Predicting Patient ICU Readmission Using Recurrent Neural Networks With Long Short-Term Memory حسب Nadia Rasheed (22997257)

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Deep Learning-Based Coding Strategy for Improved Cochlear Implant Speech Perception in Noisy Environments حسب Billel Essaid (22047578)

"…Experimental results on the TIMIT and Harvard Sentences datasets, enriched with diverse noise sources from the DEMAND database, yielded high intelligibility scores with a short-time objective intelligibility (STOI) of 0.8345, word recognition score (WRS) of 99.2636, and an near correlation coefficient (LCC) of 0.9607, underscoring the model’s capability to enhance speech perception in noisy CI environments, ensuring a balance between model size and speech quality, and surpassing the existing state-of-the-art techniques.…"

A Fast and Robust Gas Recognition Algorithm Based on Hybrid Convolutional and Recurrent Neural Network حسب Xiaofang Pan (1895950)

Time-varying volatility model equipped with regime switching factor: valuation of option price written on energy futures حسب Leduc, Guillaume

"…This paper explores the calculation of European option prices on energy futures using a time-varying volatility model enhanced by a regime switching factor. …"
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CNN and HEVC Video Coding Features for Static Video Summarization حسب Issa, Obada

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A New Parallel Genetic Algorithm Model حسب Al-Somani, Turki F.

"…This paper presents an implementation of three Genetic Algorithm models for solving a reliability optimization problem for a redundancy system with several failure modes, a modification on a parallel a genetic algorithm model and a new parallel genetic algorithm model. …"
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Logistics Optimization Using Hybrid Genetic Algorithm (HGA): A Solution to the Vehicle Routing Problem With Time Windows (VRPTW) حسب Ayesha Maroof (17984053)

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

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Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks حسب Najam Us Sahar Riyaz (22927843)

"…Ensemble schemes such as Gaussian process regression with simple averaging and gradient boosting regressors fortified by permutation feature importance improve robustness in noisy or multi-alloy environments. At the same time, virtual sample augmentation and genetic algorithm feature selection elevate sparse data performance, raising k-nearest neighbor models from R² = 0.05 to 0.99 in a representative thiophene set. …"

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 حسب Abdelbasset Krama (16870008)

"…This strategy uses a discrete model of the system based on the time domain to generate the average voltage vector at each sampling period, with the aim of canceling the errors between the estimated active and reactive power values and their references. …"

An exact and general model order reduction technique for the finite element solution of elastohydrodynamic lubrication problems حسب Habchi, W.

"…The proposed reduced model offers computational time speed-ups compared to the full model ranging between a factor of at least three and at best 15 depending on operating conditions. …"
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Reinforcement R-learning model for time scheduling of on-demand fog placement حسب Farhat, Peter

"…We also demonstrate the ability of our model to improve over time by adapting the new demand of users. …"
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Improved Transportation Model with Internet of Things Using Artificial Intelligence Algorithm حسب Ayman Khallel Al-Ani (17541447)

"…<p dir="ltr">In this paper, the application of transportation systems in real-time traffic conditions is evaluated with data handling representations. …"

A Genetic Algorithm for Improving Accuracy of Software Quality Predictive Models حسب Azar, Danielle

"…In this work, we present a genetic algorithm to optimize predictive models used to estimate software quality characteristics. …"
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An ant colony optimization algorithm to improve software quality prediction models حسب Azar, D.

"…Objective The objective of this paper is to present an approach that optimizes the accuracy of software quality predictive models when used to classify new data. Method This paper presents an adaptive approach that takes already built predictive models and adapts them (one at a time) to new data. …"
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Socially Motivated Approach to Simulate Negotiation Process حسب Hammadih, Mohammed Zaher

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A hybrid heuristic approach to optimize rule based software quality estimation models. (c2008) حسب Korkmaz, Rita

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Design of A Theoretical Framework For A Real-Time Fire Evacuation Guidance System حسب Abougharib, Arwa

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A Multiprocessing-Based Sensitivity Analysis of Machine Learning Algorithms for Load Forecasting of Electric Power Distribution System حسب Ameema Zainab (16864263)

Sensitivity analysis and genetic algorithm-based shear capacity model for basalt FRC one-way slabs reinforced with BFRP bars حسب Abathar Al-Hamrani (16494884)

"…Finally, a design equation that can predict the shear capacity of one-way BFRC-BFRP slabs was proposed based on genetic algorithm. The proposed model showed the best prediction accuracy compared to the available design codes and guidelines with a mean of predicted to experimental shear capacities (V_pred/V_exp) ratio of 0.97 and a coefficient of variation of 17.91%.…"