Search Results - (( data classification using algorithm ) OR ( variable detection sensor algorithm ))

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  1. 1
    Gas Identi cation by Using a Cluster-k-Nearest-Neighbor

    Gas Identi cation by Using a Cluster-k-Nearest-Neighbor by Brahim Belhaouari, samir

    Published 2009
    “…We find 98.7% of accuracy in the classification of 6 different types of Gas by using K-means cluster algorithm and we find almost the same by using the new clustering algorithm.…”
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  2. 2
    Evaluation of multiple In Situ and remote sensing system for early detection of Ganoderma boninense infected oil palm

    Evaluation of multiple In Situ and remote sensing system for early detection of Ganoderma boninense infected oil palm by Ahmadi, Seyedeh Parisa

    Published 2018
    “…In the next phase, the SVM classifier was trained to achieve the best classification using training data and test data integrated with selected features. …”
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  3. 3
    Observer-based fault detection with fuzzy variable gains and its application to industrial servo system

    Observer-based fault detection with fuzzy variable gains and its application to industrial servo system by Eissa, Magdy Abdullah, Sali, Aduwati, Hassan, Mohd Khair, Bassiuny, A. M., Darwish, Rania R.

    Published 2020
    “…Also, a scoring algorithm has been implemented, to evaluate the classification ability of the algorithm and the early fault detection ability. …”
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  4. 4
    Deforestation detection in Kinabalu Area, Sabah, Malaysia by using multi-sensor remote sensing approach

    Deforestation detection in Kinabalu Area, Sabah, Malaysia by using multi-sensor remote sensing approach by Phua, Mui How, Tsuyuki, Satoshi

    Published 2004
    “…This paper examines use of multi-sensor remote sensing approach for deforestation detection in the tropics. …”
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  5. 5
    Algorithm enhancement for host-based intrusion detection system using discriminant analysis

    Algorithm enhancement for host-based intrusion detection system using discriminant analysis by Dahlan, Dahliyusmanto

    Published 2004
    “…Misuse detection algorithms model know attack behavior. They compare sensor data to attack patterns learned from the training data. …”
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  6. 6
    A study on advanced statistical analysis for network anomaly detection

    A study on advanced statistical analysis for network anomaly detection by Ngadi, Md. Asri, Idris, Mohd. Yazid, Abdullah, Abd. Hanan

    Published 2005
    “…Misuse detection algorithms model know attack behavior. They compare sensor data to attack patterns learned from the training data. …”
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    Monograph
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  7. 7
    Cluster head selection using fuzzy logic and chaotic based genetic algorithm in wireless sensor network

    Cluster head selection using fuzzy logic and chaotic based genetic algorithm in wireless sensor network by Karimi, Abbas, Abedini, S. M., Zarafshan, Faraneh, Syed Mohamed, Syed Abdul Rahman Al-Haddad

    Published 2013
    “…Wireless sensor networks (WSNs) are composed of hundreds or thousands of sensor nodes in order to detect and transmit information from its surrounding environment. …”
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  8. 8
    Modelling and analysis of sensor fault tolerant control using behavioral approach to systems theory

    Modelling and analysis of sensor fault tolerant control using behavioral approach to systems theory by Ng, Peng Hong

    Published 2015
    “…State observers are then implemented as the fault detection method in which the discrepancies between the measured values by the sensors and the values of the model are expressed as residuals. …”
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  9. 9
    DESIGN OF SMART TRAFFIC LIGHT SYSTEM BASED ON INTERNET OF THINGS

    DESIGN OF SMART TRAFFIC LIGHT SYSTEM BASED ON INTERNET OF THINGS by MUHAMMAD AMIR AFIQ, MOHAMED

    Published 2018
    “…Density of the traffic is calculated by the algorithm that have various variables. This project will use Arduino as it microcontroller and the ultrasonic is used to detect the congestion. …”
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    Final Year Project Report / IMRAD
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  10. 10
    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
    “…In cluster generating process, the developed BBSI algorithm was used to select the best band combination for generating cluster by using Iterative self- Organizing Data Analysis (ISODATA) technique. …”
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  11. 11
    Multi-sensor fusion and deep learning framework for automatic human activity detection and health monitoring using motion sensor data / Henry Friday Nweke

    Multi-sensor fusion and deep learning framework for automatic human activity detection and health monitoring using motion sensor data / Henry Friday Nweke by Henry Friday , Nweke

    Published 2019
    “…This is further worsen by the use of single sensors modality and machine learning algorithms. …”
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  12. 12
    Case Slicing Technique for Feature Selection

    Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

    Published 2004
    “…Since the 1960s, many algorithms for data classification have been proposed. …”
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  13. 13
    Oil palm female inflorescences anthesis stages identification using selected emissivities through thermal imaging and Machine Learning

    Oil palm female inflorescences anthesis stages identification using selected emissivities through thermal imaging and Machine Learning by Yousefidashliboroun, Mamehgol

    Published 2022
    “…Different ML algorithms such as Random Forest (RF), k Nearest Neighbor (kNN), Support Vector Machine (SVM), Artificial Neural Network (ANN) as well as an ensemble method are used on data extracted from thermal images collected during infield oil palms pollination stages monitoring. …”
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  14. 14
    Dengue classification system using clonal selection algorithm / Karimah Mohd

    Dengue classification system using clonal selection algorithm / Karimah Mohd by Mohd, Karimah

    Published 2012
    “…Some of the dengue data are used to test the dengue classification system to produce the classification accuracy. …”
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  15. 15
    Enhancing Classification Algorithms with Metaheuristic Technique

    Enhancing Classification Algorithms with Metaheuristic Technique by Cokro, Nurwinto, Tri Basuki, Kurniawan, Misinem, ., Tata, Sutabri, Yesi Novaria, Kunang

    Published 2024
    “…Implementing this process uses classification algorithms such asNaïve Bayes, Support Vector Machine,and Random Forest. …”
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  16. 16
    Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd

    Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd by Nur Farahaina, Idris

    Published 2022
    “…Classification is a data mining technique used to classify varied data types according to a specific criterion. …”
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  17. 17
    Attribute related methods for improvement of ID3 Algorithm in classification of data: A review

    Attribute related methods for improvement of ID3 Algorithm in classification of data: A review by Nur Farahaina, Idris, Mohd Arfian, Ismail

    Published 2020
    “…Nevertheless, there are some limitations in ID3 algorithm that can affect the performance in the classification of data. …”
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  18. 18
    Faulty sensor detection mechanism using multi-variate sensors in IoT

    Faulty sensor detection mechanism using multi-variate sensors in IoT by Al-Atrakchii, Khaldoon Ammar

    Published 2019
    “…Because of this, we proposed two methods for Faulty Sensor Detection and Identification mechanism based on multi-variate sensors for Smart Parking System and smart agriculture. …”
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  19. 19
    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition

    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

    Published 2017
    “…Phase 1 is mainly to evaluate the performance of clustering algorithm (K-Means and FCM). Phase 2 is to study the performance of proposed integration system which using the data clustered to be used as train data for Naïve Bayes classifier. …”
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  20. 20
    Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model

    Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model by Sulaiman, Md. Nasir, Mohamed, Raihani, Mustapha, Norwati, Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…Expectation maximization (EM) is one of the representatives clustering algorithms which have broadly applied in solving classification problems by improving the density of data using the probability density function. …”
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