Search Results - (( java implementation path algorithm ) OR ( parameters variation step algorithm ))
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Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer
Published 2017“…The development tools used in developing this project is NetBeans by using Java for the implementation of the coding. The methodology that used for developing this system is the Dijkstra’s algorithm. …”
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment
Published 2021“…In this study, a fast iterative method known as Rotated Successive Over-Relaxation (RSOR) is introduced. The algorithm is implemented in a self-developed 2D Java tool, UAV Planner. …”
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Smart appointment organizer for mobile application / Mohd Syafiq Adam
Published 2009“…The main component of this prototype is the use of Dijkstra algorithm to compute the shortest path from source of appointment to the 6 points of destinations within UiTM Shah Alam. …”
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5
Backstepping Integral Super Twisting Sliding Mode Control Algorithm For Autonomous Underwater Glider
Published 2019“…The BISTSMC was benchmarked with integral SMC (ISMC), super twisting SMC (STSMC), integral STSMC (ISTSMC), back-stepping ISMC and back-stepping STSMC. The simulation results have shown that the proposed controller provides the smallest chattering about more than 100 times smaller than ISTSMC, more than 10000 times smaller than backstepping ISMC and backstepping STSMC in nominal, disturbance and parameter variation cases respectively. …”
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6
Development of controller for an underactuated autonomous underwater vehicle (AUV)
Published 2019“…The BSTSMC was benchmarked with super twisting SMC (STSMC) and back-stepping SMC. The simulation results have shown that the proposed controller provides the smallest chattering about more than 1000 times smaller than STSMC, more than 100 times smaller than back-stepping SMC in nominal, disturbance and parameter variation cases respectively. …”
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7
Design of low order quantitative feedback theory and H-infinity-based controllers using particle swarm optimisation for a pneumatic actuator system
Published 2010“…These algorithms are designed to achieve the robustness over a wide range of system parameters change and disturbances. …”
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A comparative evaluation of PID-based optimisation controller algorithms for DC motor
Published 2023Article -
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Multiobjective optimization using weighted sum Artificial Bee Colony algorithm for Load Frequency Control
Published 2014“…Furthermore, the proposed algorithm is robust enough to operate under different operating conditions and system parameter variations.…”
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Efficiency improvement of a standalone photovoltaic system using fuzzy-based maximum power point tracking algorithm
Published 2016“…This thesis proposes a FLC controller that calculates the E and the previous duty ratio variations (ΔDn-1) as input parameters to adaptively modify the output duty ratio (Δd). …”
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12
Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images
Published 2024“…Statistical techniques such as Anisotropic Diffusion Filter (ADF), local contrast enhancement, and haze reduction in the CIELAB colour space, are incorporated in the proposed algorithms for the pre-processing step. Hair removal is implemented through black-hat morphological processing and total variation based inpainting. …”
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A modified sine cosine algorithm for improving wind plant energy production
Published 2019“…This paper presents a Modified Sine Cosine Algorithm (M-SCA) to improve the controller parameter of an array of turbines such that the total energy production of wind plant is increased. …”
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Cellular Harmony Search for Optimization Problems
Published 2013“…Structured population in evolutionary algorithms (EAs) is an important research track where an individual only interacts with its neighboring individuals in the breeding step. …”
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Sensorless Adaptive Fuzzy Logic Control Of Permanent Magnet Synchronous Motor
Published 2008“…However, these controllers are very sensitive to step change of command speed, parameter variations and load disturbance. …”
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Fast and optimal tuning of fractional order PID controller for AVR system based on memorizable-smoothed functional algorithm
Published 2022“…The simulations of step response analysis, Bode plot analysis, trajectory tracking analysis, disturbance rejection analysis, and parameter variation analysis are conducted to evaluate the effectiveness of the proposed MSFA-FOPID controller of AVR system. …”
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Scheduling dynamic cellular manufacturing systems in the presence of cost uncertainty using heuristic method
Published 2016“…Then, design of experiments is used to examine the sensitivity of the parameters of each solving algorithm using Taguchi method. …”
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Design of QFT-based self-tuning deadbeat controller
Published 2013“…This paper presents a design method of self-tuning Quantitative Feedback Theory (QFT) by using improved deadbeat control algorithm. QFT is a technique to achieve robust control with pre-defined specifications whereas deadbeat is an algorithm that could bring the output to steady state with minimum step size. …”
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Design of QFT-based self-tuning deadbeat controller
Published 2013“…This paper presents a design method of self-tuning Quantitative Feedback Theory (QFT) by using improved deadbeat control algorithm. QFT is a technique to achieve robust control with pre-defined specifications whereas deadbeat is an algorithm that could bring the output to steady state with minimum step size. …”
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Enhanced stability and performance of the tidal energy conversion system using adaptive optimum relation-based MPPT algorithms
Published 2025“…The A-ORB algorithm integrates the optimum relation-based (ORB) approach with Hill Climb Search (HCS), along with an adaptive gain adjustment mechanism that dynamically tunes the parameter K based on power variation (ΔP). …”
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