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  1. 1

    Mobile robot path planning using hybrid genetic algorithm and traversability vectors method by Loo, C.K., Rajeswari, M., Wong, E.K., RaoTask, M.V.C.

    Published 2004
    “…Recent advances in robotics and machine intelligence have led to the application of modern optimization method such as the genetic algorithm (GA), to solve the path-planning problem. …”
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    Article
  2. 2

    Performance Evaluation of Vector Evaluated Gravitational Search Algorithms Based on ZDT Test Functions by Badaruddin, Muhammad, Zuwairie, Ibrahim, Kamarul Hawari, Ghazali, Mohd Riduwan, Ghazali, Kian, Sheng Lim, Sophan Wahyudi, Nawawi, Nor Azlina, Ab. Aziz, Marizan, Mubin, Norrima, Mokhtar

    Published 2014
    “…This paper presents a performance evaluation of Vector Evaluated Gravitational Search Algorithm (VEGSA), namely VEGSA-I and VEGSA-II algorithms, for multi-objective optimization problems. …”
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  3. 3

    Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems by Mohammad Khamees Khaleel, Alsajri

    Published 2022
    “…To achieve this goal, an improved Teaching Learning-Based Optimization (ITLBO) algorithm was proposed in dealing with subset feature selection. …”
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    Thesis
  4. 4

    An ensemble data summarization approach based on feature transformation to learning relational data by Chung, Seng Kheau

    Published 2015
    “…In this thesis, a Feature Selection algorithm is investigated and proposed to optimize the TF-IDF vector space by selecting only relevant features from the initial TF-IDF vector space. …”
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    Thesis
  5. 5

    Intrusion Detection Systems, Issues, Challenges, and Needs by Aljanabi, Mohammad, Mohd Arfian, Ismail, Ali, Ahmed Hussein

    Published 2021
    “…However, these algorithms suffer from many lacks especially when apply to detect new type of attacks, and need for new algorithms such as JAYA algorithm, teaching learning-based optimization algorithm (TLBO) algorithm is arise. …”
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  6. 6

    Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2013
    “…ACO originally deals with discrete optimization problem.In applying ACO for solving SVM model selection problem which are continuous variables, there is a need to discretize the continuously value into discrete values.This discretization process would result in loss of some information and hence affects the classification accuracy and seeking time.In this algorithm we propose to solve SVM model selection problem using IACOR without the need to discretize continuous value for SVM.The second algorithm aims to simultaneously solve SVM model selection problem and selects a small number of features.SVM model selection and selection of suitable and small number of feature subsets must occur simultaneously because error produced from the feature subset selection phase will affect the values of SVM model selection and result in low classification accuracy.In this second algorithm we propose the use of IACOMV to simultaneously solve SVM model selection problem and features subset selection.Ten benchmark datasets were used to evaluate the proposed algorithms.Results showed that the proposed algorithms can enhance the classification accuracy with small size of features subset.…”
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  7. 7

    Optimal network reconfiguration and intelligent service restoration prediction technique based on Cuckoo search spring algorithm / Mohamad Izwan Zainal by Zainal, Mohamad Izwan

    Published 2022
    “…The performance of the distribution network is very important, and it is characterized by some measurable item such as voltage profile and losses, to evaluate the actual value comply with the system needs. In this research, Cuckoo Search Spring Algorithm (CSSA) is proposed to enhance the robustness of algorithm by constructing the optimal network reconfiguration consist of reducing power losses and improve voltage profile with the various loadability factor as the constraint according to load profile, based on single and multiobjective model. …”
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    Thesis
  8. 8

    Feedforward neural network for solving particular fractional differential equations by Admon, Mohd Rashid

    Published 2024
    “…This research aims to develop a scheme based on a feedforward neural network (FNN) with a vectorized algorithm (FNNVA) for solving FDEs in the Caputo sense (FDEsC) using selected first-order optimization techniques: simple gradient descent (GD), momentum method (MM), and adaptive moment estimation method (Adam). …”
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    Compressed Sensing Implementations For Sparse Channel Estimation In OFDM Systems by Uwaechia, Anthony Ngozichukwuka

    Published 2018
    “…Secondly, based on prior knowledge of the measurement vector and measurement matrix, to accurately find the support of the unknown signal-vector from very few noisy measurements. …”
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    Thesis
  12. 12

    Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

    Published 2006
    “…There exist numerous algorithms to address the need of text categorization including Naive Bayes, k-nearest-neighbor classifier, and decision trees. …”
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    Final Year Project
  13. 13

    Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

    Published 2006
    “…There exist numerous algorithms to address the need of text categorization including Naive Bayes, k-nearest-neighbor classifier, and decision trees. …”
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    Final Year Project
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    Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms by Koh, Johnny Siaw Paw

    Published 2008
    “…This thesis presents a new approach to optimize the performance of a dual beam optical scanning system in terms of its scanning combinations and speed, using Genetic Algorithm (GA). …”
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  16. 16

    Sequence and sequence-less t-way test suite generation strategy based on the elitist flower pollination algorithm by Mohammed Abdullah, Abdullah Nasser

    Published 2018
    “…In line with the emerging field called Search based Software Engineering, many recently developed t-way strategies have adopted meta-heuristic algorithms as the basis of their implementations such as Simulated Annealing, Genetic Algorithm, Ant Colony Optimization Algorithm, Particle Swarm Optimization, Harmony Search and Cuckoo Search, owing their superior performance in term of test size reduction as compared to general computational based strategies, such as General t-way, Test Vector Generator, In Parameter Order General, Jenny, and Automatic Efficient Test Generator. …”
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    Thesis
  17. 17

    A novel peak detection algorithm using particle swarm optimization for chew count estimation of a contactless chewing detection by Selamat, Nur Asmiza, Md. Ali, Sawal Hamid, Minhad, Khairun Nisa’, Ahmad, Siti Anom, Sampe, Jahariah

    Published 2022
    “…In accordance with the result, this article proposes a novel chew count estimation based on particle swarm optimization (PSO). First, the base of the algorithm is developed based on counting the peak of the chewing signal. …”
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  18. 18

    A novel peak detection algorithm using particle swarm optimization for chew count estimation of a contactless chewing detection by Selamat, Nur Asmiza, Md. Ali, Sawal Hamid, Minhad, Khairun Nisa’, Ahmad, Siti Anom

    Published 2022
    “…In accordance with the result, this article proposes a novel chew count estimation based on particle swarm optimization (PSO). First, the base of the algorithm is developed based on counting the peak of the chewing signal. …”
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    Automated plant classification system using a hybrid of shape and color features of the leaf by Hamid, Laith Emad

    Published 2016
    “…The proposed automated alignment algorithm is based on a similarity measure between the vertical and horizontal halves of the leaf. …”
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    Thesis