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301
Concurrent BIST Synthesis and Test Scheduling Using Genetic Algorithms
Published 2007“…The method maximizes concurrent testing of modules while performing the allocation of functional units, test registers, and interconnects. The method is based on a genetic algorithm that efficiently explores the testable design space and finds a sub-optimal test registers assignment for each k-test session. …”
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302
Data mining approach to predict student's selection of program majors
Published 2019“…The approach includes a methodology to manage data mining projects, sampling techniques to handle imbalanced data and multiclass data, a set of classification algorithms to predict and measures to evaluate performance of models. …”
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An optimization approach for the computation of the minimumdestabilizing uncertainty volume
Published 2000“…We propose a nonlinear optimization based algorithm for the computation of the stability region for uncertain polynomials. …”
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305
Use of Data Mining Techniques to Detect Fraud in Procurement Sector
Published 2022“…The method used in this research is a classification of models and algorithms used in data mining. All techniques also will be studied; they include clustering, tracking patterns, classifications and outlier detection. …”
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306
Nonlinear Control of Brushless Dual-Fed Induction Generator With a Flywheel Energy Storage System for Improved System Performance
Published 2025“…In the first stage, a robust Sliding Mode Control (SMC)-based nonlinear decoupled control algorithm is designed to efficiently regulate BDFIG operation. …”
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307
An efficient approach for textual data classification using deep learning
Published 2022“…<p dir="ltr">Text categorization is an effective activity that can be accomplished using a variety of classification algorithms. In machine learning, the classifier is built by learning the features of categories from a set of preset training data. …”
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308
Dynamic performance evaluation and machine learning-assisted optimization of a solar-driven system integrated with PCM-based thermal energy storage: A case study approach
Published 2025“…<p>This paper presents the design, modeling, and multi-objective optimization of an advanced solar energy system based on concentrated solar power technology, aimed at sustainable electricity generation in urban environments. …”
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309
A new multiobjective evolutionary algorithm forenvironmental/economic power dispatch
Published 2001“…A new nondominated sorting genetic algorithm (NSGA) based approach is proposed to handle the problem as a true multiobjective optimization problem with competing and noncommensurable objectives. …”
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310
Cyberbullying Detection and Abuser Profile Identification on Social Media for Roman Urdu
Published 2024Subjects: -
311
A modified ant colony algorithm for evolutionary design of digital circuits
Published 2003“…In this paper, a multiobjective optimization of logic circuits based on a modified ant colony (ACO) algorithm is presented. …”
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312
A method for optimizing test bus assignment and sizing for system-on-a-chip
Published 2017“…Test access mechanism (TAM) is an important element of test access architectures for embedded cores and is responsible for on-chip test patterns transport from the source to the core under test to the sink. …”
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Wild Blueberry Harvesting Losses Predicted with Selective Machine Learning Algorithms
Published 2022“…The LR model showed the foremost predictions of ground loss as compared to all the other models analyzed. …”
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315
Assessment of static pile design methods and non-linear analysis of pile driving
Published 2006“…The pile/soil interaction system is described by a mass/spring/dashpot system where the properties of each component are derived from rigorous analytical solutions or finite element analysis. The outcome of this research is an algorithm that can be used to predict pile displacement and driving stresses. …”
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masterThesis -
316
A hybridization of evolution strategies with iterated greedy algorithm for no-wait flow shop scheduling problems
Published 2024“…The ES algorithm begins with a random initial solution and uses an insertion mutation to optimize the solution. …”
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317
Metaheuristic algorithm for testing web 2.0 applications. (c2012)
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masterThesis -
318
A stochastic iterative learning control algorithm with application to an induction motor
Published 2004“…A recursive optimal algorithm, based on minimizing the input error covariance matrix, is derived to generate the learning gain matrix of a P-type ILC for linear discrete-time varying systems with arbitrary relative degree. …”
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Stochastic P-type/D-type iterative learning control algorithms
Published 2003“…The optimal algorithm is based on minimizing the trace of the input error covariance matrix. …”
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