Search Results - (( parameter optimisation based algorithm ) OR ( based estimation using algorithm ))

Augmented model based double iterative loop techniques for integrated system optimisation and parameter estimation of large scale industrial processes by Normah Abdullah, Brdys, M.A., Roberts, P.D.

“…The double iterative loop structures of the proposed algorithms use the real process measurement within the outer loops while the inner loops involve model based computation only. …”
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Kernel and multi-class classifiers for multi-floor wlan localisation by Abd Rahman, Mohd Amiruddin

“…For horizontal localisation, different algorithm based on multi-class k-nearest neighbour classifiers with optimisation parameter is presented. …”
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The development of parameter estimation method for Chinese hamster ovary model using black widow optimization algorithm by Nurul Aimi Munirah, ., Muhammad Akmal, Remli, Noorlin, Mohd Ali, Hui, Wen Nies, Mohd Saberi, Mohamad, Khairul Nizar Syazwan, Wan Salihin Wong

“…Metaheuristic parameter estimation is an algorithm framework that is processed using some technique to generate a pattern or graph. …”
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Genetic algorithm for control and optimisation of exothermic batch process by Tan, Min Keng

“…In general, most of the studies use predictive approach to estimate the process behaviour and a slave controller, usually proportional-integral-derivative (PID), is employed to control the process based on the estimated plant behaviour. …”
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INTELLIGENT MODELLING OF GRADIENT FLEXIBLE PLATE STRUCTURE UTILISING HYBRID EVOLUTIONARY ALGORITHM by Muhammad Hasbollah, Hassan

“…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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An extended adaptive mechanism of evolutionary based channel assignment via reinforcement by Teo, Kenneth Tze Kin, Yew, Hoe Tung, Lye, Scott Carr Ken, Lim, Kit Guan, Ang, Soo Siang, Khairul Anuar Mohamad, Ali Chekima, Liau, Chung Fan, Aroland Jilui Kiring

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Sensorless Adaptive Fuzzy Logic Control Of Permanent Magnet Synchronous Motor by Hafz Nour, Mutasim Ibrahim

“…The design and optimisation of the FLC are carried out using an adaptive fuzzy inference system network that uses the backpropagation, least square and gradient algorithms. …”
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Analysis of the ECG signal using SVD-based parametric modelling technique by Baali, Hamza, Salami, Momoh Jimoh Emiyoka, Akmeliawati, Rini, Aibinu, Abiodun Musa

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Sediment load forecasting from a biomimetic optimization perspective: Firefly and Artificial Bee Colony algorithms empowered neural network modeling in �oruh River by Katipo?lu O.M., Kartal V., Pande C.B.

“…The hybrid model is a novel approach for estimating sediment load based on various input variables. …”

Ocean Colour Remote Sensing Of Case 2 Waters Using An Optimised Neural Network by Anwar, Saumi Syahreza

“…The NN model architecture and training parameters were optimised, with inputs being selected based correlation analysis (CA) and principal component analysis (PCA). …”
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Theory-guided machine learning for predicting and minimising surface settlement caused by the excavation of twin tunnels / Chia Yu Huat by Chia , Yu Huat

“…This is due to the data generated from the numerical model possess the pattern for the ML algorithm ease of prediction. In addition, Coati Optimization algorithm, Particle Swarm Opimisation (PSO) and Bayesian Optimsiation (BO) are integrated to identify optimal parameters and minimize settlement during twin tunnel excavation and GBT with the optimisation algorithm has shown consistent capability identifying the least SS induced by twin tunnels Keyword: …”
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Grey wolf optimization for enhanced performance in wind power system with dual-star induction generators by Benamara K., Amimeur H., Hamoudi Y., Abdolrasol M.G.M., Cali U., Ustun T.S.

“…These algorithms play a crucial role in estimating the optimal values of Kp, Ki, and Kd for the PID speed controller, as well as Kp and Ki for the PI controller used in the flux, DC-link voltage, and grid connection for wind energy conversion system based dual-star induction generator. …”

PATCH-IQ: A Patch Based Learning Framework For Blind Image Quality Assessment by Abdul Manap, Redzuan, Ling, Shao, Frangi, Alejandro Federico

“…Most well-known blind image quality assessment (BIQA) models usually follow a two-stage framework whereby various types of features are first extracted and used as an input to a regressor. The regression algorithm is used to model human perceptual measures based on a training set of distorted images. …”
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Aeronautical revenues optimisation model (AROM) for regional airports via airside operations stochastic baseline matrix analysis / Wan Mazlina Wan Mohamed by Wan Mohamed, Wan Mazlina

“…Preliminary model was developed based on the determinants and the model was analysed using Bayesian Network theory. …”
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Optimization Of Pid Controller Using Grey Wolf Optimzer And Dragonfly Algorithm by Nik Mohamed Hazli, Nik Muhammad Aiman

“…Optimisation is difficult to optimise as there are three parameters that need to be tuned, Kp, Integral parameter, Ki, and derivative parameter, Kd. …”
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Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System by Aljanabi, Mohammad, Mohd Arfian, Ismail, Mezhuyev, Vitaliy

“…Many optimisation-based intrusion detection algorithms have been developed and are widely used for intrusion identification. …”
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Evaluating Adan vs. Adam: an analysis of optimizer performance in deep learning by Ismail, Amelia Ritahani, Azhary, Muhammad Zulhazmi Rafiqi, Hitam, Nor Azizah

“…On the other hand, for image classification tasks, Adan provides more consistent optimisation across extended training periods. Based on these results, this paper aims to provide insights into the strengths and limitations of each optimizer, highlighting the importance of considering task-specific requirements when selecting an optimization algorithm for deep learning models.…”
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Mixed-variable ant colony optimisation algorithm for feature subset selection and tuning support vector machine parameter by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…This paper presents a hybrid classification algorithm, ACOMV-SVM which is based on ant colony and support vector machine.A new direction for ant colony optimisation is to optimise mixed (discrete and continuous) variables.The optimised variables are then feed into selecting feature subset and tuning its parameters are two main problems of SVM.Most approaches related to tuning support vector machine parameters will discretise the continuous value of the parameters which will give a negative effect on the performance. …”
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New techniques incorporating computational intelligence based for voltage stability evaluation and improvement in power system / Nur Fadilah Ab. Aziz by Ab. Aziz, Nur Fadilah

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

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