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binding » findings (Expand Search), building (Expand Search)
finding » findings (Expand Search)
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Leveraging Machine and Deep Learning Algorithms for hERG Blocker Prediction
Published 2025“…Some chemicals act as hERG blockers, resulting in prolonged QT intervals. Predicting the binding capability of molecules with hERG channels is expected to reduce the burden of cardiotoxicity testing in drug evaluation. …”
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Exploring the Dynamic Interplay of Deleterious Variants on the RAF1–RAP1A Binding in Cancer: Conformational Analysis, Binding Free Energy, and Essential Dynamics
Published 2024“…Hence, the current study focuses on the screening of clinically reported substitutions in the <i>RAF1</i> and <i>RAP1A</i> genes using predictive algorithms integrated with all‐atoms simulation, essential dynamics, and binding free energy methods. …”
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Fault detection and classification in hybrid energy-based multi-area grid-connected microgrid clusters using discrete wavelet transform with deep neural networks
Published 2024“…Nowadays, deep learning algorithms are essential for ensuring the reliable, safe, and efficient operation of these complex energy systems. …”
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A systematic review of text classification research based on deep learning models in Arabic language
Published 2020“…The evaluation criteria used in the algorithms of different neural network types and how they play a large role in the highly accurate classification of Arabic texts are discussed. …”
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Soft Sensor for NOx Emission using Dynamical Neural Network
Published 2020“…Lag space for the model is found by using genetic algorithm to find the best time delayed model. Lag space obtained from the linear model is then used for constriction of the dynamical neural network. …”
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Intelligent Rapidly-Exploring Random Tree Star Algorithm
Published 2024Get full text
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Efficient convex-elastic net algorithm to solve the Euclideantraveling salesman problem
Published 1998“…This paper describes a hybrid algorithm that combines an adaptive-type neural network algorithm and a nondeterministic iterative algorithm to solve the Euclidean traveling salesman problem (E-TSP). …”
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A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT
Published 2023“…This research proposed a hybrid model for energy-efficient cluster formation and a head selection (E-CFSA) algorithm based on convolutional neural networks (CNNs) and a modified k-mean clustering (MKM) method for MEC. …”
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PROVOKE: Toxicity trigger detection in conversations from the top 100 subreddits
Published 2022“…Therefore, in this study, we find the turning points (i.e., toxicity triggers) making conversations toxic. …”
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Developing a UAE-Based Disputes Prediction Model using Machine Learning
Published 2022Get full text
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