Search Results - (( time distribution _ algorithm ) OR ( parameters variation tool algorithm ))
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Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani
Published 2018“…To obtain the unknown vector of parameters of the MHTan, three heuristic optimization algorithms are employed to minimize the sum of squared residuals. …”
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An analysis of the parameter modifications in varieties of harmony search algorithm
Published 2014“…Based on the description of the fundamental concept of HS, recent variations of the extended HS were analyzed focusing on its algorithm’s theory as well as its fundamental and primary concepts. …”
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Data Analysis and Machine Learning Algorithms Evaluation for Bioliq AI-based Predictive Tool
Published 2019“…This final year project identified relevant parameters through literature research, analysis and expert interview, and evaluated different machine learning algorithms and identified linear regression as the most applicable and efficient with its R-square of 0.8015, qualifying it to be used for the development of a hybrid model for the AI-based tool for predictive process optimization for chemical plants.…”
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An analysis of the parameter modifications in varieties of harmony search algorithm
Published 2014“…Based on the description of the fundamental concept of HS, recent variations of the extended HS were analyzed focusing on its algorithm’s theory as well as its fundamental and primary concepts. …”
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Design optimization of valve timing at various engine speeds using Multi-Objective Genetic Algorithm (MOGA)
Published 2008“…This paper aims to demonstrate the effectiveness of Multi- Objective Genetic Algorithm Optimization and its robust practical application on the automobile engine valve timing where the variation of performance parameters required for finest tuning to obtain the optimal engine performances. …”
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Proceeding Paper -
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Comparison study of maximum power point tracker techniques for PV systems
Published 2010“…This paper presents in details comparative study between two most popular algorithms technique which is incremental conductance algorithm and perturb and observe algorithm. …”
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Conference or Workshop Item -
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Model-based hybrid variational level set method applied to object detection in grey scale images
Published 2024“…This algorithm leverages an improved multi-scale mean filter to mitigate grayscale inhomogeneity while reducing the impact of scale parameter selection. …”
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Investigating the performance of an amplitude-independent algorithm for detecting the hand muscle activity of stroke survivors
Published 2020“…A comparison between the performance of an amplitude-independent muscle activity detection algorithm and three amplitude-dependent algorithms was conducted by using sEMG signals recorded from six hemiparesis stroke survivors and from six healthy subjects. …”
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing
Published 2024“…Given the multitude of components to manage, streamflow forecasting is preferable to employ an algorithm with low sensitivity to parameter variations. …”
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Fast and optimal tuning of fractional order PID controller for AVR system based on memorizable-smoothed functional algorithm
Published 2022“…Nevertheless, many existing optimization tools for tuning the FOPID controller, which are based on multi-agent based optimization, require large number of function evaluation in their algorithm that could lead to high computational burden. …”
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Sensor-less vector control using adaptive observer scheme for controlling the performance of the induction motor / Mazhar Hussain Abbasi
Published 2013“…Internal parameters are used, for example, feed-forward compensator of current controller and parameters of observer model in sensor less position. …”
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Improving pipelined time stepping algorithm for distributed memory multicomputers
Published 2010“…We present a modified pipelined time stepping algorithm based on delayed pipelining and reduced communication strategies to improve overall execution time on a distributed memory environment using MPI. …”
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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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Field data-based mathematical modeling by Bode equations and vector fitting algorithm for renewable energy applications
Published 2018“…Thus, an accurate mathematical model is important because most system parameters vary with time. Curve modeling of power generation is a significant tool for evaluating system performance, monitoring and forecasting. …”
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Self-Schedule and Self-Distributive MAC Scheduling Algorithms for Next-Generation Sensor Networks
Published 2015“…It has been demonstrated that, with regard to communication overhead, energy consumption and execution time through simulation proposed that algorithms outperform existing distributed randomized scheduling algorithm (DRAND). …”
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Optimal location and size estimation of distributed generators by employing grouping particle swarm optimization and grouping genetic algorithm
Published 2017“…This work is aimed to decrease the total real and reactive power losses while enhancing the voltage profile of the distribution network with less computation time by proposing two new artificial intelligence algorithms, i.e. grouping particle swarm optimization algorithm and grouping genetic algorithm. …”
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Time Synchronization Using Distributed Observer Algorithm With Sliding Mode Control For Wireless Sensor Network
Published 2015“…The algorithm is known as Time Synchronization using Distributed Observer algorithm with Sliding mode control element (TSDOS).The main purpose of proposing TSDOS is to estimate a common global clock time by which all nodes within the WSN can use it for communication purpose. …”
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