Search Results - (( developing models mixing algorithm ) OR ( java application learning algorithm ))
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Improved expectation maximization algorithm for Gaussian mixed model using the kernel method
Published 2013“…We look at several issues encountered when calculating the maximum likelihood estimates of the Gaussian mixed model using an Expectation Maximization algorithm. …”
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Fuzzy Mixed Assembly Line Sequencing and Scheduling Optimization Model Using Multiobjective Dynamic Fuzzy GA
Published 2014“…The simulation results highlight that the performance and efficacy of the proposed novel optimization algorithm are more efficient than the performance of the standard genetic algorithm in mixed assembly line sequencing model.…”
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An Educational Tool Aimed at Learning Metaheuristics
Published 2020“…In this paper, we introduce an education tool for learning metaheuristic algorithms that allows displaying the convergence speed of the corresponding metaheuristic upon setting/changing the dependable parameters. …”
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Conference or Workshop Item -
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
Published 2013“…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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Neural network algorithm development for Ion Sensitive Field Effect Transistor (ISFET) sensor / Muhammad Nasrul Hakim Adenan
Published 2013“…Backpropagation is used as the learning method of ANN model. The algorithm will be developed in MATLAB. …”
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Neural network algorithm development for Ion Sensitive Field Effect Transistor (ISFET) sensor: article / Muhammad Nasrul Hakim Adenan and Maizatul Zolkapli
Published 2013“…Backpropagation is used as the learning method of ANN model. The algorithm will be developed in MATLAB. …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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Mathematical models and optimization algorithms for low-carbon Location-Inventory-Routing Problem with uncertainty
Published 2024“…Given the NP-Hard nature of the three models proposed in this thesis, two metaheuristic algorithms have been developed. …”
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Diagnosis of Poor Control Loop Performance: Development of a Model Based Compensation Algorithm for Control Valve Stiction Nonlinearity
Published 2016“…The objective of this paper is to develop a model based compensation algorithm using optimization approach of MIQP based MPC backlash compensator for control valve stiction nonlinearity. …”
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Final Year Project -
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Mixed Unscented Kalman Filter and differential evolution for parameter identification
Published 2013“…First, a non-linear mathematical model is developed. Next, its parameters are identified using mixed Unscented Kalman Filter (UKF) and Differential Evolution (DE) based on the experimental data. …”
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Capacity planning for mixed-load tester under demand and testing time uncertainty
Published 2018“…Currently,the company’s issue is low tester utilization of about 71%,well below the target of 96%.The objective of this research is to improve tester utilization while achieving the production target under uncertain demand and testing time and also to determine the break-even point on the testers required.A novel approach of integrating a mathematical model,robust optimization model,genetic algorithm,simulation model and cost–volume –profit analysis was developed.Firstly,a mathematical model of mixed-load tester was formulated.Next,a set of discrete scenarios was proposed to address uncertain demand and testing time.A robust optimization and genetic algorithm model was developed to optimize the number of testers under the described uncertainties.Next,these scenarios were simulated using the Pro Model simulation software to validate the proposed models and to evaluate throughput and tester utilization.Finally,the cost–volume–profit analysis was performed for scenarios that require additional testers at various levels of uncertainties.The results showed that the proposed solution improved tester utilization by 25% compared to the current system.This research has contribution by developing novel hybrid methodology and able to provide useful insights to assist company’s managers to plan and allocate resources according to variations in customers’ demands and testing time.…”
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Thesis -
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Evolutionary Algorithms In Auction Models Of Service Procurement
Published 2019“…However, previous researchers focused on solving mixed integer model for the CA based WDP, which is not efficient for large scale instance. …”
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Development Of Machine Learning User Interface For Pump Diagnostics
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Monograph -
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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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Intergrated multi-objective optimisation of assembly sequence planning and assembly line balancing using particle swarm optimisation
Published 2013“…This research extends the problem type to integrated mixed-model ASP and ALB in order to generalize the problem. …”
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AI powered asthma prediction towards treatment formulation: an android app approach
Published 2022“…TensorFlow is utilized to integrate machine learning with an Android application. We accomplished asthma therapy using an Android application developed in Java and running on the Android Studio platform.…”
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A bacteria foraging algorithm for solving integrated multi-period cell formation and subcontracting production planning in a dynamic cellular manufacturing system
Published 2011“…This research aims to apply this emerging optimisation algorithm to develop a mixed-integer programming model for designing cellular manufacturing systems (CMSs), and production planning in dynamic environments. …”
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