Search Results - (( sequence optimization sensor algorithm ) OR ( parameters variation _ algorithm ))
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Global Algorithms for Nonlinear Discrete Optimization and Discrete-Valued Optimal Control Problems
Published 2009“…Once the best filled function method is identified, we propose and test several variations of the method with numerical examples. We then consider the task of determining near globally optimal solutions of discrete-valued optimal control problems. …”
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An energy efficient reinforcement learning based cooperative channel sensing for cognitive radio sensor networks
Published 2017“…Simulation results show convergence and adaptability of the algorithm to dynamic environment in achieving optimal solutions. …”
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A reinforcement learning-based energy-efficient spectrum-aware clustering algorithm for cognitive radio wireless sensor network
Published 2016“…Simulation results show convergence, learning and adaptability of the RL based algorithms to dynamic environment toward achieving the optimal solutions. …”
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Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof
Published 2019“…In the simulation the robot is equipped with thirteen distance sensing sensors. From the simulation result, by using these sensors information the AUTOWiSARD algorithm can successfully differentiate and classify states without supervision, while the Q-learning algorithm is able to produce and optimized states-actions policy. …”
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Supervised deep learning algorithms for process fault detection and diagnosis under different temporal subsequence length of process data
Published 2025“…Current FDD technologies mostly rely on data-driven solutions by making full use of abundant process data collected by the state-of-the-art distributed process instruments and sensors. Deep learning algorithms were widely used among all the data-driven algorithms. …”
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Simulated Kalman Filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem
Published 2022“…There were also attempts to hybridize SKF with other famous algorithms such as Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), and Sine Cosine Algorithm (SCA) to improve its performance. …”
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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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Robustness Analysis Of An Optimized Controller Via Particle Swarm Algorithm
Published 2017“…The finding shows that the SMC that utilized the PSO algorithm parameters are capable to produce smaller robustness index values, which demonstrated better robustness characteristic in confront with the variation of the system parameter.…”
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Voltage Variation Analysis By Using Gabor Transform
Published 2019“…The parameters extracted can detect the voltage variation signals successfully. …”
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Hybrid Control of A Quadrotor System Carrying Suspended Payload With Parameter Variations
Published 2025thesis::master thesis -
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Performance of particle swarm optimization under different range of direct current motor's moment of inertia / Mohd Azri Abdul Aziz
Published 2018“…A prevalent application is a Direct Current (DC) motor control system with variations in parameters value have been used. Moment of inertia is one of the essential parameters of a DC motor which can affect the transient response including rise time, settling time, overshoot and steady state error. …”
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Decentralized Adaptive Pi With Adaptive Interaction Algorithm Of Wastewater Treatment Plant
Published 2014“…The Pi controller parameters are obtained by using simple updating algorithm developed based on adaptive interaction theory. …”
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Improved Differential Evolution-Based MPPT Algorithm Using SEPIC for PV Systems Under Partial Shading Conditions and Load Variation
Published 2018“…The main contribution of the proposed algorithm are the following: capability in tracking GMPP and faster respond against load variation; optimization algorithm can search for the GMPP within a larger operating region as it is implemented by using a single-ended primary-inductor converter; and easy tuning as less parameter has to be set in the algorithm. …”
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An Evolutionary Stream Clustering Technique for Outlier Detection
Published 2020“…Later, this algorithm will be extended to optimize the model in detecting outlier on data streams. …”
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Performance of particle swarm optimization under different range of direct current motor's moment of inertia / Mohd Azri Abdul Aziz
Published 2018“…A prevalent application is a Direct Current (DC) motor control system with variations in parameters value have been used. Moment of inertia is one of the essential parameters of a DC motor which can affect the transient response including rise time, settling time, overshoot and steady state error. …”
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Direct Adaptive Predictive Control For Wastewater Treatment Plant
Published 2012“…This N4SID plays the role of the software sensor for on-line estimation of prediction matrices and control matrices of the bioprocess, joint together with model predictive control (MPC) in order to obtain the optimal control sequence. …”
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