Search Results - (( using evolution sensor algorithm ) OR ( quality classifications using 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
    Recognizing complex human activities using hybrid feature selections based on an accelerometer sensor

    Recognizing complex human activities using hybrid feature selections based on an accelerometer sensor by Zainudin, Muhammad Noorazlan Shah, Sulaiman, Md Nasir, Mustapha, Norwati, Perumal, Thinagaran, Mohamed, Raihani

    Published 2017
    “…In order to tackle this issue, the hybrid feature selection using Relief-f and differential evolution is proposed. …”
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  3. 3
    Evolution strategy for collaborative beamforming in wireless sensor networks

    Evolution strategy for collaborative beamforming in wireless sensor networks by Wong, Chen How

    Published 2013
    “…An iterative algorithm using evolution strategy (ES) is proposed to achieve phase alignment at the intended location in static channels, which require one-bit feedback from the receiver destination. …”
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  4. 4
    A centralized localization algorithm for prolonging the lifetime of wireless sensor networks using particle swarm optimization in the existence of obstacles

    A centralized localization algorithm for prolonging the lifetime of wireless sensor networks using particle swarm optimization in the existence of obstacles by Abdulhasan Al-Jarah, Ali Husam

    Published 2017
    “…These wireless sensor nodes has been used in many applications at many areas. …”
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  5. 5
    Classification model for water quality using machine learning techniques

    Classification model for water quality using machine learning techniques by Azilawati, Rozaimee, Azrul Amri, Jamal, Azwa, Abdul Aziz

    Published 2015
    “…There is a need to resolve this problem for us to get good water that can be used for domestic purposes. This article proposes a suitable classification model for classifying water quality based on the machine learning algorithms. …”
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  6. 6
    Comparison of Logistic Regression, Random Forest, SVM, KNN Algorithm for Water Quality Classification Based on Contaminant Parameters

    Comparison of Logistic Regression, Random Forest, SVM, KNN Algorithm for Water Quality Classification Based on Contaminant Parameters by Teguh, Sutanto, Muhammad Rafli, Aditya, Haldi, Budiman, M.Rezqy, Noor Ridha, Usman, Syapotro, Noor, Azijah

    Published 2024
    “…This finding emphasizes that Stacking with Gradient Boosting provides much better performance in water quality classification compared to other models. This research provides new insights into the application of machine learning algorithms for water quality management as well as guidance for optimal algorithm selection.…”
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  7. 7
    Cluster head selection optimization in wireless sensor network via genetic-based evolutionary algorithm

    Cluster head selection optimization in wireless sensor network via genetic-based evolutionary algorithm by Vincent Chung, Hamzarul Alif Hamzah, Norah Tuah, Kit, Guan Lim, Min, Keng Tan, Kenneth Tze Kin Teo

    Published 2020
    “…Existing approaches for this optimization problem have several drawbacks, including non-adaptive network configuration that may cause premature death of sensor nodes. 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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  8. 8
    Evoluation strategy for collaborative beamforming in wireless sensor networks

    Evoluation strategy for collaborative beamforming in wireless sensor networks by Wong, Chen How

    Published 2013
    “…An iterative algorithm using evolution strategy (ES) is proposed to achieve phase alignment at the intended location in static channels, which require one-bit feedback from the receiver destination. …”
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  9. 9
    Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad

    Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

    Published 2018
    “…Experimental results show that the developed methods and model are able to classify the Harumanis quality with accuracy of 79% using fuzzy classification based on shape and size.…”
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  10. 10
    Real-time power quality disturbance classification using convolutional neural networks

    Real-time power quality disturbance classification using convolutional neural networks by Husodo, Budi Yanto, Dalimi, Rinaldy, Ihsanto, Eko, Gunawan, Teddy Surya

    Published 2020
    “…Experimental results showed that the proposed algorithm produced a good result with the classification accuracy of 97.52% trained using 100 epochs. …”
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  11. 11
    Vision Based Calibration and Localization Technique for Video Sensor Networks

    Vision Based Calibration and Localization Technique for Video Sensor Networks by Mohamed Sharif, Sharif Amar Mohamed Sharif

    Published 2009
    “…The recent evolutions in embedded systems have now made the video sensor networks a reality. …”
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  12. 12
    A novelty classification model for varied agarwood oil quality using the K-Nearest Neighbor algorithm / Aqib Fawwaz Mohd Amidon … [et al.]

