Search Results - (( data normalization based algorithm ) OR ( parameter detection path algorithm ))

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    Path Planning and Control of Mobile Robot in Road Environments using Sensor Fusion and Active Force Control by Ali, Mohammed A. H., Mailah, Musa

    Published 2018
    “…The sensor fusion algorithm is used to remove noises and uncertainties from sensors' data and provide optimum measurements for path planning. …”
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    Article
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    Surface defect detection and polishing parameter optimization using image processing for G3141 cold rolled steel by Zamri, Ruzaidi

    Published 2016
    “…To realize this, automatic cropping algorithm is developed to detect the region of interest and interpret the Ga value. …”
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    Thesis
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    Algorithm enhancement for host-based intrusion detection system using discriminant analysis by Dahlan, Dahliyusmanto

    Published 2004
    “…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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    Thesis
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    Detection of black hole nodes in mobile ad hoc network using hybrid trustworthiness and energy consumption techniques by Mustafa, Ahmed Sudad

    Published 2017
    “…In this thesis, a hybrid detection algorithm mechanism has been proposed which combines two detection algorithms based on nodes’ trustworthiness and energy consumption in a parallel manner in order to detect the black hole nodes. …”
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    Thesis
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    A novel bio-inspired routing algorithm based on ACO for WSNs by Sharmin, Afsah, Anwar, Farhat, Motakabber, S. M. A.

    Published 2019
    “…The issue of path selection to reach the nodes and vital correspondence parameters, for example, the versatility of nodes, their constrained vitality, the node residual energy and route length are considered since the communications parameters and imperatives must be taken into account by the imperative systems that mediate in the correspondence procedure, and the focal points of the subterranean insect framework have been utilized furthermore. …”
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    The effect of dose calculation algorithms on the normal tissue complication probability values of thoracic cancer by Ahmad, Noor Ashikin

    Published 2015
    “…Purpose: To identify the effect of dose calculation algorithms on the Normal Tissue Complication Probability values of thoracic cancer. …”
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    Monograph
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    A study on advanced statistical analysis for network anomaly detection by Ngadi, Md. Asri, Idris, Mohd. Yazid, Abdullah, Abd. Hanan

    Published 2005
    “…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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    Monograph
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    Data normalization techniques in swarm-based forecasting models for energy commodity spot price by Yusof, Yuhanis, Mustaffa, Zuriani, Kamaruddin, Siti Sakira

    Published 2014
    “…Data mining is a fundamental technique in identifying patterns from large data sets.The extracted facts and patterns contribute in various domains such as marketing, forecasting, and medical.Prior to that, data are consolidated so that the resulting mining process may be more efficient.This study investigates the effect of different data normalization techniques.which are Min-max, Z-score and decimal scaling, on Swarm-based forecasting models.Recent swarm intelligence algorithms employed includes the Grey Wolf Optimizer (GWO) and Artificial Bee Colony (ABC).Forecasting models are later developed to predict the daily spot price of crude oil and gasoline.Results showed that GWO works better with Z-score normalization technique while ABC produces better accuracy with the Min-Max.Nevertheless, the GWO is more superior than ABC as its model generates the highest accuracy for both crude oil and gasoline price.Such a result indicates that GWO is a promising competitor in the family of swarm intelligence algorithms.…”
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    Conference or Workshop Item
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    An alternative approach to normal parameter reduction algorithms for decision making using a soft set theory / Sani Danjuma by Sani , Danjuma

    Published 2017
    “…In addition, the algorithm was relatively easy to understand compare to the state of the art of normal parameter reduction algorithm. …”
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    Thesis
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    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

    Published 2019
    “…Even a normal people using clustering to grouping their data. …”
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    Thesis
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    An improved recommender system based on normalization of matrix factorization and collaborative filtering algorithms by Zahid, Aafaq

    Published 2015
    “…The hypothesis is that the tendency of normalization technique to simplify the data combined with the accuracy of the neighborhood models can improve the accuracy of the RS. …”
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    Adaptive grid-meshed-buffer clustering algorithm for outlier detection in evolving data stream by Abdulateef, Alaa Fareed

    Published 2023
    “…Existing clustering algorithms for outlier detection encounter significant challenges due to insufficient data pre-processing methods and the absence of a suitable data summarization framework for effective data stream clustering. …”
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    Thesis
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    Pengkelasan Sel Kanser Pangkal Rahim Kepada Sel Normal Dan Tidak Normal Menggunakan Analisis Pembezalayan Dan Rangkaian Neural by Saidin, Mohammad Norrish

    Published 2006
    “…The system is built to classify some certain data into two classes, which are normal or abnormal cells. …”
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    Monograph
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    Mobile robot safe navigation in unknown environment by Shayestegan, Mohsen, Marhaban, Mohammad Hamiruce

    Published 2012
    “…The information about the target and the low-range sensory information are used by the controller to produce the commands that gives a favorable direction in terms of reaching to the target within the collision detection. Furthermore, the mobile robot does not suffer from typical ushape environment by a planned local minimum trapping algorithm and also designed controller is easy to understand, simple, and not sensitive to the system model parameters. …”
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    Conference or Workshop Item
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    A clustering-based method for outlier detection under concept drift by Tahir, Mahjabeen, Abdullah, Azizol, Udzir, Nur Izura, Kasmiran, Khairul Azhar

    Published 2024
    “…However, challenges may arise from assuming the majority of data comprises normal instances, particularly during sudden spikes in attack data, potentially diminishing algorithm effectiveness. …”
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    Article