Search Results - (( evolution optimization sensor algorithm ) OR ( mode selection method algorithm ))
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1
Cluster head selection optimization in wireless sensor network via genetic-based evolutionary algorithm
Published 2020“…Genetic-based evolutionary algorithms such as Genetic Algorithm (GA) and Differential Evolution (DE) have been popularly used to optimize cluster head selection in WSN to improve energy efficiency for the extension of network lifetime. …”
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2
A centralized localization algorithm for prolonging the lifetime of wireless sensor networks using particle swarm optimization in the existence of obstacles
Published 2017“…In a previous research, a relocating algorithm for mobile sensor network had been introduced and the goal was to save energy and prolong the lifetime of the sensor networks using Particle Swarm Optimization (PSO) where both of sensing radius and travelled distance had been optimized in order to save energy in long-term and shortterm. …”
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3
Design, optimization and fabrication of a climbing six articulated-wheeled robot using artificial evolution and 3D printing
Published 2015“…In this research, an artificial evolution approach utilizing Single-Objective Evolutionary Algorithm (SOEA) and Multi-Objective Evolutionary Algorithm (MOEA) respectively are investigated in the automatic design and optimization of the morphology of a Six Articulated-Wheeled Robot (SAWR) with climbing ability. …”
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4
An improved gbln-pso algorithm for indoor localization problem in wireless sensor network
Published 2022“…Then, we compared the result with Particle Swarm Optimization (PSO), Differential Evolution Particle Swarm Optimization (DEPSO), Health Particle Swarm Optimization (HPSO) and Global best Local Neigborhood Particle Swarm Optimization (GbLN-PSO) algorithm. …”
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5
Using the evolutionary mating algorithm for optimizing the user comfort and energy consumption in smart building
Published 2023“…EMA belongs to the evolutionary computation group of nature-inspired metaheuristic algorithms and offers a promising solution. A comparative analysis is conducted with other well-known algorithms such as Particle Swarm Optimization (PSO), Differential Evolution (DE), Ant Colony Optimization (ACO), Biogeography-Based Optimization (BBO), Teaching-Learning Based Optimization (TLBO), and Beluga Whale Optimization (BWO). …”
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6
Dealing with Routing Hole Problem in Multi-hop Hierarchical Routing Protocol in Wireless Sensor Network
Published 2019“…In the proposed work, the focused problem is how to reduce the communication energy consumption and to avoid the routing hole problem by optimized routing algorithms. First, a routing hole detection algorithm is proposed prior to designing the routing protocol which decreases about 30 percent energy consumption rate, detection time and detection overhead. …”
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7
A secure trust aware ACO-Based WSN routing protocol for IoT
Published 2022“…The performance of the proposed routing algorithm is demonstrated through MATLAB. Based on the proposed system, to find the secure and optimal path while aiming at providing trust in IoT environment, the average energy consumption is minimized by nearly 50% even as the number of nodes has increased, as compared with the conventional ACO algorithm, a current ant-based routing algorithm for IoT-communication, and a present routing protocol RPL for IoT.…”
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8
Artificial neural controller synthesis for TORCS
Published 2015“…The results showed: (1) DE hybrid FFNN could generate optimal controllers, (2) the proposed fitness function had successfully generated the required car's racing controllers, (3) the proposed minimization algorithm had been successfully minimize the number of RF sensors used, (4) the PDE algorithm could be implemented to generate optimal solutions for car racing controllers, and (5) the combination of components for average car speed and distance between the car and track axis is very important compared to other components. …”
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9
Enhancing Model Selection Based On Penalized Regression Methods And Empirical Mode Decomposition
Published 2021“…Those methods are combined with the first part of the Hilbert–Huang transformation, namely, the empirical mode decomposition (EMD) algorithm. …”
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10
Automatic design, optimization and In-Situ Fabrication of Heterogeneous Swarm Robot bodies using 3-D printing and multi-objective evolutionary algorithms
Published 2012“…In this research, an artificial evolution approach utilizing Single-Objective Evolutionary Algorithm (SOEA) and Multi-Objective Evolutionary Algorithm (MOEA) respectively are investigated in the automatic design and optimization of the morphology of a Six Articulated-Wheeled Robot (SAWR) with climbing ability. …”
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11
An Improved Grasshopper Optimization Algorithm Based Echo State Network for Predicting Faults in Airplane Engines
Published 2020“…This problem is often formulated as a typical optimization problem. Metaheuristic algorithms are known to be excellent tools for solving optimization problems. …”
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An approach of filtering to select IMFs of EEMD in acoustic emission AE sensors for oxidized carbon steel
Published 2019“…Using four datasets, analysis parameters of the Ensemble Empirical Mode Decomposition (EEMD) algorithm has been conducted. …”
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An approach of filtering to select IMFs of EEMD in acoustic emission AE sensors for oxidized carbon steel
Published 2019“…Using four datasets, analysis parameters of the Ensemble Empirical Mode Decomposition (EEMD) algorithm has been conducted. …”
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Smart agriculture: precision farming through sensor-based crop monitoring and control system
Published 2024“…Subsequently, four distinct algorithms are trained with the collected dataset to ascertain the most optimal algorithm for predicting crop growth and harvesting time, resulting in the selection of the Random Forest Regression model, which attains the highest model score of 86%. …”
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An enhance approach of filtering to select adaptive IMFs of EEMD in fiber optic sensor for oxidized carbon steel
Published 2019“…However, receiving desired and eliminating undesired information is yet a significant problem of these methods. Empirical Mode Decomposition (EMD) algorithm shows promising results in comparison to other signal processing methods especially in terms of accuracy. …”
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An enhance approach of filtering to select adaptive IMFs of EEMD in fiber optic sensor for oxidized carbon steel
Published 2019“…However, receiving desired and eliminating undesired information is yet a significant problem of these methods. Empirical Mode Decomposition (EMD) algorithm shows promising results in comparison to other signal processing methods especially in terms of accuracy. …”
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17
Penalized Quantile Regression Methods And Empirical Mode Decomposition For Improving The Accuracy Of The Model Selection
Published 2024“…Therefore, three methods based on a combination of the empirical mode decomposition (EMD) algorithm and penalized quantile regression have been proposed in this study. …”
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18
Performance evaluation of different data aggregation algorithms for different types of sensors in WSN based cluster
Published 2018“…Also CS-RD show acceptable performance which is above 85% for compression ratio which that reflect the energy consumption. The Mode method effect negatively in performance all algorithms, the worst CS-RD with Mode in term of energy consumption closes to 2500uJ. …”
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19
Evolution, design, and future trajectories on bipedal wheel-legged robot: A comprehensive review
Published 2023“…The analysis encompasses optimization techniques, sensor integration, machine learning, and adaptive control methods, evaluating their impact on robot capabilities. …”
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Transient analysis for leak signature identification based on Hilbert Huang transform and integrated kurtosis algorithm for z-notch filter technique
Published 2018“…However, this method has the difficulty in selecting the suitable IMF for the next data post-processing method, which is Hilbert Transform (HT). …”
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