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  1. 1
    An efficient anomaly intrusion detection method with evolutionary neural network

    An efficient anomaly intrusion detection method with evolutionary neural network by Sarvari, Samira

    Published 2020
    “…The second anomaly detection method is the Evolutionary Kernel Neural Network Random Weights (EKNNRW) in order to increase the accuracy of classification. The third proposed method is a new Evolutionary Neural Network (ENN) algorithm with a combination of Genetic Algorithm and Multiverse Optimizer (GAMVO) as a training part of ANN to create efficient anomaly-based detection with low false alarm rate. …”
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  2. 2
    Development of predictive modeling and deep learning classification of taxi trip tolls

    Development of predictive modeling and deep learning classification of taxi trip tolls by Al-Shoukry, Suhad, M. Jawad, Bushra Jaber, Zalili, Musa, Sabry, Ahmad H.

    Published 2022
    “…Using a classification algorithm, it is possible to extract drop-off and pickup locations from taxi trip data and estimate if the tour would incur tolls. …”
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  3. 3
    Network Traffic Classification Analysis on Differentiated Services Code Point Using Deep Learning Models for Efficient Deep Packet Inspection

    Network Traffic Classification Analysis on Differentiated Services Code Point Using Deep Learning Models for Efficient Deep Packet Inspection by Ahmed Khan, Fazeel, Abubakar, Adamu

    Published 2024
    “…There is a need to have effective prioritization and classification of IP packets for routers to enable the forwarding of such packets including packets having critical data efficiently and with a lower drop rate. …”
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  4. 4
    DEVELOPMENT OF PREDICTIVE MODELING AND DEEP LEARNING CLASSIFICATION OF TAXI TRIP TOLLS

    DEVELOPMENT OF PREDICTIVE MODELING AND DEEP LEARNING CLASSIFICATION OF TAXI TRIP TOLLS by Al-Shoukry S., Jawad B.J.M., Musa Z., Sabry A.H.

    Published 2023
    “…Using a classification algorithm, it is possible to extract drop-off and pickup locations from taxi trip data and estimate if the tour would incur tolls. …”
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  5. 5
    An Improve k-NN Classifier using Similarity Distance Plot-Data Reduction and Dask for Big Datasets

    An Improve k-NN Classifier using Similarity Distance Plot-Data Reduction and Dask for Big Datasets by Abdul Muqtasid, Rushdi

    Published 2025
    “…The classification of test data follows the conventional k-NN procedure. …”
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  6. 6
    Electronic Tongue: Study on the Freshness of Milk

    Electronic Tongue: Study on the Freshness of Milk by Jaafar, Mohamad Nazrin

    Published 2012
    “…After the experiment has been done, the data obtained was used in Matlab for classification purpose. …”
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  7. 7
    Automated traffic counting data collection and analysis

    Automated traffic counting data collection and analysis by Low, Anand Hong Ren

    Published 2021
    “…The performance of the algorithm is determined by the counting, classification, and speed measuring accuracy. …”
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  8. 8
    Comparison of algorithm Support Vector Machine and C4.5 for identification of pests and diseases in chili plants

    Comparison of algorithm Support Vector Machine and C4.5 for identification of pests and diseases in chili plants by M, Irfan, N, Lukman, A. A, Alfauzi, J, Jumadi

    Published 2019
    “…In this study comparing the performance classification techniques of Support Vector Machine (SVM) and C4.5 algorithms. …”
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  9. 9
    Land Use Changes in Jeli, Kelantan

    Land Use Changes in Jeli, Kelantan by Muhammad Firdaus Abdul Karim

    Published 2013
    “…Satellite imagery are pre-processed in geometric correction and further processed in subsetting, masking cloud and supervised classification. Land use maps from supervised classification of satellite imagery and existing land use maps are then digitized into shapefile (.shp) format in ArcGIS software, spatial reference is updated to WGS1984 and accuracy assessment is performed to validate data. …”
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    Undergraduate Final Project Report
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  10. 10
    Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions

    Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions by Abbas, Iraq Tareq

    Published 2018
    “…The BOGS-BAT algorithm is based on three techniques. The first technique is to move or switch solution from single function to functions that contain more than one objective functions. …”
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  11. 11
    A block cipher based on genetic algorithm

    A block cipher based on genetic algorithm by Zakaria, Nur Hafiza

    Published 2016
    “…In many algorithms which are based on the genetic algorithm approach, diffusion properties using crossover and mutation function are being generated to produce a secure data transmission. …”
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  12. 12
    A comparative study and simulation of object tracking algorithms

    A comparative study and simulation of object tracking algorithms by Ji, Yuanfa, Yin, Pan, Sun, Xiyan, Kamarul Hawari, Ghazali, Guo, Ning

    Published 2020
    “…The algorithms using convolution features and multi-features fusion algorithms have more advantages in tracking accuracy than the algorithm using a single feature, but the tracking speed will also drop rapidly. …”
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  13. 13
    FaaSBid: an auction-based model for Function as a Service in edge-fog environments using unallocated resources

    FaaSBid: an auction-based model for Function as a Service in edge-fog environments using unallocated resources by Al-Qadhi, Abdulrahman K., Athauda, Rukshan, Latip, Rohaya, Hussin, Masnida

    Published 2026
    “…To initialise function placement, Fitness-Based Swap (FBSW) algorithm is proposed which places functions based on pre-defined information such as function size, function maximum execution time, and storage cost. …”
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  14. 14
    Computation of cryptosystem based on Lucas functions using addition chain

    Computation of cryptosystem based on Lucas functions using addition chain by Md Ali, Zulkarnain, Othman, Mohamed, Md. Said, Mohamad Rushdan, Sulaiman, Md. Nasir

    Published 2010
    “…Cryptosystem based on Lucas Functions is known as LUC Cryptosystem. …”
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  15. 15
    An improved fast scanning algorithm based on distance measure and threshold function in region image segmentation

    An improved fast scanning algorithm based on distance measure and threshold function in region image segmentation by Ismael, Ahmed Naser

    Published 2016
    “…Hence, this study proposes an Improved Fast Scanning algorithm that is based on Sorensen distance measure and adaptive threshold function. …”
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  16. 16
    Enhancing speed performance of the cryptographic algorithm based on the lucas sequence

    Enhancing speed performance of the cryptographic algorithm based on the lucas sequence by M. Abulkhirat, Esam

    Published 2003
    “…Utilizing the properties of Lucas functions introduced a public key system based on Lucas functions instead of exponentiation, which offer a good alternative to the most publicly used exponential public key system RSA. …”
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  17. 17
    Image encryption algorithm based on chaotic mapping

    Image encryption algorithm based on chaotic mapping by Salleh, Mazleena, Ibrahim, Subariah, Isnin, Ismail Fauzi

    Published 2003
    “…HVT function is based on a two-dimensional chaotic map that utilized Baker’s map algorithm. …”
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  18. 18
    An efficient computation technique for cryptosystems based on Lucas functions

    An efficient computation technique for cryptosystems based on Lucas functions by Md Ali, Zulkarnain, Othman, Mohamed, Md. Said, Mohamad Rushdan, Sulaiman, Md. Nasir

    Published 2008
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  19. 19
    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms

    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Alzaeemi, Shehab Abdulhabib, Tay, Kim Gaik, Huong, Audrey, Sathasivam, Saratha, Majahar Ali, Majid Khan

    Published 2023
    “…Based on the results, the EP algorithm achieved a higher training rate and simple structure compared with the rest of the algorithms. …”
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  20. 20
    Biological-based semi-supervised clustering algorithm to improve gene function prediction

    Biological-based semi-supervised clustering algorithm to improve gene function prediction by Kasim, Shahreen, Deris, Safaai, M. Othman, Razib, Hashim, Rathiah

    Published 2011
    “…However, commonclustering algorithms do not provide a comprehensive approach that look into the three categories of annotations; biologicalprocess, molecular function, and cellular component, and were not tested with different functional annotation database formats.Furthermore, the traditional clustering algorithms use random initialization which causes inconsistent cluster generation and areunable to determine the number of clusters involved. …”
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