Search Results - (( java application using algorithm ) OR ( (variable OR variables) integration a algorithm ))
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A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models
Published 2017“…Keywords - artificial neural network; mean absolute percentage error; genetic algorithm; simulated annealing; correlation analysisAbstract — Electrical energy demand forecasting plays a pivotal role as a decision support tool in the modern power industry. …”
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Variable order step size method for solving orbital problems with periodic solutions
Published 2022“…Existing variable order step size numerical techniques for solving a system of higher-order ordinary differential equations (ODEs) requires direct calculating the integration coefficients at each step change. …”
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Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization
Published 2014“…This research aims to improve the PSO-PID tuning algorithms by integrating the tuning process with the Variable Weight Grey-Taguchi Design of Experiment (DOE) method. …”
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4
Optimization of PID Parameters Utilizing Variable Weight Grey-Taguchi Method and Particle Swarm Optimization
Published 2017“…This research aims to improve the PSO-PID tuning algorithms by integrating the tuning process with the Variable Weight Grey-Taguchi Design of Experiment (DOE) method. …”
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Variable order step size method for solving orbital problems with periodic solutions
Published 2024journal::journal article -
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ENGINEERING DESIGN WITH PSO ALGORITHM
Published 2019“…Creating a PSO algorithm-based infrastructure integrating with the recommendation system will further enhance solution to the design problem. …”
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Variable order step size algorithm for solving second order ODEs
Published 2019“…The proposed method will also be equipped with a variable order step size algorithm to reduce computational cost (calculation time). …”
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Book Section -
8
Variable Speed Control Of Two-Mass Wind Turbine System Via State Feedback With Adaptation Law
Published 2018“…Wind turbine convert kinetic energy from the wind to rotational energy and then to electrical energy.In a wind energy conversion system (WECS),its electrical power control (EPC) side demanded a maximum mechanical power from the mechanical power control (MPC) side despite any intermittent wind and seasonal interference.Therefore,it is necessary to develop a variable speed algorithm for a modern WECS.For a two-mass horizontal axis wind turbine, the rotor and generator stiffness is commonly being neglected in the system dynamic.The inclusion of stiffness in system dynamic introduces integral term in the system expression and hence,incur mathematical complexity in the controller design phase.Contrary,this study consider stiffness as unknown parameter in the wind turbine dynamic.In order to obtain the maximum output power,the design of an algorithm with adaptation law for the speed control of a two-mass wind turbine system with an unknown stiffness is proposed in this research.The algorithm is formulated using a full-state feedback.In pursuance of solving the tracking control as a regulation case,the speed of the turbine is bijective mapped into the error dynamic.The stability of the proposed algorithm is guaranteed by Lyapunov.The adaptation law used in the variable speed algorithm is to successfully acquire the adaptability of the algorithm towards an unknown stiffness.Therein,the estimated stiffness is augmented in the Lyapunov function.The Lie derivative of the function is made into a negative semi-definite via the non-negative control parameters.In order to control the rotor speed to sustain the optimum tip-speed ratio (TSR),as well as obtaining the maximum power output from the turbine,the proposed algorithm is constructed.A MATLAB with Simulink® toolbox is used to validate the effectiveness of the proposed control speed.The simulation result showed that the rotor speed achieved an asymptotic tracking towards the demanded rotor speed irrespective of the stiffness value.The error is proved to be minimized as the integral of absolute error (IAE) obtained for wind turbine with stiffness ranging from 134550 Nmrad-1,269100 Nmrad-1,and 403650 Nmrad-1 are recorded as 0.003088,0.003063 and 0.003088 respectively. …”
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Numerical algorithm of block method for general second order ODEs using variable step size
Published 2017“…Consequently, a direct block multistep method with utilization of variable step size strategy is proposed. …”
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Numerical algorithm of block method for general second order ODEs using variable step size
Published 2017“…Consequently, a direct block multistep method with utilization of variable step size strategy is proposed. …”
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Cloudlet deployment and task offloading in mobile edge computing using variable-length whale and differential evolution optimization and analytical hierarchical process for decisio...
Published 2023“…VL-WIDE has accomplished a higher median value for the domination over state-of-the-art algorithms with a higher number of non- dominated solutions value than all other benchmarks. …”
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RSA Encryption & Decryption using JAVA
Published 2006“…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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Mixed variable ant colony optimization technique for feature subset selection and model selection
Published 2013“…This paper presents the integration of Mixed Variable Ant Colony Optimization and Support Vector Machine (SVM) to enhance the performance of SVM through simultaneously tuning its parameters and selecting a small number of features.The process of selecting a suitable feature subset and optimizing SVM parameters must occur simultaneously,because these processes affect each ot her which in turn will affect the SVM performance.Thus producing unacceptable classification accuracy.Five datasets from UCI were used to evaluate the proposed algorithm.Results showed that the proposed algorithm can enhance the classification accuracy with the small size of features subset.…”
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SURE-Autometrics algorithm for model selection in multiple equations
Published 2016“…The algorithm is developed by integrating the SURE model with the Autometrics search strategy; hence, it is named as SURE-Autometrics. …”
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A hybridisation of adaptive variable neighbourhood search and large neighbourhood search: Application to the vehicle routing problem
Published 2016“…In this paper, an adaptive variable neighbourhood search (AVNS) algorithm that incorporates large neighbourhood search (LNS) as a diversification strategy is proposed and applied to the capacitated vehicle routing problem. …”
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Provider independent cryptographic tools
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Monograph -
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Feature selection and model selection algorithm using incremental mixed variable ant colony optimization for support vector machine classifier
Published 2013“…In order to enhance SVM performance, these problems must be solved simultaneously because error produced from the feature subset selection phase will affect the values of the SVM parameters and resulted in low classification accuracy.Most approaches related with solving SVM model selection problem will discretize the continuous value of SVM parameters which will influence its performance.Incremental Mixed Variable Ant Colony Optimization (IACOMV) has the ability to solve SVM model selection problem without discretising the continuous values and simultaneously solve the two problems.This paper presents an algorithm that integrates IACOMV and SVM.Ten datasets from UCI were used to evaluate the performance of the proposed algorithm.Results showed that the proposed algorithm can enhance the classification accuracy with small number of features.…”
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Parallel method using MPI for solving large systems of delay differential equations
Published 2012“…The algorithm is based on a variable stepsize variable order block method. …”
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Conference or Workshop Item -
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