Search Results - (( using simulation model algorithm ) OR ( sequence optimization sensor algorithm ))
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1
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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2
Vector evaluated particle swarm optimization approach to solve assembly sequence planning problem
Published 2022“…Meta-heuristic method is able to escape the local optima. Simulated Annealing (SA) is used where search is done in sequence basis and to solve optimization problems. …”
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3
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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4
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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5
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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6
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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7
Assessing the simulation performances of multiple model selection algorithm
Published 2015“…The Autometrics is an algorithm for single equation model selection.It is a hybrid method which combines expanding and contracting search techniques.In this study, the algorithm is extended for multiple equations modelling known as SURE-Autometrics.The aim of this paper is to assess the performance of the extended algorithm using various simulation experiment conditions. …”
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8
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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9
Implementation of New Improved Round Robin (NIRR) CPU scheduling algorithm using discrete event simulation
Published 2015“…The main objective of this research is to validate the NIRR algorithm by developing a comprehensive simulation model using Discrete Event Simulation (DES). …”
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10
Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems
Published 2014“…This demonstrates the feasibility of using the FDM and parallel computing to reduce the computational time in the EHD model enabling to simulate the micropumps with very small dimensions of electrodes. …”
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11
Implementation of New Improved Round Robin (NIRR) CPU scheduling algorithm using discrete event simulation
Published 2016“…The main objective of this research is to validate the NIRR algorithm by developing a comprehensive simulation model using Discrete Event Simulation (DES). …”
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12
A Model for Evaluation of Cryptography Algorithm on UUM Portal
Published 2004“…The simulation model was developed using Active Server Page, JavaScript and SQL 7.0 as database. …”
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13
Ensemble Dual Recursive Learning Algorithms for Identifying Custom Tanks Flow with Leakage
Published 2010“…Relative mass release of the leakage is introduced as the input for the simulation model and the data from the simulation model is taken at real time (on-line) to feed into the recursive algorithms. …”
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14
Modelling and simulation of hysteresis control algorithm for use in single phase ac-to-ac matrix converter / Seri Iryani Mohd Noor
Published 2003“…This thesis is illustrated by developing computer simulation models of ac-to-ac single phase matrix converter (SPMC) using sinusoidal pulse width modulation (SPWM) technique and another algorithm i.e hysteresis control technique. …”
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15
Incorporating the range-based method into GridSim for modeling task and resource heterogeneity
Published 2017“…In this paper, we propose a new simulation model that incorporates the range-based method into GridSim for modeling and simulating heterogeneous tasks and resources in order to capture the inherent heterogeneity of Grid environments that later can be used by other researchers to test their algorithms.…”
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16
Power Delivery Network Modeling And Simulation By Using Delaunay-Voronoi Triangulation And The Latency Insertion Method
Published 2018“…The research is focused into the analysis of PDN by modeling and simulation of the power plane. In the project, power plane is modeled using Delaunay-Voronoi algorithm and for simulation, a fast transient simulation algorithm which is latency insertion method (LIM) is applied. …”
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17
Performance of Semi Active Lateral Control (SALC) algorithm for semi active suspension system in multibody co-simulation method / M. M. Abdul Majid ...[et al.]
Published 2018“…The experimental data used for simulation model correlation and validation. …”
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18
A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models
Published 2017“…Genetic algorithm and simulated annealing techniques are used to optimize the control parameters of the neural network. …”
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19
Octane number prediction for gasoline blends using convolution neural network / Zhu Yue
Published 2021“…Machine performance learning models depend to a large extant to the data quality used train the model. …”
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20
Utilization of canny and velocity bunching algorithms for modelling shoreline change
Published 2006“…There is significant relationship between shoreline change rate estimated using Canny algorithm and ones modeled using velocity bunching model. …”
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