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  1. 1
    Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer

    Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer by Ahmad Nezer, Nurul Aqilah

    Published 2017
    “…The development tools used in developing this project is NetBeans by using Java for the implementation of the coding. The methodology that used for developing this system is the Dijkstra’s algorithm. …”
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  2. 2
    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization

    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

    Published 2019
    “…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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  3. 3
    Modified word representation vector based scalar weight for contextual text classification

    Modified word representation vector based scalar weight for contextual text classification by Abbas Saliimi, Lokman

    Published 2024
    “…Based on the acquired results, the experiments reveal that the modified word vectors algorithm can effectively alter original LLM-generated word vectors to reflect intended contexts and can outperform baseline scores in contextual text classification tasks. …”
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  4. 4
    Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment

    Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment by Shaliza Hayati A. Wahab, Nordin Saad, Azali Saudi, Ali Chekima

    Published 2021
    “…In this study, a fast iterative method known as Rotated Successive Over-Relaxation (RSOR) is introduced. The algorithm is implemented in a self-developed 2D Java tool, UAV Planner. …”
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  5. 5
    A modified fuzzy min-max neural network with a genetic-algorithm-based rule extractor for pattern classification

    A modified fuzzy min-max neural network with a genetic-algorithm-based rule extractor for pattern classification by Quteishat, A., Lim, C.P., Tan, K.S.

    Published 2010
    “…The first stage consists of a modified fuzzy min-max (FMM) neural-network-based pattern classifier, while the second stage consists of a genetic-algorithm (GA)-based rule extractor. …”
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  6. 6
    A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network

    A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network by Salari, Nader, Shohaimi, Shamarina, Najafi, Farid, Nallappan, Meenakshii, Karishnarajah, Isthrinayagy

    Published 2014
    “…Among numerous artificial intelligence approaches, k-Nearest Neighbor algorithms, genetic algorithms, and artificial neural networks are considered as the most common and effective methods in classification problems in numerous studies. …”
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  7. 7
    Smart appointment organizer for mobile application / Mohd Syafiq Adam

    Smart appointment organizer for mobile application / Mohd Syafiq Adam by Adam, Mohd Syafiq

    Published 2009
    “…The main component of this prototype is the use of Dijkstra algorithm to compute the shortest path from source of appointment to the 6 points of destinations within UiTM Shah Alam. …”
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  8. 8
    Modified Hopfield Neural Network Classification Algorithm For Satellite Images

    Modified Hopfield Neural Network Classification Algorithm For Satellite Images by Ahmed Asal Kzar, Ahmed Asal Kzar

    Published 2016
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  9. 9
    Modified anfis architecture with less computational complexities for classification problems

    Modified anfis architecture with less computational complexities for classification problems by Talpur, Noureen

    Published 2018
    “…The results show that the proposed modified ANFIS architecture with gaussian membership function and Artificial Bee Colony (ABC) optimization algorithm, on average has achieved classification accuracy of 99.5% with 83% less computational complexity.…”
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  10. 10
    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem

    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

    Published 2021
    “…Nowadays, the use of SVM is very perspective for the big data classification. SVM provides a global solution for data classification but SVM is highly sensitive to noise data and may not be effective when the level of noise data is high. …”
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  11. 11
    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem

    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

    Published 2021
    “…Nowadays, the use of SVM is very perspective for the big data classification. SVM provides a global solution for data classification but SVM is highly sensitive to noise data and may not be effective when the level of noise data is high. …”
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  12. 12
    Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study

    Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study by Li Yu Yab, Li Yu Yab, Wahid, Noorhaniza, A Hamid, Rahayu

    Published 2023
    “…This comparative study aims to investigate and compare the effectiveness of the inversed control parameter in the proposed methods against the original algorithms in terms of the number of selected features and the classification accuracy. …”
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  13. 13
    Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study

    Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study by Li Yu Yab, Li Yu Yab, Wahid, Noorhaniza, A Hamid, Rahayu

    Published 2023
    “…This comparative study aims to investigate and compare the effectiveness of the inversed control parameter in the proposed methods against the original algorithms in terms of the number of selected features and the classification accuracy. …”
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  14. 14
    Improvement of fuzzy neural network using mine blast algorithm for classification of Malaysian Small Medium Enterprises based on strength

    Improvement of fuzzy neural network using mine blast algorithm for classification of Malaysian Small Medium Enterprises based on strength by Hussain Talpur, Kashif

    Published 2015
    “…Mine Blast Algorithm (MBA) which has been improved by Improved MBA (IMBA) can be further improved by modifying its exploitation phase. …”
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  15. 15
    Aco-based feature selection algorithm for classification

    Aco-based feature selection algorithm for classification by Al-mazini, Hassan Fouad Abbas

    Published 2022
    “…The modified graph clustering ant colony optimisation (MGCACO) algorithm is an effective FS method that was developed based on grouping the highly correlated features. …”
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  16. 16
    Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification

    Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification by Myaser, Jwan

    Published 2020
    “…Furthermore, using SVM requires the user to set certain parameters values, including kernel type and kernel parameters, since these parameters own a significant effect on the effectiveness of SVM. The second stage involved assessing the spatial resolution effect through utilizing Landsat 8 (30 m) and Sentinel (10 m) data on LCM accuracy using SVM, K-Nearest Neighbor (K-NN), Random Forest (RF), and Neural Network (NN) algorithms. …”
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  17. 17
    Logistic regression methods for classification of imbalanced data sets

    Logistic regression methods for classification of imbalanced data sets by Santi Puteri Rahayu, -

    Published 2012
    “…This thesis aims to develop the simple and effective imbalanced classification algorithms by previously improving the algorithms performance of general classifiers i.e. …”
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  18. 18
    Comparative analysis of convolutional neural network frameworks for efficient classification of calcification patches in Digital Breast Tomosynthesis images / Nurhazwani Mohamad Fozi

    Comparative analysis of convolutional neural network frameworks for efficient classification of calcification patches in Digital Breast Tomosynthesis images / Nurhazwani Mohamad Fo... by Mohamad Fozi, Nurhazwani

    Published 2025
    “…A comparative analysis of CNN models including GoogleNet, SqueezeNet, modified GoogleNet and modified SqueezeNet is conducted to determine their classification performance. …”
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  19. 19
    A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani

    A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani by Mahmoud Reza, Saybani

    Published 2016
    “…Experimental results on real-world machine learning benchmark data sets have demonstrated the effectiveness of the proposed algorithms. …”
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  20. 20
    Modified symbiotic organisms search optimization for automatic construction of convolutional neural network architectures

    Modified symbiotic organisms search optimization for automatic construction of convolutional neural network architectures by Jauro, Fatsuma, Abdullahi, Usman Ali, Abdulsalami, Aminu Onimisi, Ibrahim, Adamu Abubakar, Abdullahi, Mohammed, Chiroma, Haruna

    Published 2024
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