Search Results - (( data classification sensor algorithm ) OR ( evolution optimization _ algorithm ))

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  1. 1
    Class binarization with self-adaptive algorithm to improve human activity recognition

    Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
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  2. 2
    Investigation of the optimal sensor location and classifier for human motion classification

    Investigation of the optimal sensor location and classifier for human motion classification by Anuar, Mohamed, Nur Aqilah, Othman, Hamzah, Ahmad, Mohd Hasnun Ariff, Hassan

    Published 2022
    “…In addition, this study seeks to find the best classification algorithm for human daily activities. The data recorded at these three locations were analysed using several classification algorithms in both Orange software and MATLAB. …”
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  3. 3
    Whale optimization algorithm based on tent chaotic map for feature selection in soft sensors

    Whale optimization algorithm based on tent chaotic map for feature selection in soft sensors by AlRijeb, Mothena Fakhri Shaker, Othman, Mohammad Lutfi, Ishak, Aris, Hassan, Mohd Khair, Albaker, Baraa Munqith

    Published 2025
    “…The soft sensor was designed using several stages, including data collection, preprocessing, clustering, feature selection, and classification. …”
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  4. 4
    Performance comparison of classification algorithms for EEG-based remote epileptic seizure detection in wireless sensor networks

    Performance comparison of classification algorithms for EEG-based remote epileptic seizure detection in wireless sensor networks by Abualsaud, Khalid, Mahmuddin, Massudi, Saleh, Mohammad, Mohamed, Amr

    Published 2014
    “…Identification of epileptic seizure remotely by analyzing the electroencephalography (EEG) signal is very important for scalable sensor-based health systems.Classification is the most important technique for wide-ranging applications to categorize the items according to its features with respect to predefined set of classes.In this paper, we conduct a performance evaluation based on the noiseless and noisy EEG-based epileptic seizure data using various classification algorithms including BayesNet, DecisionTable, IBK, J48/C4.5, and VFI.The reconstructed and noisy EEG data are decomposed with discrete cosine transform into several sub-bands.In addition, some of statistical features are extracted from the wavelet coefficients to represent the whole EEG data inputs into the classifiers.Benchmark on widely used dataset is utilized for automatic epileptic seizure detection including both normal and epileptic EEG datasets.The classification accuracy results confirm that the selected classifiers have greater potentiality to identify the noisy epileptic disorders.…”
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  5. 5
    A refined differential evolution algorithm for improving the performance of optimization process

    A refined differential evolution algorithm for improving the performance of optimization process by A. R., Yusoff, Nafrizuan, Mat Yahya

    Published 2011
    “…Various Artificial Intelligent (AI) algorithms can be applied in solving optimization problems. …”
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  6. 6
    Evaluations of oil palm fresh fruit bunches maturity degree using multiband spectrometer

    Evaluations of oil palm fresh fruit bunches maturity degree using multiband spectrometer by Tuerxun, Adilijiang

    Published 2017
    “…Furthermore, the Lazy-IBK algorithm have been validated to produce the best classifier model, with the machine learning algorithm performance of 65.26%, recall of 65.3%, and 65.4% F-measured as compared to other evaluated machine learning classifier algorithms proposed within the WEKA data mining algorithm. …”
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  7. 7
    Smart phone sensor data: Comparative analysis of various classification methods for task of human activity recognition

    Smart phone sensor data: Comparative analysis of various classification methods for task of human activity recognition by Tanveer Abbas Gadehi, Faheem Yar Khuhawar, Ahmed Memon, Kashif Nisar

    Published 2018
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  8. 8
    Combining data mining algorithm and object-based image analysis for detailed urban mapping of hyperspectral images

    Combining data mining algorithm and object-based image analysis for detailed urban mapping of hyperspectral images by Hamedianfar, Alireza, Mohd Shafri, Helmi Zulhaidi, Mansor, Shattri, Ahmad, Noordin

    Published 2014
    “…The high accuracy of object-based classification can be linked to the knowledge discovery produced by the DM algorithm. …”
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  9. 9
    EMG Signals Classification on Human Activity Recognition using Machine Learning Algorithm

    EMG Signals Classification on Human Activity Recognition using Machine Learning Algorithm by Nurhanim, K., Elamvazuthi, I., Izhar, L.I., Capi, G., Su, S.

