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

"…Featuring the capability of learning the correlations of time-series data, the proposed deep learning method is well-suited for extracting the valuable transient feature contained in the very beginning of the response curve. …"

Teaching–learning-based optimization algorithm: analysis study and its application حسب Abualigah, Laith

"…The teaching–learning-based optimization (TLBO) algorithm is a novel nature-based optimization approach that has attracted a lot of interest from researchers because of its great capacity to handle optimization problems. …"
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CNN and HEVC Video Coding Features for Static Video Summarization حسب Issa, Obada

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Design and implementation of a deep learning-empowered m-Health application حسب Akhan Akbulut (17380285)

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

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

Multi-Objective Optimisation of Injection Moulding Process for Dashboard Using Genetic Algorithm and Type-2 Fuzzy Neural Network حسب Mohammad Reza Chalak Qazani (13893261)

"…Computational techniques, like the finite element method, are used to analyse behaviours based on varied input parameters. …"

A combined algorithm based on finite elements and a modified methodof characteristics for the analysis of the corona in wire-ductelectrostatic precipitators حسب Al-Hamouz, Z.M.

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

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

Augmented arithmetic optimization algorithm using opposite-based learning and lévy flight distribution for global optimization and data clustering حسب Abu Zitar, Raed

"…This paper proposes a new data clustering method using the advantages of metaheuristic (MH) optimization algorithms. A novel MH optimization algorithm, called arithmetic optimization algorithm (AOA), was proposed to address complex optimization tasks. …"

DeepRaman: Implementing surface-enhanced Raman scattering together with cutting-edge machine learning for the differentiation and classification of bacterial endotoxins حسب Samir Brahim, Belhaouari

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Cluster-based anonymity model and algorithm for 1:1 dataset with a single sensitive attribute using machine learning technique حسب J. Jayapradha (21323774)

Design of adaptive arrays based on element position perturbations حسب Dawoud, M.M.

"…The authors report on the design of a digital feedback control system to provide null steering by controlling the array element positions automatically. The array comprises a signal processor, digital control algorithm (PID), stepper motors, shaft encoders, actuators and multiplexers. …"
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On the Optimization of Band Gaps in Periodic Waveguides حسب Jamil Renno (14070771)

الموضوعات: "…Nature-inspired optimization algorithms…"

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

"…The proposed approach can be significantly more efficient than training a machine learning algorithm using the raw numerical data. To evaluate the proposed method, two different structures are assessed where the training data is created using nonlinear finite element analysis. …"

Competitive learning/reflected residual vector quantization for coding angiogram images حسب Mourn, W.A.H.

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Automatic Video Summarization Using HEVC and CNN Features حسب Issa, Obada

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Extended Behavioral Modeling of FET and Lattice-Mismatched HEMT Devices حسب Khawam, Yahya Bader

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Day-Ahead Load Demand Forecasting in Urban Community Cluster Microgrids Using Machine Learning Methods حسب Sivakavi Naga Venkata Bramareswara Rao (15944992)

"…Thus, to identify the best load forecasting method in cluster microgrids, this article implements a variety of machine learning algorithms, including linear regression (quadratic), support vector machines, long short-term memory, and artificial neural networks (ANN) to forecast the load demand in the short term. …"