Search Results - (( mobile evaluation bat algorithm ) OR ( early identification based algorithm ))

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    A comprehensive overview of classical and modern route planning algorithms for self-driving mobile robots by Wan Daud, Wan Mohd Bukhari, Abu, Nur Syuhadah, Omar, Siti Nashayu, Sohaimeh, Shahirul Ashraf, Adli,, M. H.

    Published 2022
    “…Classical or traditional methods, such as Roadmaps (Visibility Graph and Voronoi Diagram), Potential Fields, and Cell Decomposition, and modern methodologies such as heuristic-based (Dijkstra Method, A* Algorithms, and D* Algorithms), metaheuristics algorithms (such as PSO, Bat Algorithm, ACO, and Genetic Algorithm), and neural systems such as fuzzy neural networks or fuzzy logic (FL) and Artificial Neural Networks (ANN) are described in this report. …”
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    Article
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    Bat optimized link state routing protocol for energy-aware mobile ad-hoc networks by Jubair M.A., Mostafa S.A., Muniyandi R.C., Mahdin H., Mustapha A., Hassan M.H., Mahmoud M.A., Al-Jawhar Y.A., Al-Khaleefa A.S., Mahmood A.J.

    Published 2023
    “…The symmetry between OLSR of MANET and Bat Algorithm (BA) is that both of them use the same mechanism for finding the path via sending and receiving specific signals. …”
    Article
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    Delay and energy-aware routing for efficient data collection in wireless sensor networks / Ihsan Ali by Ihsan , Ali

    Published 2024
    “…Both Bat Algorithm parameters and AFW parameters are adaptively tuned to balance exploration and exploitation throughout the optimization process. …”
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    Thesis
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    Quality of service and energy efficient aware (QEEA) scheduling algorithm for long term evolution (LTE) network / Nurulanis Mohd Yusoff by Mohd Yusoff, Nurulanis

    Published 2017
    “…Basically, the QEEA is based on the Time Domain (TD) and Frequency Domain (FD) scheduling where it is dependent on the QoS requirements to allocate resources. The proposed algorithm is compared against other scheduling algorithms, namely, the Channel and QoS Aware (CQA), Priority Set Scheduler (PSS), Proportional Fair (PF), Maximum Throughput (MT) and Blind Average Throughput (BAT). …”
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    Methods for identification of the opportunistic gut mycobiome from colorectal adenocarcinoma biopsy tissues by Aisyah, Yunus, Norfilza, Mohd Mokhtar, Raja Affendi, Raja Ali *, Siti Maryam, Ahmad Kendong, Hajar, Fauzan Ahmad

    Published 2024
    “…•Application of machine learning algorithms to the identification of potential mycobiome biomarkers for non-invasive colorectal cancer screening. …”
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    Identification of transformer fault based on dissolved gas analysis using hybrid support vector machine-modified evolutionary particle swarm optimisation by Illias, Hazlee Azil, Wee, Zhao Liang

    Published 2018
    “…It was found that the proposed hybrid SVM-Modified EPSO (MEPSO)-Time Varying Acceleration Coefficient (TVAC) technique results in the highest correct identification percentage of faults in a power transformer compared to other PSO algorithms. …”
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    Deep learning-based colorectal cancer classification using augmented and normalised gut microbiome data / Mwenge Mulenga by Mwenge , Mulenga

    Published 2022
    “…First, to investigate the methods used to address limitations associated with microbiome-based datasets in colorectal cancer identification using deep neural network algorithms. …”
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    Ensemble-based machine learning algorithms for classifying breast tissue based on electrical impedance spectroscopy by Rahman, Sam Matiur, Ali, Md. Asraf, Altwijri, Omar, Alqahtani, Mahdi, Ahmed, Nasim, Ahamed, Nizam Uddin

    Published 2020
    “…In addition, the ranked order of the variables based on their importance differed across the ML algorithms. …”
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    Predictive Modelling of Stroke Occurrence among Patients using Machine Learning by Sures, Narayasamy, Thilagamalar, Maniam

    Published 2023
    “…Early identification of high-risk patients enables timely intervention and implementation of preventive measures, potentially reducing the burden of stroke-related complications. …”
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    Comparative study of informative acoustic features for VTOL UAV faulty prediction using machine learning by Mohd Sani, Fareisya Zulaikha, Makhtar, Siti Noormiza, Mohd Nor, Elya, Kamarudin, Nur Diyana, Md Ali, Syaril Azrad, Md Ali, Kurnianingsih

    Published 2025
    “…The sound emitted by Vertical Take Off and Landing (VTOL) UAVs offers valuable insights into their flight performance, serving as a crucial element for the efficient monitoring of flying conditions and early detection of potential faults. This paper will focus on developing fault detection and identification using audio data of different propeller conditions. …”
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    Outlier Detection Technique in Data Mining: A Research Perspective by Mansur, M. O., Md. Sap, Mohd. Noor

    Published 2005
    “…In this paper we will explain the first part of our research, which is focused on outlier identification and provide a description of why an identified outlier exceptional, based on Distance-Based outlier detection and Density-Based outlier detection.…”
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