    Published 2021
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  10. 10
    Two level Differential Evolution algorithms for ARMA parameters estimatio

    Two level Differential Evolution algorithms for ARMA parameters estimatio by Salami, Momoh Jimoh Emiyoka, Tijani, Ismaila, Aibinu, Abiodun Musa

    Published 2013
    “…The problem of determining simultaneously the model order and coefficient of an Autoregressive Moving Average (ARMA) model is examined in this paper. An Evolutionary Algorithm (EA) comprising two-level Differential Evolution (DE) optimization scheme is proposed. …”
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  11. 11
    Comparison between Lamarckian Evolution and Baldwin Evolution of neural network

    Comparison between Lamarckian Evolution and Baldwin Evolution of neural network by Taha, Imad, Inazy, Qabas

    Published 2006
    “…We presented hybrid genetic algorithm for optimizing weights as well as the topology of artificial neural networks, by introducing the concepts of Lamarckian and Baldwin evolution effects. …”
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  12. 12
    The application of neural network data mining algorithm into mixed pixel classification in geographic information system environment

    The application of neural network data mining algorithm into mixed pixel classification in geographic information system environment by Nanna Suryana, Herman

    Published 2007
    “…Region growing segmentation and radial basis function algorithms are considered a powerful tool to minimize the mixed pixel classification error.…”
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  13. 13
    Integrated approach using data mining-based decision tree and object-based image analysis for high-resolution urban mapping of WorldView-2 satellite sensor data

    Integrated approach using data mining-based decision tree and object-based image analysis for high-resolution urban mapping of WorldView-2 satellite sensor data by Hamedianfar, Alireza, Mohd Shafri, Helmi Zulhaidi

    Published 2016
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  14. 14
    Broadening selection competitive constraint handling algorithm for faster convergence

    Broadening selection competitive constraint handling algorithm for faster convergence by Shaikh, T.A., Hussain, S.S., Tanweer, M.R., Hashmani, M.A.

    Published 2020
    “…In this study, the BSCCH algorithm has been coupled with Differential Evolution algorithm as a proof of concept because it is found to be an efficient algorithm in the literature for constrained optimization problems. …”
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  15. 15
    A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising

    A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising by Al-Dabbagh, Mohanad Dawood, Al-Dabbagh, Rawaa Dawoud, Raja Abdullah, Raja Syamsul Azmir, Hashim, Fazirulhisyam

    Published 2015
    “…The main intention of this study was to investigate the development of a new optimization technique based on the differential evolution (DE) algorithm, for the purpose of linear frequency modulation radar signal de-noising. …”
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  16. 16
    Performance comparison of differential evolution and particle swarm optimization in constrained optimization

    Performance comparison of differential evolution and particle swarm optimization in constrained optimization by Iwan, Mahmud, Akmeliawati, Rini, Faisal, Tarig, Al-Assadi, Hayder M.A.A.

    Published 2012
    “…Particle swarm optimization (PSO) and differential evolution (DE) are among the well-known modern optimization algorithms. …”
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  17. 17
    Crossover-first differential evolution for improved global optimization in non-uniform search landscapes

    Crossover-first differential evolution for improved global optimization in non-uniform search landscapes by Teo, Jason Tze Wi, Mohd Hanafi Ahmad Hijazi, Hui, Keng Lau, Salmah Fattah, Aslina Baharum

    Published 2015
    “…The differential evolution (DE) algorithm is currently one of the most widely used evolutionary-based optimizers for global optimization due to its simplicity, robustness and efficiency. …”
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  18. 18
    Reliably optimal PMU placement using disparity evolution-based genetic algorithm

    Reliably optimal PMU placement using disparity evolution-based genetic algorithm by Matsukawa, Yoshiaki, Othman, Mohammad Lutfi, Watanabe, Masayuki, Mitani, Yasunori

    Published 2017
    “…In this paper, Disparity Evolution-type Genetic Algorithm (DEGA) based on disparity theory of evolution is applied. …”
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  19. 19
    Differential evolution optimization algorithm based on generation systems reliability assessment integrated with wind energy

    Differential evolution optimization algorithm based on generation systems reliability assessment integrated with wind energy by Kadhem, Athraa Ali, Abdul Wahab, Noor Izzri, Abdalla, Ahmed N.

    Published 2019
    “…This stuffy proposed a novel optimization method labeled the "Differential Evolution Optimization Algorithm" (DEOA) to assess the reliability of power generation systems (PGS). …”
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  20. 20
    A review: radar-based fall detection sensor / Hidayatusherlina Razali ... [et al.]

    A review: radar-based fall detection sensor / Hidayatusherlina Razali ... [et al.] by Razali, Hidayatusherlina, Abd. Rashid, Nur Emileen, Nasarudin, Muhammad Nazrin Farhan, Ismail, Nor Najwa, Ismail Khan, Zuhani, Enche Ab Rahim, Siti Amalina

    Published 2024
    “…Fall recognition involves steps: sensor type, data pre-processing, and data classification. …”
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