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Assessment of four dose calculation algorithms using IAEA-TECDOC-1583 with medium dependency correction factor (K<sub>med</sub>) application
Published 2024“…<h3>Purpose</h3><p dir="ltr">This study discusses the measurement of dose in clinical commissioning tests described in IAEA-TECDOC-1583. It explores the application of Monte Carlo (MC) modelled medium dependency correction factors (K<sub>med</sub>) for accurate dose measurement in bone and lung materials using the CIRS phantom. …”
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Efficient Approximate Conformance Checking Using Trie Data Structures
Published 2021“…In this paper, we contribute a new formulation of the proxy behavior derived from a model for approximate conformance checking. By encoding the proxy behavior using a trie data structure, we obtain a logarithmically reduced search space for alignment computation compared to a set-based representation. …”
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Stochastic management of hybrid AC/DC microgrids considering electric vehicles charging demands
Published 2020“…An IEEE standard test system is used as the hybrid AC/DC microgrid case study to assess the performance of proposed model.…”
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Parallel Algorithms for Distinguishing Nondeterministic Finite State Machines
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doctoralThesis -
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Tensile Test Optimization Using the Design of Experiment and Soft Computing
Published 2023“…The objective of this study is to investigate the effects of temperature, the area of the contact point, and the operator on the tensile test of brass samples. This study employs a hybrid soft computing approach, integrating an adaptive network-based fuzzy inference system (ANFIS), genetic algorithm (GA) optimization, and design of experiments (DOE). …”
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A hybrid heuristic approach to optimize rule based software quality estimation models. (c2008)
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masterThesis -
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A Novel Hybrid Genetic-Whale Optimization Model for Ontology Learning from Arabic Text
Published 2019“…Ontologies are used to model knowledge in several domains of interest, such as the biomedical domain. …”
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A genetic-based algorithm for fuzzy unit commitment model
Published 2000“…The genetic algorithm (GA) approach is then used to solve the proposed fuzzy UCP model. …”
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Optimization of Piezoelectric Sensor-Actuator for Plate Vibration Control Using Evolutionary Computation: Modeling, Simulation and Experimentation
Published 2021“…Both disturbance and control signal acting on the plate is created by using piezoelectric (PZT) patches. The analytical model is derived based on the Euler-Bernoulli model. …”
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Fuzzy Logic Adaptive Crow Search Algorithm for MPPT of a Partially Shaded Photovoltaic System
Published 2024“…Three distinct situations are used to validate the efficacy and speed of the proposed FL-CSA through numerical modeling and experimental testing. …”
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Capturing outline of fonts using genetic algorithm and splines
Published 2001“…The chromosomes have been constructed by considering the candidates of the locations of knots as genes. The best model among the candidates is searched by using the Akaike Information Criterion (AIC). …”
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Topology design of switched enterprise networks using a fuzzy simulated evolution algorithm
Published 2020“…The problem consists of deciding the number, types, and locations of the network active elements (hubs, switches, and routers), as well as the links and their capacities. …”
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Topology design of switched enterprise networks using a fuzzy simulated evolution algorithm
Published 2020“…The problem consists of deciding the number, types, and locations of the network active elements (hubs, switches, and routers), as well as the links and their capacities. …”
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Prediction of pressure gradient for oil-water flow: A comprehensive analysis on the performance of machine learning algorithms
Published 2022“…A Friedman's test and Wilcoxon Sign-Rank post hoc analysis with Bonferroni correction show that PG prediction errors using GP are significantly lower than using the ANN model (p < 0.05). …”
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Estimation of the methanol loss in the gas hydrate prevention unit using the artificial neural networks: Investigating the effect of training algorithm on the model accuracy
Published 2023“…Adjusting the weight and bias of the ANN model using an optimization algorithm is known as the training process. …”