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201
A reduced model for phase-change problems with radiation using simplified PN approximations
Published 2025“…In these problems at high temperature, a mathematical model used to describe the heat transfer and phase change should also include equations accounting for thermal radiation. …”
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202
Predicting Plasma Vitamin C Using Machine Learning
Published 2022“…The objective of this study is to predict plasma vitamin C using machine learning. The NHANES dataset was used to predict plasma vitamin C in a cohort of 2952 American adults using regression algorithms and clustering in a way that a hypothetical health application might. …”
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203
Modeling of Chlorophyll-a and Eutrophication Indicators in the Dubai Creek Area using Remote Sensing
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204
Bee Colony Algorithm for Proctors Assignment.
Published 2015“…The Bee Colony algorithm is a recent population-based search algorithm that mimics the natural behavior of swarms of honey bees during the process of collecting food. …”
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205
Improvement Algorithm for Limited Space Scheduling
Published 2001“…This paper addresses the combined problem termed “space scheduling” and presents an algorithmic time-space trade-off model for adjusting activity durations and start dates to decrease the need for space over congested time periods. …”
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206
Evolutionary algorithm for protein structure prediction
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207
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Process Mining over Unordered Event Streams
Published 2020“…Using directly-follows graphs as a basic model for many process mining tasks, we provide two approaches to handle such unorderedness, either through buffering or speculative processing. …”
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209
An Effective Hybrid NARX-LSTM Model for Point and Interval PV Power Forecasting
Published 2021“…Then, the stacked LSTM model, optimized by Tabu search algorithm, uses the residual error correction associated with the original data to produce a point and interval PVPF. …”
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210
Predicting Dropouts among a Homogeneous Population using a Data Mining Approach
Published 2019“…Our research reveals that the Gradient Boosted Trees is a robust algorithm that predicts dropouts with an accuracy of 79.31% and AUC of 88.4% using only pre-enrollment data. …”
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211
An Uncertainty Based Genetic Algorithm Approach for Project Resource Scheduling
Published 2016“…The work presented in thesis add to the existing literature in a proposing the use of a genetic algorithm uncertain approach to resource- scheduling in projects. …”
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212
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213
An Intensive and Comprehensive Overview of JAYA Algorithm, its Versions and Applications
Published 2021“…Initially, the optimization model and convergence characteristics of JAYA algorithm are carefully analyzed. …”
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214
Interpreting patient-Specific risk prediction using contextual decomposition of BiLSTMs: application to children with asthma
Published 2019“…</p><h3>Methods</h3><p dir="ltr">We use a real EHR dataset comprising 11071 patients, to evaluate and compare CD interpretations from LSTM and BiLSTM models. …”
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215
Mapping realistic data sets on parallel computers
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216
Assessment of four dose calculation algorithms using IAEA-TECDOC-1583 with medium dependency correction factor (K<sub>med</sub>) application
Published 2024“…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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217
Type 2 Diabetes Mellitus Automated Risk Detection Based on UAE National Health Survey Data: A Framework for the Construction and Optimization of Binary Classification Machine Learn...
Published 2020“…LR with the reduced feature set using the intersection between CS and RFE proved to be the best model among the tested algorithms. …”
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218
An L2 Gap Metric Identification Algorithm
Published 2020“…In this paper, an L2-gap metric identification algorithm is proposed. The algorithm uses a set of frequency response samples to come up with rational models so that the L2-gap between the observations and the identified model is minimized. …”
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219
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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220
Delay Optimization in LoRaWAN by Employing Adaptive Scheduling Algorithm With Unsupervised Learning
Published 2023“…This paper aims to optimize the delay in LoRaWAN by using an Adaptive Scheduling Algorithm (ASA) with an unsupervised probabilistic approach called Gaussian Mixture Model (GMM). …”