Search Results - (( developing systematic sensor algorithm ) OR ( java implementation phase algorithm ))

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  1. 1

    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

    Published 2019
    “…All the algorithm for the engine has been developed by using Java script language. …”
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    Thesis
  2. 2

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

    Published 2015
    “…Finally, the algorithm to obtain a general FTCS framework is developed to provide compensation of the sensor faults through the introduction of a new control law unto the existing nominal one. …”
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  3. 3

    Optimal route checking using genetic algorithm for UiTM's bus services / Tengku Salman Fathi Tengku Jaafar by Tengku Jaafar, Tengku Salman Fathi

    Published 2006
    “…Although from human logical thinking, the route can be generated easily but the calculation of checking the route whether it is optimal route or not is difficult and will take long time to be implemented. This research study with the development of the Optimal Route Checking Using Genetic Algorithm system should solve this scenario. …”
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  4. 4

    Simulation and Design of an Intelligent Mobile Robot for Fire Fighting by Chor, Keong Seng

    Published 2003
    “…A method of Path Recognition Algorithms (PRA) providing robots the autonomous ability to judge purpose of action likes human base on the input sensors from the environment. …”
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  5. 5

    Conventional and intelligent models for detection and prediction of fluid loss events during drilling operations: A comprehensive review by Krishna, S., Ridha, S., Vasant, P., Ilyas, S.U., Sophian, A.

    Published 2020
    “…This study aims to provide a systematic review of the published literature from the last forty years on the developed conventional and intelligent models for detection and prediction of fluid loss events and emphasizes on increasing AI involvement for precise results. …”
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  6. 6

    Conventional and intelligent models for detection and prediction of fluid loss events during drilling operations: a comprehensive review by Krishna, Shwetank, Ridha, Syahrir, Vasant, Pandian M., Ilyas, Suhaib Umer, Sophian, Ali

    Published 2020
    “…This study aims to provide a systematic review of the published literature from the last forty years on the developed conventional and intelligent models for detection and prediction of fluid loss events and emphasizes on increasing AI involvement for precise results.…”
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  7. 7

    Remote sensing technologies for unlocking new groundwater insights: a comprehensive review by Ibrahim, Abba, Wayayok, Aimrun, Mohd Shafri, Helmi Zulhaidi, Toridi, Noorellimia Mat

    Published 2024
    “…While significant progress has been made, ongoing constraints include coarse spatial and temporal resolutions limiting basin-scale utility, propagation of uncertainties from sensor calibrations and data merging, and a lack of systematic validation impeding operational readiness. …”
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  8. 8

    An approach to enhance the structural operational deflection shape under random ambient excitation through mode shape expansion / Muhamad Azhan Anuar by Anuar, Muhamad Azhan

    Published 2021
    “…The implementation of this study involves systematic methodology; (i) Operational Modal Analysis (OMA) as an experimental method – The experimental data were collected and processed in order to decompose the signal into modal components using different algorithms to obtain reliable experimental modal data (ii) Finite Element (FE) as numerical technique – FE model was developed, and normal modes results were obtained. …”
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  9. 9

    Monitoring water quality in Pusu river using Internet of Things (IoT) and Machine Learning (ML) by Kabbashi, Nassereldeen Ahmed, Hasan, Tahsin Fuad, Alam, Md Zahangir, Saleh, Tanveer, Hassan Abdalla Hashim, Aisha

    Published 2024
    “…In the subsequent iteration, the dataset was expanded to include a dissolved oxygen sensor in addition to the initial four sensors. The data collection process for turbidity and other water quality parameters involved more than just 879 data points, the data collection process was comprehensive, and the dataset was validated and analyzed with seasonal changes in mind, systematic approach ensured that the water quality parameters data collected were reliable, accurate, and actionable for monitoring water quality in the river. …”
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