Improvement Algorithm for Limited Space Scheduling by Zouein, Pierrette

“…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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Evolutionary algorithm for protein structure prediction by Mansour, Nashat

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Correlation Clustering via s-Club Cluster Edge Deletion by Makarem, Norma

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Sensitivity to parameters and general applicability of genetic algorithms and simulated annealing algorithms for mapping data to multicomputers. (c1994) by Kawash, Jalal Y.

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An Effective Hybrid NARX-LSTM Model for Point and Interval PV Power Forecasting by Mohamed Massaoudi (16888710)

“…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. …”

Predicting Dropouts among a Homogeneous Population using a Data Mining Approach by BILQUISE, GHAZALA

“…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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An Uncertainty Based Genetic Algorithm Approach for Project Resource Scheduling by ALKETBI, SAIF

“…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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An Intensive and Comprehensive Overview of JAYA Algorithm, its Versions and Applications by Abu Zitar, Raed

“…Initially, the optimization model and convergence characteristics of JAYA algorithm are carefully analyzed. …”
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Interpreting patient-Specific risk prediction using contextual decomposition of BiLSTMs: application to children with asthma by Rawan AlSaad (14159019)

“…</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. …”

Nonlinear analysis of shell structures using image processing and machine learning by M.S. Nashed (16392961)

“…We show that the results of the trained network agree well with the results of the nonlinear finite element analysis. …”

Novel algorithms for accurate DNA base-calling by Mohammed, Omniyah Gul

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A Hybrid Approach for Predicting Critical Machining Conditions in Titanium Alloy Slot Milling Using Feature Selection and Binary Whale Optimization Algorithm by Amirsajjad Rahmani (17541453)

Assessment of four dose calculation algorithms using IAEA-TECDOC-1583 with medium dependency correction factor (K_med) application by Aram Rostami (22045274)

“…It explores the application of Monte Carlo (MC) modelled medium dependency correction factors (K_med) for accurate dose measurement in bone and lung materials using the CIRS phantom. …”

An L2 Gap Metric Identification Algorithm by Al-Amer, Samir Hasan

“…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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Metaheuristic Algorithm for State-Based Software Testing by Haraty, Ramzi A.

“…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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Delay Optimization in LoRaWAN by Employing Adaptive Scheduling Algorithm With Unsupervised Learning by Zulfiqar Ali (117651)

“…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). …”

Predicting the Release of Chemotherapeutics From the Core of Polymeric Micelles Using Ultrasound by Abdel-Hafez, Mamoun

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Analyzing Partial Shading in PV Systems Using Wavelet Packet Transform and Empirical Mode Decomposition Techniques by Kais Abdulmawjood (17947784)

Performance of artificial intelligence models in estimating blood glucose level among diabetic patients using non-invasive wearable device data by Arfan Ahmed (17541309)

“…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. …”

Energy utilization assessment of a semi-closed greenhouse using data-driven model predictive control by Farhat Mahmood (15468854)

“…The proposed method consists of a multilayer perceptron model representing the greenhouse system integrated with an objective function and an optimization algorithm. …”