Search Results - (( using optimization method algorithm ) OR ( a interactive learning algorithm ))
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Particle swarm optimization with deep learning for human action recognition
Published 2021“…This paper proposes a deep learning framework for human action recognition to overcome the drawbacks of the current state-of-the-art methods. …”
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Social media mining: a genetic based multiobjective clustering approach to topic modelling
Published 2021“…However, less works have been conducted in applying multiobjective based algorithm for topic extraction. Most of these algorithms are not optimized, even if they are, they are only optimized by using a single objective method and may underperform when solving real-world problems which are typically multi-objectives in nature. …”
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A fast learning network with improved particle swarm optimization for intrusion detection system
Published 2019“…This situation makes the detection of cyber-based attacks on computer networks a relevant and challenging area of research. The Fast Learning Network (FLN) is one of the new machine learning algorithms that are easy to implement, computationally efficient, and with excellent learning performance characteristics. …”
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An adaptive HMM based approach for improving e-Learning methods
Published 2023“…This adaptive algorithm can thus be applied to any e-learning platform for optimal content delivery to its users in real-time. © 2014 IEEE.…”
Conference Paper -
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Nomadic people optimizer (NPO) for large-scale optimization problems
Published 2019“…A metaheuristic is defined as an iterative generation process which guides a subordinate heuristic through a combination of different intelligent concepts for exploring and exploiting the solution space; they employ learning strategies to structure information in order to establish efficient near-optimal solutions. …”
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Social media mining: a genetic based multiobjective clustering approach to topic modelling
Published 2021“…However, less works have been conducted in applying multiobjective based algorithm for topic extraction. Most of these algorithms are not optimized, even if they are, they are only optimized by using a single objective method and may underperform when solving real-world problems which are typically multi-objectives in nature. …”
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An intelligent framework for modelling and active vibration control of flexible structures
Published 2004“…The first controller design is formulated so as to allow on-line modeling, controller design and implementation and thus, yield a self-tuning control algorithm. Performance of the AVC algorithm is assessed based on parametric design techniques, using RLS and GAS, and non-parametric design techniques, using MLP-NN and ANFIS in the suppression of vibration of the flexible structures. …”
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Short-term electricity price forecasting in deregulated electricity market based on enhanced artificial intelligence techniques / Alireza Pourdaryaei
Published 2020“…In this research, a hybrid electricity price forecasting methodology is proposed using two-stage feature selection method and optimization using adaptive neuro-fuzzy inference system (ANFIS) technique as a forecasting engine. …”
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Kernerlized Correlation Filters Parameters Optimization For Enhanced Visual Tracking
Published 2017“…A simple optimization is used in here, where the global best results with respect to the value of the parameters are selected through a range of values defined in our work. …”
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Monograph -
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Genetic ensemble biased ARTMAP method of ECG-Based emotion classification
Published 2012“…The ARTMAP system is dependent on training sequence presentation to determine the effectiveness of the learning processes, as well as the strength of the biasing parameter, lambda λ. The optimal combination of λ and training sequence can be computed efficiently using a genetic permutation algorithm. …”
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Conference or Workshop Item -
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Leaf condition analysis using convolutional neural network and vision transformer
Published 2024“…Through the use of a hybrid deep learning model that combines vision transformer and convolutional neural networks for classification, the algorithm can be optimized. …”
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Brewing perfection: real-time monitoring of arabic coffee using iot and machine learning
Published 2026“…Using the YOLOv8 algorithm, a model was trained to detect and track the state of coffee in real time. …”
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Proceeding Paper -
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Improving Patient Rehabilitation Performance In Exercise Games Using Collaborative Filtering Approach
Published 2024journal::journal article -
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Improving neural networks training using experiment design approach
Published 2005“…This data is selected by two methods: random and Experiment Design Approach (D-optimal and Maxmin Distance). …”
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Mean of correlation method for optimization of affective states detection in children
Published 2018“…Result from the fine k-NN classifier obtained promises the efficacy of the proposed approach to be applied in our future work in human–robot interaction for autistic children learning and training.…”
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Customer mobile behavioral segmentation and analysis in telecom using machine learning
Published 2021“…Unsupervised machine learning algorithm K-means was used to cluster the data, and these results were analyzed and labeled with labels and descriptions. …”
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Framework for stream clustering of trajectories based on temporal micro clustering technique
Published 2018“…The algorithm assigns a life time for each newly created temporal micro clusters so that the new incoming batch of trajectories segments will interact only with the non-expired temporal micro clusters. …”
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Path planning methods for autonomous vehicles at intersections: A review
Published 2026“…This review paper presents a comprehensive analysis of major path-planning methods used in Autonomous Vehicle (AV) navigation at intersections, including graph-based, sampling-based, curve-based, optimization-based, and machine learning–based approaches, while also examining emerging AI-driven path planners to better understand their capabilities. …”
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