Search Results - (( using optimization sensor algorithm ) OR ( data validation using algorithm ))
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Real-Time State of Charge Estimation of Lithium-Ion Batteries Using Optimized Random Forest Regression Algorithm
Published 2024“…The experimental results demonstrate that the DSA optimized RFR algorithm achieves RMSE of 0.382% in the HPPC test using LiNMC battery. …”
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Differential Search Optimized Random Forest Regression Algorithm for State of Charge Estimation in Electric Vehicle Batteries
Published 2023Conference Paper -
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Multi-objective optimization for integrated task scheduling and load balancing in fog computing for IoT applications
Published 2025“…By using a task scheduling and offloading method, the FOCS algorithm arranges data according to size and sends it to the appropriate fog nodes. …”
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Energy-efficient data transmission with clustering and compressive sensing in wireless sensor networks / Mukil Alagirisamy
Published 2020“…The simulation results of clustering algorithms, INACS and Perceptron framework are validated using various data analysis methods. …”
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A novel peak detection algorithm using particle swarm optimization for chew count estimation of a contactless chewing detection
Published 2022“…The proposed approach is validated using data from a larger number of participants, 20, and different food types, eight. …”
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Incremental interval type-2 fuzzy clustering of data streams using single pass method
Published 2020“…Data Streams create new challenges for fuzzy clustering algorithms, specifically Interval Type-2 Fuzzy C-Means (IT2FCM). …”
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A novel peak detection algorithm using particle swarm optimization for chew count estimation of a contactless chewing detection
Published 2022“…The proposed approach is validated using data from a larger number of participants, 20, and different food types, eight. …”
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Integrated approach using data mining-based decision tree and object-based image analysis for high-resolution urban mapping of WorldView-2 satellite sensor data
Published 2016“…Many features were explored by using a DM algorithm, which created the classification rules as a decision tree (DT) structure from the first study area. …”
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Simultaneous measurement of multiple soil properties through proximal sensor data fusion: a case study
Published 2019“…After choosing the optimal sensor combination for each soil property, the predictive capability was compared using different data mining algorithms, including support vector machines (SVM), random forest (RF), multivariate adaptive regression splines (MARS), and regression trees (CART). …”
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An efficient network mobility management for a 6LoWPAN mobile network in hospital environments
Published 2017“…Finally, by using the selective optimal algorithm, the MR energy consumption in NEMO-HWSN is minimized by approximately 15.5%. …”
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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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Brain source localization using reduced EEG sensors
Published 2018“…This research work discusses and implements the brain source localization for real-time and synthetically generated EEG dataset with reduced number of sensors. For this, various optimization algorithms are used which include Bayesian framework-based multiple sparse priors (MSP), classical low-resolution brain electromagnetic tomography (LORETA), beamformer and minimum norm estimation (MNE). …”
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Brain source localization using reduced EEG sensors
Published 2018“…This research work discusses and implements the brain source localization for real-time and synthetically generated EEG dataset with reduced number of sensors. For this, various optimization algorithms are used which include Bayesian framework-based multiple sparse priors (MSP), classical low-resolution brain electromagnetic tomography (LORETA), beamformer and minimum norm estimation (MNE). …”
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An Electrocardiogram-Based Authentication Protocol In Wireless Body Area Network
Published 2016“…While the result of FFT algorithm summarizes that the number of the common FFT peak location index for sensors on the same subject is significantly higher compared to the number of common feature for sensors on different subjects.…”
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15
An autonomous wheelchair speed control using fuzzy logic controller / Muhammad Ashraf Mohamad Ghazali
Published 2025“…Future enhancements could involve integrating additional sensors and refining the control algorithm for enhanced performance in real-world applications.…”
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Fuzzy control algorithm for educational light tracking system
Published 2010“…The fuzzy control algorithm for light tracking system is implemented using a webcamera as a vision sensor, two PC sound cards as output signal controller, and two DC motors as a pan-tilt driver mechanism. …”
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Photogrammetric low-cost unmanned aerial vehicle for pothole detection mapping / Shahrul Nizan Abd Mukti
Published 2022“…The study set four main objectives to achieve its aim: (1) To analyse RGB and multispectral sensor calibration, (2) To evaluate the optimal flight parameters for pothole modelling production using RGB imagery, (3) To investigate various classifier algorithms and band combinations for pothole region areas using multispectral imagery and (4) To validate geometric information from the extracted pothole. …”
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Enhancing Accuracy in WBANs Through Optimal Sensor Positioning and Signal Processing: A Systematic Methodology
Published 2025“…This method not only enhances the dependability of health monitoring systems but also validates their ability to be scaled and their effectiveness in various medical uses. …”
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Artificial neural network (ANN) as post-processing stage for chemically selective field effect transistor (CHEMFET) sensor selectivity based-on ion concentration / Nurhakimah Abd A...
Published 2016“…In this study, the sensor voltage response was acquired to act as input data while sample concentrations which set from 10"6 to 10"1 mol/L was used as target for training data. …”
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Bayesian Network Classifiers for Damage Detection in Engineering Material
Published 2007“…To validate the classi¯ers and the proposed algorithm, two data sets were used, the ¯rst set represents voltage amplitudes of Lamb-waves produced and col- lected by sensors and actuators mounted on the surface of laminates contain di®erent arti¯cial damages. …”
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