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Using genetic algorithms to optimize software quality estimation models
Published 2004“…This thesis explores the use of genetic algorithms for the problem of optimizing existing rule-based software quality estimation models. …”
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masterThesis -
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Evaluation of Aerosol Optical Depth and Aerosol Models from VIIRS Retrieval Algorithms over North China Plain
Published 2017“…The aerosol model used in VIIRS_EDR algorithm shows that dust and clean urban models were the dominant model types during the evaluation period. …”
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Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks
Published 2025“…At the same time, virtual sample augmentation and genetic algorithm feature selection elevate sparse data performance, raising k-nearest neighbor models from R<sup>2</sup> = 0.05 to 0.99 in a representative thiophene set. …”
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Efficient Approximate Conformance Checking Using Trie Data Structures
Published 2021“…Specifically, conformance checking may rely only on so-called proxy behavior, a subset of the behavior of the model. However, the question how such proxy behavior shall be represented for efficient alignment computation has been largely neglected. …”
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Algorithmic Study of Online Multi-Facility Location Problems
Published 2022“…To overcome facility failures and provide a robust solution, we investigate in this paper FL problems that require each client to be connected to multiple facilities, represented by an additional input parameter. The aim of the algorithm is then to provide a robust service to all clients while minimizing the total connecting and facility purchasing costs. …”
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Optimizing Document Classification: Unleashing the Power of Genetic Algorithms
Published 2023“…Additionally, our proposed model optimizes the features using a genetic algorithm. …”
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Natural optimization algorithms for the cross-dock door assignment problem
Published 2016“…This paper modifies a classical mathematical model that represents the CDAP and implements an evolutionary metaheuristic SS algorithm and tests it and then compares the results with those of another evolutionary algorithm, i.e., genetic algorithm (GA). …”
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Efficient Dynamic Cost Scheduling Algorithm for Data Batch Processing
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doctoralThesis -
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Identification of physically based models of residential air-conditioners for direct load control management
Published 2004“…In this work, we address the problem of identifying the parameters of an aggregated elemental model representing a housing unit with an A/C system. …”
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Modeling of magnetization curves for computer-aided design
Published 1993“…A simple algorithm is presented for obtaining the coefficients of the sine-series function for modelling the magnetization curves of magnetic materials. …”
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Development of Machine Learning Models for Studying the Premixed Turbulent Combustion of Gas-To-Liquids (GTL) Fuel Blends
Published 2024“…In addition, the possible minimum and maximum values of responses at the corresponding operating parameters are found using a genetic algorithm (GA) approach. Model 1 could capture the computational fluid dynamics (CFD) outputs with high precision at different flame radiuses and time instants with a maximum absolute error percentage of 5.46%. …”
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Modeling and automated blackbox regression testing of web applications
Published 2008“…Motivated by the fact that there is no single model to represent the entire web application, and to model it from different perspectives at the same time, we propose a single analysis model with it testing techniques which models and tests the three poles of the web application: the client side pages navigated by the user, the server side programs executed at runtime, and the architectural environment hosting the application. …”
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Modeling, testing, and regression testing of web applications. (c2006)
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masterThesis -
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Modelling Exchange Rates during Currency Crisis using Neural Networks
Published 2006“…This paper presents an artificial neural network (ANN) approach to the forecasting of exchange rate movements during periods of currency crises characterized by excessive volatility. The models are built using the feedforward ANN structure trained by the backpropagation algorithm. …”
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Internal Model Control Structure Using Adaptive Inverse Control Strategy
Published 2003“…In this paper, we propose a new adaptive IMC scheme based on adaptive finite impulse response filters, which can be designed for both minimum and non-minimum phase systems in the same fashion. The internal model of the plant is estimated by recursive least square algorithm and the inverse of the system by least mean square. …”
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Performance of artificial intelligence models in estimating blood glucose level among diabetic patients using non-invasive wearable device data
Published 2023“…One of the key aspects of WDs with machine learning (ML) algorithms is to find specific data signatures, called Digital biomarkers, that can be used in classification or gaging the extent of the underlying condition. …”