Search Results - (( motion detection system algorithm ) OR ( swarm optimization learning algorithm ))
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Particle swarm optimization with deep learning for human action recognition
Published 2021“…Also, the current motion target detection algorithms extract features from the relevant object only if the moving object has complex texture features. …”
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Development of optimized damage prediction method for health monitoring of ultra high performance fiber-reinforced concrete communication tower
Published 2018“…Therefore, this study aims to develop a new health monitoring system for communication towers based on AdaBoost, Bagging, and RUSBoost algorithms as hybrid algorithm, which can predict the damage by using noisy, random, unstable, and skewed frequency data with high accuracy. …”
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Predicting longitudinal dispersion coefficient using ensemble models and optimized multi-layer perceptron models
Published 2024Subjects:Article -
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Investigating the Performance of Deep Reinforcement Learning-Based MPPT Algorithm under Partial Shading Condition
Published 2024Subjects:Conference Paper -
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Particle swarm optimization for neural network learning enhancement
Published 2006“…In this study, the latest optimization algorithm, Particle Swarm Optimization (PSO) is chosen and applied in feedforward neural network to enhance the learning process in terms of convergence rate and classification accuracy. …”
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A particle swarm optimization levy flight algorithm for imputation of missing creatinine dataset
Published 2021“…We improve the algorithms by modifying the Particle Swarm Optimization Algorithm (PSO), by enhancing the algorithm with levy flight (PSOLF). …”
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Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization
Published 2015“…This paper presents a classification approach on android malware using candidate detectors generated from an unsupervised association rule of Apriori Algorithm. The algorithm is improved with Particle Swarm Optimization that trains three different supervised classifiers. …”
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Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm
Published 2011“…Artificial Neural Network (ANN) is a new information processing system with large quantity of highly interconnected neurons or elements processing parallel to solve problems.Recently, evolutionary computation technique, Artificial Fish Swarm Algorithm (AFSA) is chosen to optimize global searching of ANN.In optimization process, each Artificial Fish (AF) represents a neural network with output of fitness value.The AFSA is used in this study to analyze its effectiveness in enhancing Multilayer Perceptron (MLP) learning compared to Particle Swarm Optimization (PSO) and Differential Evolution (DE) for classification problems.The comparative results indeed demonstrate that AFSA show its efficient, effective and stability in MLP learning.…”
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Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection
Published 2020“…In addition, ISSA was compared with four well-known optimization algorithms such as Genetic Algorithm, Particle Swarm Optimization, Grasshopper Optimization Algorithm, and Ant Lion Optimizer. …”
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Particle Swarm Optimization in Machine Learning Prediction of Airbnb Hospitality Price Prediction
Published 2022“…Particle Swarm Optimization is a meta-heuristics algorithm widely used for optimization problems. …”
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Forecasting of photovoltaic output using hybrid particle swarm optimization-artificial neural network model / Muhamad Faizol Adli Abdullah
Published 2010“…To overcome these problems, Particle Swarm Optimization (PSO) has been used to determine optimal value for BP parameters such as learning rate and momentum rate and also for weighting optimization. …”
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Optimal neural network approach for estimating state of energy of lithium-ion battery using heuristic optimization techniques
Published 2023“…Backpropagation algorithms; Errors; Learning algorithms; Mean square error; Neural networks; Particle swarm optimization (PSO); Torsional stress; Back propagation neural networks; Backtracking search algorithms; Heuristic optimization technique; Optimal neural network; Optimization algorithms; Particle swarm optimization algorithm; Root mean square errors; state of energy; Lithium-ion batteries…”
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WEBCAM MOTION DETECTION USINGVISUAL BASIC
Published 2005“…Watch Eyes Motion Detection System is aproject used to enhance student's interest in multimedia system development, but at the same time the project can be used as motion detection system that will help any person in doing research in motion detection purposes. …”
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Applying machine learning and particle swarm optimization for predictive modeling and cost optimization in construction project management
Published 2024“…This study emphasizes the importance of Machine Learning and Particle Swarm Optimization (PSO) in the context of predictive modeling and cost optimization within the field of construction project management. …”
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Taylor-Bird Swarm Optimization-Based Deep Belief Network For Medical Data Classification
Published 2022“…However, finding the most appropriate deep learning algorithm for a medical classification problem along with its optimal parameters becomes a difficult task. …”
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Pressure vessel design simulation: Implementing of multi-swarm particle swarm optimization
Published 2019“…Among several optimization models, multi-swarm approach has been proposed most recently for balancing the exploration and exploitation capability through the Particle Swarm Optimization (PSO) algorithm. …”
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Web Camera Application For Motion Detection
Published 2003“…The new method to detect motion is "vision motion detection". It is the artificial way of machine vision system compared to human's vision in detecting motion. …”
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Artificial fish swarm optimization for multilayer network learning in classification problems
Published 2012“…Nature-Inspired Computing (NIC) has always been a promising tool to enhance neural network learning. Artificial Fish Swarm Algorithm (AFSA) as one of the NIC methods is widely used for optimizing the global searching of ANN.In this study, we applied the AFSA method to improve the Multilayer Perceptron (MLP) learning for promising accuracy in various classification problems.The parameters of AFSA: AFSA prey, AFSA swarm and AFSA follow are implemented on the MLP network for improving the accuracy of various classification datasets from UCI machine learning. …”
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Machine failure prediction technique using recurrent neural network long short-term memory-particle swarm optimization algorithm
Published 2019“…A result of proof of concept validates that by increasing the number of epochs, the accuracy of prediction has improved but increases the execution time. To optimize between the accuracy and execution time, a population-inspired Particle Swarm Optimization (PSO) algorithm is employed. …”
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