Search Results - (( variable affecting swarm algorithm ) OR ( java interactive learning algorithm ))
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Teaching and learning via chatbots with immersive and machine learning capabilities
Published 2019“…These chatbots support learning of Java via problem-solving steps through “learning by doing”. …”
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Solving large-scale problems using multi-swarm particle swarm approach
Published 2018“…The proposed approach strived to scale up the application of the (PSO) algorithm towards solving large-scale optimization tasks of up to 1000 real-valued variables. …”
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Optimal planning of energy storage system for hybrid power system considering multi correlated input stochastic variables
Published 2025“…This optimization problem is solved by the hybrid non-dominated sorting genetic algorithm (NSGAII) and the multi-objective particle swarm optimization (MOPSO). …”
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The use of heuristic ordering and particle swarm optimization for nurse scheduling problem
Published 2017“…The comparison of the result of HOPSO, harmony search algorithm (HSA) and heuristic variable neighborhood search (HVNS) is presented. …”
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Adapting perturbation voltage for variable speed micro-hydro using particle swarm optimization (PSO)
Published 2022“…Results show that the value of perturbation speed affects the performance of MPPT algorithm to search the maximum operating point. …”
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Proceedings -
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TUNING PROCESS OF SINGLE INPUT FUZZY LOGIC CONTROLLER BASED ON LINEAR CONTROL SURFACE APPROXIMATION METHOD FOR DEPTH CONTROL OF UNDERWATER REMOTELY OPERATED VEHICLE
Published 2013“…This method will focus on slope of a linear equation to give optimum performances of depth control without overshoot in system response and faster rise time and settling time. The variable parameter for signed distance method in SIFLC tuning by Particle Swarm Optimization (PSO) algorithm. …”
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Optimal parameter estimation of permanent magnet synchronous motor by using Mothflame optimization algorithm / Abdolmajid Dejamkhooy and Sajjad Asefi
Published 2018“…In the next step, the parameter identification as an optimization problem is solved by Moth-flame optimization, which is a novel nature-inspired heuristic algorithm. Simulation results and their comparison with Particle Swarm Optimization based method show high performance and good ability of the proposed method in PMSM parameter estimation.…”
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Developing flood mapping procedure through optimized machine learning techniques. Case study: Prahova river basin, Romania
Published 2025“…To achieve this goal, we employed ten flood-related variables as independent variables in our machine learning models. …”
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Modelling knowledge transfer of nursing students during clinical placement / Nor Azairiah Fatimah Othman
Published 2017“…The influence of the variables selected for this study was tested on two distinct samples of Lower Semester Group, LSG (semester 1- 3) and Higher Semester Group, HSG (semester 4-6) separately… The assessment and improvement of angle stability condition of the power system using particle swarm optimization (PSO) technique / Nor Azwan Mohamed Kamari This thesis presents the assessment and improvement of stability domains for the angle stability condition of the power system using particle swarm optimization (PSO) technique. …”
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Production quantity estimation using an improved artificial neural network
Published 2015“…In order to increase the performance of NNBP, optimization techniques such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are being hybrid with the ANN model to become Hybrid Neural Network Genetic Algorithm (HNNGA) model and Hybrid Neural Network Particle Swarm Optimization (HNNPSO) model respectively. …”
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Tuning Factor the Single Input Fuzzy Logic Controller to Improve the Performances of Depth Control for Underwater Remotely Operated Vehicle
Published 2013“…This study and investigates will focus on the number of rules in SIFLC, lookup table, slope of a linear equation, and also model reference to give optimum performances of depth control without overshoot in system response and faster rise time and settling time. The variable parameter for SIFLC is tuned by Particle Swarm Optimization (PSO) algorithm. …”
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Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform
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Acoustic emission partial discharge localization in oil based on artificial bee colony
Published 2025“…Comparisons with the genetic algorithm (GA), particle swarm optimization (PSO) and bat algorithm (BA) revealed that the distance error, maximum deviation and computation time for AE PD localization based on ABC are the lowest. …”
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Optimized multi-level elongated quinary patterns for the assessment of thyroid nodules in ultrasound images
Published 2018“…However, visual assessment of nodules is difficult and often affected by inter- and intra-observer variabilities. …”
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Online auto-tuned proportional-integral controller using particle swarm optimization for dual active bridge DC-DC converter
Published 2021“…The PI optimization is concerned because the traditional manual tuning of the PI controller only delivers satisfactory performance as long as the affecting variables do not deviate far from the original tuning condition. …”
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Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed
Published 2012“…Modeling of hydrological process has been increasingly complicated since we need to take into consideration an increasing number of descriptive variables. In recent years soft computing methods like fuzzy logic and genetic algorithm are being used in modeling complex processes of hydrologic events. …”
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Evaluation of lightning return stroke current using measured electromagnetic fields
Published 2012“…This research proposed an inverse procedure algorithm using the proposed general fields’ expressions and the particle swarm optimization algorithm (PSO) in the time domain where the full channel base current wave shape in time domain can be determined. …”
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Dynamic stability studies of generators in power system using fuzzy logic controller based power system stabilizer
Published 2018“…Excitation systems are affected by low frequency oscillation (LFO)when they are subjected to small perturbations.Damping during the LFOis enhanced via the addition of power system stabilizer (PSS) to the excitation system.This research entails a study on fuzzy logic controller power system stabilizer (FLCPSS) for the purpose of enhancing the stability of a single machine power system.In order to accomplish the stability enhancement,two approaches were used to design fuzzy logic controller (FLC).The first approach includes the use ofgenetic algorithm (GA) to design the PSS.The second approach entails the use of particle swarm optimization (PSO) to design the PSS.The performance of these two approaches is compared with the systemand without PSS.The stabilizing signals were computed using the fuzzy membership functions depending on these variables.The simulations were tested under different operating conditions and also tested with different membership functions.The simulation is implemented using Matlab /Simulink and the results have been found to be quite good and satisfactory.Electro-mechanical oscillations were created in the event of trouble or when there was high power transfer through weak tie-line in the machines of an interrelated power network.This research presents an analysis on the change of speed (Δω), change of angle position (Δδ) and tie-line power flow (Δp).FLC which includes two areas of symmetrical systems are connected via tie-line to identify the performance of the controllers.Simulation results of the fuzzy logic based controller indicate dual inputs of rotor speed deviation and generator’s accelerating power.Two generators have been used to control the arrangement in the tie-line system.The single fuzzy logic controller (S-FLC) has been used as a primary controller and the double fuzzy logic controller(D-FLC) has been used as a secondary controller.Additionally,the system shows a comparison between the two controllers,namely the S-FLC and D-FLC which have been used to achieve the best results.Notably, the double fuzzy controller has been found to have a greater effect on the multi-machine system and it is smoother than the single fuzzy controller as it increased the damping of the speed Δω and rotorangle (degree) Δδ. …”
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