    A novelty classification model for varied agarwood oil quality using the K-Nearest Neighbor algorithm / Aqib Fawwaz Mohd Amidon … [et al.] by Mohd Amidon, Aqib Fawwaz, Mohd Huzir, Siti Mariatul Hazwa, Mohd Yusoff, Zakiah, Ismail, Nurlaila, Taib, Mohd Nasir

    Published 2022
    “…Their services are used to sniff and evaluate each agarwood to determine if it is of high quality or not. …”
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  13. 13
    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms

    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

    Published 2005
    “…The comparison showed that, the accuracy of the unsupervised classification map with value of 88.4% that was generated by using the cluster labelling algorithm was slightly more than the maximum-likelihood supervised classification map with value of 87.5%. …”
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  14. 14
    An adaptive ant colony optimization algorithm for rule-based classification

    An adaptive ant colony optimization algorithm for rule-based classification by Al-Behadili, Hayder Naser Khraibet

    Published 2020
    “…Ant-Miner is a variant of ant colony optimisation and a prominent intelligent algorithm widely use in rules-based classification. …”
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  15. 15
    Development of Sense and Avoid system based on multi sensor integration for unmanned vehicle system

    Development of Sense and Avoid system based on multi sensor integration for unmanned vehicle system by Legowo, Ari, Ramli, M. Faiz, Syafiq Shamsudin, Syariful

    Published 2016
    “…Proper logics or algorithm related to the fusion of output from each sensor will also be studied.The combination of Extended Kalman Filter (EKF) and Differential Evolution(DE) method is used for the purpose of development of detection and tracking system which considered to be the main challenges in SAA system development. …”
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  16. 16
    Agarwood oil quality classification using one versus all strategies in multiclass on SVM model / Aqib Fawwaz Mohd Amidon … [et al.]

    Agarwood oil quality classification using one versus all strategies in multiclass on SVM model / Aqib Fawwaz Mohd Amidon … [et al.] by Mohd Amidon, Aqib Fawwaz, Mahabob, Noratikah Zawani, Ismail, Nurlaila, Mohd Yusoff, Zakiah, Taib, Mohd Nasir

    Published 2021
    “…So, the output was the classification of quality between low, medium low, medium high or high quality while the input was the abundances (%) of compounds. …”
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  17. 17
    Hybrib NSGA-II optimization for improving the three-term BP network for multiclass classification problems

    Hybrib NSGA-II optimization for improving the three-term BP network for multiclass classification problems by Ibrahim, Ashraf Osman, Shamsuddin, Siti Mariyam, Qasem, Sultan Noman

    Published 2015
    “…This paper presents a hybrid of the multiobjective evolutionary algorithm to gain a better accuracy of the fi nal solutions.The aim of using the hybrid algorithm is to improve the multiobjective evolutionary algorithm performance in terms of the enhancement of all the individuals in the population and increase the quality of the Pareto optimal solutions.The multiobjective evolutionary algorithm used in this study is a nondominated sorting genetic algorithm-II (NSGA-II) together with its hybrid, the backpropagation algorithm (BP), which is used as a local search algorithm to optimize the accuracy and complexity of the three-term backpropagation (TBP) network. …”
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  18. 18
    Hybrid NSGA-II Optimization for Improving the Three-Term BP Network for Multiclass Classification Problems

    Hybrid NSGA-II Optimization for Improving the Three-Term BP Network for Multiclass Classification Problems by Ibrahim, Ashraf Osman, Shamsuddin, Siti Mariyam, Qasem, Sultan Noman

    Published 2015
    “…The aim of using the hybrid algorithm is to improve the multiobjective evolutionary algorithm performance in terms of the enhancement of all the individuals in the population and increase the quality of the Pareto optimal solutions. …”
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  19. 19
    Classification of hand gestures from EMG signals / Diaa Albitar

    Classification of hand gestures from EMG signals / Diaa Albitar by Albitar, Diaa

    Published 2022
    “…This study is to develop classification model to classify six hand gestures using Artificial Intelligent algorithm. …”
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  20. 20
    Intent-IQ: customer’s reviews intent recognition using random forest algorithm

    Intent-IQ: customer’s reviews intent recognition using random forest algorithm by Mazlan, Nur Farahnisrin, Ibrahim Teo, Noor Hasimah

    Published 2025
    “…Two machine learning model is chosen to build the classification models which are Random Forest (RF) algorithm and Multinomial Naïve Bayes (MNB) algorithm. …”
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