Search Results - (( java implication based algorithm ) OR ( parametric optimization swarm algorithm ))

Parametric modelling of a TRMS using dynamic spread factor particle swarm optimisation by Toha, Siti Fauziah, Abd Latiff, I., Mohamad, M., Tokhi, M Osman

“…In this paper, a sound approach for a Twin Rotor Multi-input Multi-Output System (TRMS) parametric modeling is proposed based on dynamic spread factor particle swarm optimization. …”
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A MODIFIED PARTICLE SWARM OPTIMIZATION ALGORITHM FOR WELLBORE TRAJECTORY DESIGN by BISWAS, KALLOL

“…To address this issue, a new hybridization of cellular automata (CA) technique with grey wolf optimization (GWO) and particle swarm optimization (PSO) algorithms is proposed in this work which solves these three optimization objectives of drilling through 17 tuning variables. …”
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Particle swarm modelling of a flexible beam structure by Mohamad, M., Tokhi, M. O., Toha, Siti Fauziah, Latiff, I. Abd.

“…This paper presents a particle swarm optimization (PSO) algorithm with dynamic spread factor inertia weight and its application to dynamic modeling of a flexible beam structure. …”
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Parametric modelling application to a twin rotor system using recursive least squares, genetic, and swarm optimization techniques by Toha, Siti Fauziah, Tokhi, M. O.

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Experimental dataset to develop a parametric model based of DC geared motor in feeder machine by Azlan, W. M, Salleh, S. M, Mahzan, S, Sadikin, A, Ahmad, S

“…This paper presents the application of a System Identification based on Particle Swarm Optimization (PSO) technique to develop parametric model of experimental dataset of DC geared motor in feeder machine. …”
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ANFIS modelling of a twin rotor system using particle swarm optimisation and RLS by Toha, Siti Fauziah, Tokhi, M. O.

“…An adaptive neuro-fuzzy inference system (ANFIS) tuned by particle swarm optimization (PSO) algorithm is developed in search for non-parametric model for the TRMS. …”
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Intelligently tuned weights based robust H∞ controller design for pneumatic servo actuator system with parametric uncertainty by Ali, Hazem Ibrahim, Mohd Noor, Samsul Bahari, Bashi, Sinan Mahmod, Marhaban, Mohammad Hamiruce

“…This paper presents a new method for tuning the weighing functions to design an H∞ controller. Based on a particle swarm optimization (PSO) algorithm the, weighting functions are tuned. …”
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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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Implementation of Evolutionary Algorithms to Parametric Identification of Gradient Flexible Plate Structure by Annisa, Jamali, Muhammad Hasbollah, Hassan, Lidyana, Roslan, Muhamad Sukri, Hadi

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Implementation of Evolutionary Algorithms to Parametric Identification of Gradient Flexible Plate Structure by Annisa, Jamali, Lidyana, Roslan, Muhammad Hasbollah, Hassan

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Parameter identification of thermoelectric modules using enhanced slime mould algorithm (ESMA) by Ponnalagu, Dharswini, Mohd Ashraf, Ahmad, Jui, Julakha Jahan

“…Acquired results which demonstrate lower values of RMSE and parameter deviation index against the standard SMA and other preceding algorithms such as particle swarm optimization, sine cosine algorithm, moth flame optimizer and ant lion optimizer ultimately verified ESMA’s efficacy as an effective approach for accurate model identification.…”
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Application of hybrid intelligent systems in predicting the unconfined compressive strength of clay material mixed with recycled additive by Al-Bared, M.A.M., Mustaffa, Z., Armaghani, D.J., Marto, A., Yunus, N.Z.M., Hasanipanah, M.

