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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Therefore, in this paper, we proposed Dynamic tasks scheduling algorithm based on attribute reduction with an enhanced hybrid Genetic Algorithm and Particle Swarm Optimization for optimal device selection. …”
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Model structure selection for a discrete-time non-linear system using a genetic algorithm
Published 2004“…In this paper, a methodology for model structure selection based on a genetic algorithm was developed and applied to non-linear discrete-time dynamic systems. …”
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Model structure selection for a discrete-time non-linear system using a genetic algorithm
Published 2004“…In this paper, a methodology for model structure selection based on a genetic algorithm was developed and applied to non-linear discrete-time dynamic systems. …”
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Model structure selection for a discrete-time non-linear system using genetic algorithm
Published 2004“…In this paper, a methodology for model structure selection based on a genetic algorithm was developed and applied to non-linear discrete-time dynamic systems. …”
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An Integer Linear Programming model and Adaptive Genetic Algorithm approach to minimize energy consumption of Cloud computing data centers
Published 2018“…This paper focuses on the development of a dynamic task scheduling algorithm by proposing an Integer Linear Programming (ILP) model that minimizes the energy consumption in a Cloud data center. …”
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Augmentation of basic-line-search and quick-simplex-method algorithms to enhance linear programming computational performance
Published 2021“…Linear programming (LP) is a mathematical modelling that formulate a problem into three components which are decision variables, objective function and constraints. …”
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Model structure selection for a discrete-time non-linear system using a genetic algorithm
Published 2004“…In this paper, a methodology for model structure selection based on a genetic algorithm was developed and applied to non-linear discrete-time dynamic systems. …”
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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Recent research in cooperative path planning algorithms for multi-agent using mixed- integer linear programming
Published 2016“…This paper will review and compare the performances of those existing methods that can find solution without graph search algorithm such as Mixed-Integer Linear Programming (MILP) techniques which exactly solves the problem and then propose four alternative MILP formulations which are computationally less intensive and suited for real-time purposes, but yield a theoretically guaranteed suboptimal solution.…”
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Charge-coupled device based on optical tomography system for monitoring two-phase flow
Published 2024Article -
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A mixed integer linear programming model for real-time task scheduling in multiprocessor computer system
Published 2012“…The advent of multi-processor systems offers a more efficient way of processing multimedia data in real-time.With the development of appropriate scheduling algorithm, another challenge is the mode of assigning tasks in multi-processor systems.This calls for the use of an appropriate mathematical model that will take cognizance of the nature of variables involved.In this research work, a Mixed Integer Linear Programming Model (MILP) was developed to assign tasks in a multiprocessor system.The MILP model was used to assign tasks to multi-processor systems ranging between 5 and 10 homogeneous processors.The result of the simulation runs shows that with the appropriate scheduling algorithm, a high success rate ratio and guaranteed number of deadlines met could be achieved.…”
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Programming Approach in Teaching Operations Research Techniques for Computer Science Students
Published 2005“…OR techniques include among others, linear programming, non-linear programming, integer programming, data analysis including statistics, simulation, and goal programming. …”
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Solving transcendental equation using genetic algorithm / Masitah Hambari
Published 2004“…This project studies the potential of using Genetic Algorithm and develops a program in order to solve Transcendental Equation in optimizing problem domain. …”
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AI recommendation penetration testing tool for SQL injection: linear regression
Published 2025“…In conclusion, the objective of this project is success because the linear regression algorithm was able to be insert in the penetration testing framework.…”
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Performance evaluation of direction of arrival (DOA) for linear array antenna design using multiple signal classification (MUSIC) algorithm in variation of displacement vectors and...
Published 2007“…The algorithm have been implemented in MATLAB software and a program was developed to investigate the power spectrum of a fixed samples, 100 with the number of elements 15 with the existence of noise. …”
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Comparison between fuzzy bootstrap weighted multiple linear regression and multiple linear regression: a case study for oral cancer modelling
Published 2018“…(MLR) is the most common type of linear regression analysis. Current technology advancement and increasing of development of the new or modified methodology building leads to the development of an alternative method for multiple linear regression model calculation. …”
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Development of nonlinear model for continuous stirred tank reactor (CSTR)
Published 2010“…Continuous stirred tank reactors (CSTR) finds wide application in the chemical industry from pilot plant to full-scale production operation.CSTRs generally present operational problems due to complex open-loop nonlinear behavior in the form of input/output multiplicities and ignition/extinction phenomena.A major limitation of linear model is that plant behavior is described by linear dynamic model.As a result,linear model is inadequate for highly nonlinear process and moderately nonlinear process which have large operating regimes.This shortcoming coupled with increasingly stringent demands on throughput and product quality has spurred the development of nonlinear model.The objective of this research are development mathematical model for CSTR process based on first principal,validation of mathematical model through experimentation and nonlinear model identification of a CSTR process.The mathematical model based on first principles is developed from sodium hydroxide,ethyl acetate,and sodium acetate and ethanol mass balance.Then,the model equation is solving in MATLAB environment by doing algorithm for this process.The program for CSTR system is created and this program known as nonlinear fundamental model.The result from the MATLAB simulation program is compared with experimental result to validate the fundamental model. …”
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