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Don't understand a measure? Learn it: Structured Prediction for Coreference Resolution optimizing its measures
Published 2017“…The accurate model comparison on the standard CoNLL-2012 setting shows the benefit of more expressive loss functions.…”
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An Optimized Feature Selection Technique in Diversified Natural Scene Text for Classification Using Genetic Algorithm
Published 2021“…The Support Vector Machine (SVM) algorithm is used for classification and the average F-Score is used as fitness function and target condition. …”
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Computational evluation of protein energy functions
Published 2014“…In this project, we carry out a computational evaluation of putative protein energy functions. Our findings show that the CHARMM energy model tends to be more appropriate for ab initio computational techniques that predict protein structures. …”
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Real-Time Implementation of High Performance Control Scheme for Grid-Tied PV System for Power Quality Enhancement Based on MPPC-SVM Optimized by PSO Algorithm
Published 2018“…<p dir="ltr">This paper proposes a high performance control scheme for a double function grid-tied double-stage PV system. It is based on model predictive power control with space vector modulation. …”
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Exploring New Parameters to Advance Surface Roughness Prediction in Grinding Processes for the Enhancement of Automated Machining
Published 2024“…To evaluate a robust algorithm, a method is devised that involves different networks utilizing various activation functions and neuron sizes to distinguish and select the best architecture for this study. …”
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Iterative Least Squares Functional Networks Classifier
Published 2007“…A comparative study with the most common classification algorithms in both machine learning and statistics communities is carried out. …”
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Cross entropy error function in neural networks
Published 2002“…The ANN is implemented using the cross entropy error function in the training stage. The cross entropy function is proven to accelerate the backpropagation algorithm and to provide good overall network performance with relatively short stagnation periods. …”
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From Collatz Conjecture to chaos and hash function
Published 2023“…The effectiveness and dependability of the proposed hash function are evaluated by comparing it with two well-known hash algorithms, namely SHA-3 and SHA-2, as well as several other Chaos-based hash algorithms. …”
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Boosting the visibility of services in microservice architecture
Published 2023“…We utilized parameter optimization techniques, namely Grid Search, Random Search, Bayes Search, Halvin Grid Search, and Halvin Random Search to fine-tune the hyperparameters of our classifier models. Experimental results demonstrated that the CatBoost algorithm achieved the highest level of accuracy (90.42%) in predicting microservice quality.…”
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Motion Artifacts Correction From EEG and fNIRS Signals Using Novel Multiresolution Analysis
Published 2022Subjects: -
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Optimization of Support Structures for Offshore Wind Turbines using Genetic Algorithm with Domain-Trimming (GADT)
Published 2017“…The two versions of the optimization problem are nonlinearly constrained where the objective function is the material weight of the supporting truss. …”
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Stochastic evolution algorithm for technology mapping
Published 1998“…SELF-Map is based on the Stochastic Evolution (SE) algorithm. The state space model of the problem is defined and suitable cost function which allows optimization for area, delay, or area-delay combinations is proposed. …”
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On the Optimization of Band Gaps in Periodic Waveguides
Published 2025“…The second example involves a periodic beam with alternating thick and thin segments, modeled using WFE, where the objective is to minimize transmissibility over a lower frequency range. …”
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An improved kernelization algorithm for r-Set Packing
Published 2010“…We present a reduction procedure that takes an arbitrary instance of the r -Set Packing problem and produces an equivalent instance whose number of elements is in O(kr−1), where k is the input parameter. Such parameterized reductions are known as kernelization algorithms, and a reduced instance is called a problem kernel. …”
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Metaheuristic Algorithm for State-Based Software Testing
Published 2018“…This article presents a metaheuristic algorithm for testing software, especially web applications, which can be modeled as a state transition diagram. …”
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Finite state machine state assignment for area and power minimization
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Evolutionary algorithm for predicting all-atom protein structure
Published 2011“…We present an improved version of a scatter search (SS) algorithm for predicting all-atoms protein structures using a recent energy model. …”
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