Search Results - (( data application using algorithm ) OR ( parameters variation using algorithm ))
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1
Development Of An Algorithm To Reduce The Topographical Effects In Reflected Radiance
Published 2020“…These algorithms use data from extraterrestrial irradiance, atmospheric profiles, digital elevation models, and radiative transfer models to calculate the amount of irradiance on Earth’s surface to reduce distortions due to the topographic effect. …”
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CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING
Published 2017“…To overcome these ANN problems, the Genetic Algorithm (GA) has been most frequently used for this purpose, however, some drawbacks of GA include, slow search speed and dependence on initial parameters. …”
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3
Identification of continuous-time model of hammerstein system using modified multi-verse optimizer
Published 2021“…Multi-Verse Optimizer (MVO) is one of the most recent robust nature-inspired metaheuristic algorithm. It has been successfully implemented and used in various areas such as machine learning applications, engineering applications, network applications, parameter control, and other similar applications to solve optimization problems. …”
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Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar
Published 2019“…This study presents robust pitch angle control for the output wind power model in wide range wind speed by proportional-integral-derivative (PID) controller. In addition, ACO algorithm has been used for optimization of PID controller parameters to obtain within rated smooth output power of WT from fluctuating wind speed. …”
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5
Field data-based mathematical modeling by Bode equations and vector fitting algorithm for renewable energy applications
Published 2018“…From the minimal RMSE, the results show clear improvements in data fitting over other methods. The most powerful features of this method is the ability to model irregular or randomly shaped data and to be applied to any algorithms that estimating models using frequency-domain data to provide state-space or transfer function for the model.…”
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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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Final Year Project -
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Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources
Published 2021“…In this research, a novel algorithm (Herschel Bulkley Network) is introduced to simulate the non-Newtonian fluid flow in a pipe using data redundant deep neural network (DNN) for fully developed, laminar, and incompressible flow conditions. …”
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Renewable sources-based automatic load frequency control of interconnected systems using chaotic atom search optimization
Published 2022“…Moreover, the sensitivity analysis is carried out by considering ±25 % variation in HPS parameters and the real-time applicability is tested with Malaysian meteorological data of solar radiation and wind speed variation. …”
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Fuzzy control algorithm for educational light tracking system
Published 2010“…The fuzzy controller input parameters (light source pixel coordinate) and output parameters (variation of duty cycle) are used to generate the optimal pulse-width modulated (PWM) under different operating conditions to drive the motors. …”
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Proceeding Paper -
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Stochastic And Modified Sequent Peak Algorithm For Reservoir Planning Analysis Considering Performance Indices
Published 2016“…The results show that the reliability and vulnerability metrics are significant in critical period and storage capacity modeling. Subsequently, using the simulation results, new regression equations are developed to model the critical period and total storage capacity of study systems individually and three systems together applying standard demand parameter, reliability and vulnerability performance measures and coefficient of variation and skewness of annual flows. …”
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12
Interpolation and extrapolation techniques based Neural Network in estimating the missing ionospheric TEC data
Published 2024“…The solar and magnetic indices, seasonal variation as well as diurnal variation are used as the input spaces in the NN to estimate the missing GPS TEC. …”
Conference Paper -
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Metaheuristic approach for optimizing neural networks parameters in battery state of charge estimation
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Adaptive linux-based TCP congestion control algorithm for high-speed networks
Published 2017“…Thereafter, the gained increase is balanced using the weighting function according to the variation of RTT in order to maintain the fairness. …”
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15
Modified least trimmed squares method for face recognition / Nur Azimah Abdul Rahim
Published 2018“…The genetic algorithm configuration for n (number of observations) and p (parameter) was changed to assess the performance of modified method. …”
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16
Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
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Scene illumination classification based on histogram quartering of CIE-Y component
Published 2014“…The result of categorization will be validated using inherent illumination data of scene. Applying the improving algorithm for characterizing histograms (histogram quartering) handed out the advantages of high accuracy. …”
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Interpolation and Extrapolation Techniques Based Neural Network in Estimating the Missing Ionospheric TEC Data
Published 2024Proceedings Paper -
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Improved power output forecastingtechnique for effective battery management in photovoltaic system / Utpal Kumar Das
Published 2019“…In this process, an SVR-based model is developed based on the historical PV output power and most influential meteorological data of real PV station. A PSO-based algorithm is adopted for the appropriate selection of dominated parameters of SVR-based model to achieve better performance. …”
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