“…Then, these basic properties were selected as input variables to predict the UCS values through the use of two hybrid intelligent systems i.e., the neuro-swarm and the neuro-imperialism. Actually, in these systems, respectively, the weights and biases of the artificial neural network (ANN) were optimized using the particle swarm optimization (PSO) and imperialism competitive algorithm (ICA) to get a higher accuracy compared to a pre-developed ANN model. …”
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Application of hybrid intelligent systems in predicting the unconfined compressive strength of clay material mixed with recycled additive by Al-Bared, M.A.M., Mustaffa, Z., Armaghani, D.J., Marto, A., Yunus, N.Z.M., Hasanipanah, M.

“…Then, these basic properties were selected as input variables to predict the UCS values through the use of two hybrid intelligent systems i.e., the neuro-swarm and the neuro-imperialism. Actually, in these systems, respectively, the weights and biases of the artificial neural network (ANN) were optimized using the particle swarm optimization (PSO) and imperialism competitive algorithm (ICA) to get a higher accuracy compared to a pre-developed ANN model. …”
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Design of combined robust controller for a pneumatic servo actuator system with uncertainty by Mohd Noor, Samsul Bahari, Ali, Hazem Ibrahim, Marhaban, Mohammad Hamiruce

“…First, an H-inf controller is designed to assure robust stability for the system. Particle swarm optimization (PSO) algorithm is used to tune the weighting functions. …”
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Optimized controllers for stabilizing the frequency changes in hybrid wind-photovoltaic-wave energy-based maritime microgrid systems by Peddakapu, K., Mohd Rusllim, Mohamed, Srinivasarao, P., Licari, J.

“…The AOA-based 2DOF-TIDN performance is compared to the following algorithms: genetic, Jaya, bat, grasshopper optimization, particle swarm optimization, and moth flame optimization. …”
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Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms by Alswaitti, Mohammed Y. T.

“…Hence, this research has proposed three enhanced frameworks, namely, Optimized Gravitational-based (OGC), Density-Based Particle Swarm Optimization (DPSO), and Variance-based Differential Evolution with an Optional Crossover (VDEO) frameworks for data clustering. …”
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The advancement of artificial intelligence's application in hybrid solar and wind power plant optimization: a study of the literature by Mauludin, Mochamad Subchan, Khairudin, Moh., Asnawi, Rustam, Mustafa, Wan Azani, Toha, Siti Fauziah

“…Our findings underscore prevalent methodologies such as computational modellingutilizing software suites like MATLAB/Simulink, HOMER, and others to derive empirical data. Additionally, parametric analyses emerge as the predominant approach, characterized by the application of algorithms such as Particle Swarm Optimization (PSO), Fuzzy Logic Control (FLC), and Genetic Algorithms (GA), among others. …”
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Estimating Crack Effects on Electrical Characteristics of PV Modules Based on Monitoring Data and I-V Curves by Feng L., Zhang J., Kiong T.S., Ding K., Amin N., Hamelmann F.U.

“…Meanwhile, an innovative parameter optimization algorithm based on particle swarm optimization is developed to extract the parameters. …”

Analysis of bubble departure and lift-off boiling model using computational intelligence techniques and hybrid algorithms by Quadros, Jaimon Dennis, Mogul, Yakub Iqbal, Ağbulut, Ümit, Gürel, Ali Etem, Khan, Sher Afghan, Akhtar, Mohammad Nishat, Jilte, Ravindra D., Asif, Mohammad

“…The soft computing techniques used for prediction were - the artificial neural network (ANN), and the Fuzzy Mamdani model, and the hybrid algorithms were adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network trained particle swarm optimization (ANN PSO). …”
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Improved pole-placement control with feedforward dead zone compensation for position tracking of electro-pneumatic actuator system by Sunar, Noorhazirah, Rahmat, Mohd Fua’ad, Mohd Fauzi, Ahmad ‘Athif, Ismail, Zool Hilmi, Osman, Siti Marhanis, Sulaiman, Siti Fatimah

“…In order to cater this issue, the EPA system transfer function and the dead-zone model is identified by MATLAB SI toolbox and the Particle Swarm Optimization (PSO) algorithm respectively. …”
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