Search Results - (( data identification using algorithm ) OR ( variable detection using algorithm ))

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  1. 1

    Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification by Abd Samad, Md Fahmi

    Published 2011
    “…A deterministic mutation-based algorithm is introduced to overcome this problem. Identification studies using NARX (Nonlinear AutoRegressive with eXogenous input) models employing simulated systems and real plant data are used to demonstrate that the algorithm is able to detect significant variables and terms faster and to select a simpler model structure than other well-known EC methods.…”
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    Article
  2. 2

    Development of fault detection, diagnosis and control system identification using multivariate statistical process control (MSPC) by Ibrahim, Kamarul 'Asri, Ahmad, Arshad, Ali, Mohamad Wijayanuddin, Mak, Weng Yee

    Published 2006
    “…In this research work, an FDD algorithm is developed using MSPC and correlation coefficients between process variables. …”
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    Monograph
  3. 3

    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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    Article
  4. 4

    Damage visualization based on frequency shift of single-mode ultrasound-guided wavefield by Shahrim, Muhamad Azim, Harmin, Mohammad Yazdi, Romli, Fairuz Izzuddin, Chia, Chen Ciang, Jung-Ryul, Lee

    Published 2022
    “…Overall, the results show that frequency analysis can detect the damage four times faster and the algorithm uses two-dimensional calculation instead of conventional three-dimensional of VTWAM method.…”
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    Article
  5. 5

    Robust Estimation Methods And Outlier Detection In Mediation Models by Fitrianto, Anwar

    Published 2010
    “…The Ordinary Least Squares (OLS) method is often use to estimate the parameters of the mediation model. …”
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    Thesis
  6. 6

    Modelling of cupping suction system based on system identification method by Suresh, Kavindran, Ghazali, M. R., Ahmad, M. A.

    Published 2022
    “…The detection of cupped suction system plants using a standard model based on a modified Sine Cosine Algorithm (mSCA) is presented in this research. …”
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    Conference or Workshop Item
  7. 7

    Modeling of cupping suction system based on system identification method by Kavindran, Suresh

    Published 2022
    “…The input and output data were used to create this modeling output variable of the cupping suction system is detected by connecting a differential pressure sensor to the cup, while the input variable is determined by the speed of the pump applied in various locations. …”
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    Undergraduates Project Papers
  8. 8

    Sentiment-analysis to detect early depressive symptom in Bangla language from social media: a review study by Hassan, Md. Hasibul, Kamaruddin, Azrina, Azmi Murad, Masrah Azrifah

    Published 2021
    “…WHO reported that the numbers on existing mental health disorders are a troubling phenomenon. The identification of mental health can be detected using several data domains such as: sensors, text, structured data, and multi-modal system use. …”
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    Article
  9. 9

    All-in-1 adverse drug reaction reporting system / Long Chiau Ming … [et al.] by Chiau Ming, Long, Karuppannan, Mahmathi, Abdul Wahab, Izyan, Abd Wahab, Mohd Shahezwan, Zulkifly, Hanis Hanum

    Published 2014
    “…Values obtained from this algorithm are used in peer reviews to verify the validity of reporter’s conclusion regarding ADRs. …”
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    Book Section
  10. 10
  11. 11

    An improved machine learning model of massive Floating Car Data (FCD) based on Fuzzy-MDL and LSTM-C for traffic speed estimation and prediction by Ahanin, Fatemeh

    Published 2023
    “…When there are missing data in the dataset, TSP may use TSE for estimation of missing data and then performs prediction. …”
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    Thesis
  12. 12

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

    Published 2019
    “…The accuracy of the algorithm for data correlation may be changing depending on the application that wants to detect the faulty sensor in the system and according to how many data that income to the microcontroller per minute and how many data should take to calculate the correlation coefficient. …”
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    Thesis
  13. 13

    Identification of debris flow initiation zones using topographic model and airborne laser scanning data by Lay, Usman Salihu, Pradhan, Biswajeet

    Published 2017
    “…MARSpline multivariate data mining predictive approach was implemented using morphometric indices and topographical derived parameter as independent variables. …”
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    Conference or Workshop Item
  14. 14

    Effect of mixing time and frequency-domain objectives in detecting problematic vibration on unmanned aerial vehicles via barnicle mating optimization by Fatimah, Dg Jamil, Mohammad Fadhil, Abas, Mohd Sharif, Zakaria, Norhafidzah, Mohd Saad, Mohd Hisyam, Ariff

    Published 2024
    “…The goal of this work is to demonstrate the impact of integrating frequency-domain and time-domain analysis as time-domain and frequency-domain objectives. a suggested fitness function that combines the time and frequency domains with a mixing variable. Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and detection time are used to test and assess the fitness function with the Barnicle Mating optimization (BMO) Algorithm optimization technique. …”
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    Conference or Workshop Item
  15. 15

    Tree species and aboveground biomass estimation using machine learning, hyperspectral and LiDAR data / Nik Ahmad Faris Nik Effendi by Nik Effendi, Nik Ahmad Faris

    Published 2022
    “…Besides, Artificial Neural Network (ANN) and Random Forest (RF) algorithm was used to predicted the AGB using different combination of variables. …”
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    Thesis
  16. 16

    Feature Ranking Techniques For 3D ATS Drug Molecular Structure Identification by Saw, Yee Ching

    Published 2018
    “…The proposed feature selection approach has a simple algorithmic framework and makes use of the existing feature selection techniques to cater different variety of data issues, namely Ensemble Filter-Embedded Feature Ranking Approach (FEFR). …”
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    Thesis
  17. 17

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

    Published 2022
    “…This research studies different Machine Learning (ML) classification and ensemble techniques for the assessment of the four pollination stages consist of pre-anthesis I, pre-anthesis II, pre-anthesis III, and anthesis using thermal imaging. 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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    Thesis
  18. 18

    Non-fungible token based smart manufacturing to scale Industry 4.0 by using augmented reality, deep learning and industrial Internet of Things by Ahmed Khan, Fazeel, Ibrahim, Adamu Abubakar

    Published 2023
    “…The predictive maintenance is a major scenario in which early equipment failure detection using deep learning model on acquired data from IIoT devices has major potential for it. …”
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    Article
  19. 19

    Optimization of Lipase Catalysed Synthesis of Sugar Alcohol Esters Using Taguchi Method and Neural Network Analysis by Adnani, Seyedeh Atena

    Published 2011
    “…In this system,similar insolvent system, three methods including one variable at a time, Taguchi method and ANN were used for optimization and prediction of percentage of conversion. …”
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    Thesis
  20. 20

    Comparing seabed roughness result from QPS fledermaus software, benthic trrain modeler [BTM] and developed model derived FRM slope variability algorithm for hard coral reef detecti... by Mohd Sayud, Nur Asikin

    Published 2018
    “…In this study, several models has been created which are from QPS Fledermaus model, BTM model and Slope Variability model. Slope variability model is an algorithm that is being used for detecting terrain roughness. …”
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    Thesis