Search Results - (( developing data swarm algorithm ) OR ( java application optimization algorithm ))
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Then canonical Polyadic decomposition-based attribute reduction is applied to the offload-able task to reduce the data size. Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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Optimization of blood vessel detection in retina images using multithreading and native code for portable devices
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Performance evaluation of real-time multiprocessor scheduling algorithms
Published 2016“…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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Route Optimization System
Published 2005“…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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Final Year Project -
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Taylor-Bird Swarm Optimization-Based Deep Belief Network For Medical Data Classification
Published 2022“…Then, the selected features are given as input to the DBN classifier which is trained using the Taylor-based bird swarm algorithm (Taylor-BSA). Taylor-BSA is designed by combining the Taylor series and bird swarm algorithm (BSA).…”
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Data normalization techniques in swarm-based forecasting models for energy commodity spot price
Published 2014“…Data mining is a fundamental technique in identifying patterns from large data sets.The extracted facts and patterns contribute in various domains such as marketing, forecasting, and medical.Prior to that, data are consolidated so that the resulting mining process may be more efficient.This study investigates the effect of different data normalization techniques.which are Min-max, Z-score and decimal scaling, on Swarm-based forecasting models.Recent swarm intelligence algorithms employed includes the Grey Wolf Optimizer (GWO) and Artificial Bee Colony (ABC).Forecasting models are later developed to predict the daily spot price of crude oil and gasoline.Results showed that GWO works better with Z-score normalization technique while ABC produces better accuracy with the Min-Max.Nevertheless, the GWO is more superior than ABC as its model generates the highest accuracy for both crude oil and gasoline price.Such a result indicates that GWO is a promising competitor in the family of swarm intelligence algorithms.…”
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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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An efficient IDS using hybrid Magnetic swarm optimization in WANETs
Published 2018“…Our developed algorithm works in extracting the most relevant features that can assist in accurately detecting the network attacks. …”
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An Optimized Binary Scheduling Controller for Microgrid Energy Management Considering Real Load Conditions
Published 2024“…This study presents an optimal schedule controller for microgrid energy management, utilizing the Binary Particle Swarm algorithm (BPSO) to minimize costs and ensure optimal power delivery to loads. …”
Conference Paper -
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Evolvable traffic signal control for intersection congestion alleviation with enhanced particle swarm optimisation
Published 2017“…Enhanced particle swarm optimisation algorithm is developed to ensure result consistency with smaller variation. …”
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Proceedings -
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Data transmission in wireless sensor network with greedy function and particle swarm optimization
Published 2019“…As distances affect greatly on the energy consumption, Particle Swarm Optimization (PSO) is developed to replace greedy algorithm in PEGASIS to reduce the distances of data transmission. …”
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Proceedings -
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Predictive modeling of condominium prices using a Particle Swarm Optimization-Random Forest approach / Che Wan Sufia Che Wan Samsudin
Published 2025“…Essential phases of the project include data collection, data preprocessing, and the implementation of the Particle Swarm Optimization-Random Forest price prediction algorithm. …”
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An expanded square pattern technique in swarm of quadcopters for exploration algorithm
Published 2017“…We simulate the swarm-based exploration algorithm with expanded square pattern using a VREP simulator. …”
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An Efficient IDS Using Hybrid Magnetic Swarm Optimization in WANETs
Published 2018“…Our developed algorithm works in extracting the most relevant features that can assist in accurately detecting the network attacks. …”
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Multi-objective clustering algorithm using particle swarm optimization with crowding distance (MCPSO-CD)
Published 2020“…According to the literature, crowding distance is one of the most efficient algorithms that was developed based on density measures to treat the problem of selection mechanism for archive updates. …”
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Estimation of small-scale kinetic parameters of escherichia coli (E. coli) model by enhanced segment particle swarm optimization algorithm ese-pso
Published 2023“…The numerical findings indicate a good agreement between the observed and predicted data. In this regard, the result of the ESe-PSO algorithm achieved superior accuracy compared with the Segment Particle Swarm Optimization (Se-PSO), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Differential Evolution (DE) algorithms. …”
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TBat: A Novel Strategy for Minimization of T-Way Interaction Test Suite Based on the Particle Swarm Optimization and the Bat Algorithm
Published 2016“…Often, this results into combinatorial explosion of test cases. This project develops a novel strategy to minimize the test consideration using the Particle Swarm Optimization and the Bat Algorithm.…”
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