reviews two existing parameter free optimization algorithms involving Teaching Learning Based Optimization (TLBO) and Fruitfly Optimization Algorithm (FOA) in an effort to promote their adoption for CIT.…”
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Finite impulse response optimizers for solving optimization problems by Ab Rahman, Tasiransurini

“…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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Finite impulse response optimizers for solving optimization problems by Tasiransurini, Ab Rahman

“…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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LS-SVM Hyper-parameters Optimization Based on GWO Algorithm for Time Series Forecasting by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, M. N. M., Kahar

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Enhanced gravitational search algorithm for nano-process parameter optimization problem / Norlina Mohd Sabri by Mohd Sabri, Norlina

“…Based on the capabilities of the metaheuristic algorithms, this research is proposing the enhanced Gravitational Search Algorithm (eGSA) to solve the nano-process parameter optimization problem. …”
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Optimisation of energy efficient Assembly Sequence Planning using Moth-Flame Optimisation alghorithm by Muhammad Arif, Abdullah

“…For optimisation purpose, this research proposed a relatively new algorithm called the Moth-Flame Optimisation (MFO). …”
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Optimization of turning parameters using genetic algorithm method by Shah Izwandi, Mohd Zawawi

“…This study about development of optimization for turning parameters based on the Genetic Algorithm (GA). …”
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Optimization of milling parameters using ant colony optimization by Mohd Saupi, Mohd Sauki

“…The simulation based on ACO algorithm are successful develop and the optimization of parameters values is to maximize the production rate is obtain from the simulation.…”
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Improvement of horizontal streak on disparity map thru parameter optimization for stereo vision algorithm by Gan, Melvin Yeou Wei, Hamzah, Rostam Affendi, Nik Anwar, Nik Syahrim, Herman, Adi Irwan, Jamil Alsayaydeh, Jamil Abedalrahim

“…Then, the research continues to optimize the proposed local based SVDM algorithm through parameters optimization in obtaining the final disparity map. …”
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Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study by Li Yu Yab, Li Yu Yab, Wahid, Noorhaniza, A Hamid, Rahayu

“…—Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO) are well-perform metaheuristic algorithms used by various researchers in solving feature selection problems. …”
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