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learning algorithm » learning algorithms (Expand Search)
coding algorithm » cosine algorithm (Expand Search), colony algorithm (Expand Search), scheduling algorithm (Expand Search)
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Sensitivity analysis and genetic algorithm-based shear capacity model for basalt FRC one-way slabs reinforced with BFRP bars
Published 2023“…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<sub>pred</sub>/V<sub>exp</sub>) ratio of 0.97 and a coefficient of variation of 17.91%.…”
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Predicting Compression Modes and Split Decisions for HEVC Video Coding Using Machine Learning Techniques
Published 2017Get full text
doctoralThesis -
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Teaching–learning-based optimization algorithm: analysis study and its application
Published 2024“…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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Multi-Objective Optimisation of Injection Moulding Process for Dashboard Using Genetic Algorithm and Type-2 Fuzzy Neural Network
Published 2024“…A full factorial experiment design is utilised to determine the best settings. These variables notably influence the end product’s physical and mechanical properties. …”
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Augmented arithmetic optimization algorithm using opposite-based learning and lévy flight distribution for global optimization and data clustering
Published 2022“…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. …”
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Large language models for code completion: A systematic literature review
Published 2024“…Different techniques can achieve code completion, and recent research has focused on Deep Learning methods, particularly Large Language Models (LLMs) utilizing Transformer algorithms. …”
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Day-Ahead Load Demand Forecasting in Urban Community Cluster Microgrids Using Machine Learning Methods
Published 2022“…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. …”
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Artificial neural network algorithms. (c1999)
Published 1999Get full text
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masterThesis -
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An exact and general model order reduction technique for the finite element solution of elastohydrodynamic lubrication problems
Published 2017“…This work presents an exact and general model order reduction (MOR) technique for a fast finite element resolution of elastohydrodynamic lubrication (EHL) problems. …”
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Image-Based Air Quality Estimation Using Convolutional Neural Network Optimized by Genetic Algorithms: A Multi-Dataset Approach
Published 2025“…The convolutional neural network is optimized using genetic algorithms, which dynamically tune hyper-parameters such as learning rate, batch size, and momentum to improve performance and generalizability across diverse environmental conditions. …”
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A Clinically Interpretable Approach for Early Detection of Autism Using Machine Learning With Explainable AI
Published 2025“…While research in ASD diagnosis is evolving through the application of machine learning (ML) techniques, practical implementation in clinical settings has not progressed at the same pace. …”
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Metaheuristic Optimization Algorithms for Training Artificial Neural Networks
Published 2012“…The Cuckoo Search (CS) algorithm is a recently developed meta-heuristic optimization algorithm which is suitable for solving optimization problems. …”
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Synthesis of MVL Functions - Part I: The Genetic Algorithm Approach
Published 2006“…Multiple-Valued Logic (MVL) has been used in the design of a number of logic systems, including memory, multi-level data communication coding, and a number of special purpose digital processors. …”
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Distributed DRL-Based Downlink Power Allocation for Hybrid RF/VLC Networks
Published 2021“…We implement a simulation environment to benchmark the proposed distributed DRL-based method against other methods such as Q-Learning (QL) and Deep Q-Networks (DQN), and centralized heuristic power allocation algorithms. …”