Search Results - (( software optimization based algorithm ) OR ( using optimization clustering algorithm ))

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    Web-Based Route Optimization System For Logistic Using Agglomerative Clustering And Genetic Algorithm by Tan, Chee Kuan

    Published 2020
    “…This system will first cluster those addresses based on the number of trucks involved and then perform the route optimization algorithm to suggest the shortest route to the user. …”
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    Final Year Project / Dissertation / Thesis
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    An enhanced version of black hole algorithm via levy flight for optimization and data clustering problems by Abdulwahab, Haneen A., Noraziah, Ahmad, Al-Sewari, Abdul Rahman Ahmed Mohammed, Salih, Sinan Q.

    Published 2019
    “…Recently, nature-inspired algorithms have been proposed and utilized for solving the optimization problems in general, and data clustering problem in particular. …”
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    Article
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    Weight-based firefly algorithm for document clustering by Mohammed, Athraa Jasim, Yusof, Yuhanis, Husni, Husniza

    Published 2013
    “…FA is a nature-inspired algorithm that is used in many optimization problems.The FA is realized in document clustering by executing it on Reuters-21578 database.The algorithm identifies documents that has the highest light intensity in a search space and represents it as a centroid.This is followed by recognizing similar documents using the cosine similarity function.Documents that are similar to the centroid are located into one cluster and dissimilar in the other.Experiments performed on the chosen dataset produce high values of Purity and F-measure.Hence, suggesting that the proposed Firefly algorithm is a possible approach in document clustering.…”
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    Conference or Workshop Item
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    Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed by Borujeni, Sattar Chavoshi

    Published 2012
    “…This approach was based on fuzzy expert system (FES) using Fuzzy Toolbox of MATLAB software. …”
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    Thesis
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    A Comparative Study Of Fuzzy C-Means And K-Means Clustering Techniques by Sharifah Sakinah, Syed Ahmad

    Published 2014
    “…Next, we also optimize the fuzzification variable, m in FCM algorithm in order to improve the clustering performance. …”
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    Methodology for modified whale optimization algorithm for solving appliances scheduling problem by Omar, Mohd Faizal, Mohd Bakeri, Noorhadila, Mohd Nawi, Mohd Nasrun, Hairani, Norfazlirda, Khalid, Khalizul

    Published 2020
    “…Whale Optimization Algorithm (WOA) is considered as one of the newest metaheuristic algorithms to be used for solving a type of NP-hard problems. …”
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    Optimized Load Balancing based Task Scheduling in Cloud Environment by Noraziah, Ahmad, Sultan, Elrasheed Ismail, Faisal, Alamri, Abdalla, Ahmed N.

    Published 2014
    “…In addition, the salient feature of this algorithm is to optimize node available throughput dynamically using MatLab10A software. …”
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    Minimizing the number of stunting prevalence using the euclid algorithm clustering approach by Zarlis, Muhammad, Oktavia, Tanty, Buaton, Relita, Ernawan, Ferda, Andrian, Kevin

    Published 2023
    “…The algorithm used is Euclid. The Euclid algorithm can cluster stunting prevalence data into 4 clusters with the very little category at 79%, the little category at 67%, the many categories at 51%, and the very much category at 21%. …”
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    Conference or Workshop Item
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    Efficient classifying and indexing for large iris database based on enhanced clustering method by Khalaf, Emad Taha, Mohammed, Muamer N., Kohbalan, Moorthy, Khalaf, Ahmad Taha

    Published 2018
    “…The proposed method can be used to perform global search and exhibits quick convergence rate while optimizing the initial clustering centers of the K-means algorithm. …”
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    Spatial Clustering Algorithm for Time Series Rainfall Data Using X-Means Data Splitting by Ali, Noor Rasidah, Ku Mahamud, Ku Ruhana

    Published 2017
    “…The performance of the clustering algorithm gets even worse if it relies on actual data and many clustering algorithms are often faced with conflict in handling high dimensional data. …”
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    A new routing mechanism for energy-efficient in bluetooth mesh-low power nodes based on wireless sensor network by Almuslehi, Hussein Saad Mohammed

    Published 2023
    “…Compared to the Ant Colony Optimization-Genetic Algorithm (ACO-GA) and Ant Colony Optimization- Hierarchical Clustering Mechanism (ACOHCM), the ACO algorithm shows superior power savings and efficiency. …”
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    Thesis
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    An evaluation of Monte Carlo-based hyper-heuristic for interaction testing of industrial embedded software applications. by S. Ahmed, Bestoun, Enoiu, Eduard, Afzal, Wasif, Kamal Z., Zamli

    Published 2020
    “…Hyper-heuristic is a new methodology for the adaptive hybridization of meta-heuristic algorithms to derive a general algorithm for solving optimization problems. …”
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    Fuzzy subtractive clustering (FSC) with exponential membership function for heart failure disease clustering by Annisa Eka Haryati, ., Sugiyarto, Surono, Tommy Tanu, Wijaya, Goh, Khang Wen, Aris, Thobirin

    Published 2022
    “…It simulated and processed using Fuzzy Subtractive Clustering Algorithm, Jupyter Notebook Software with Python programming language. …”
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    Hybrid metaheuristic method for clustering in wireless sensor networks / Bryan Raj Peter Jabaraj by Bryan Raj , Peter Jabaraj

    Published 2023
    “…As such, this thesis proposes a hybrid metaheuristic method that consists of Sperm Swarm Optimization (SSO) algorithm and Genetic Algorithm (GA), which is termed HSSOGA. …”
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    Abnormalities detection in apert syndrome using hierarchical clustering algorithms by Nur Syahirah, Zulkipli, Siti Zanariah, Satari, Wan Nur Syahidah, Wan Yusoff

    Published 2025
    “…There are 12 skull angles and these angles are analysed using hierarchical clustering algorithms for identifying the outliers or abnormalities. …”
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    Clustering Based on Customers’ Behaviour in Accepting Personal Loan using Unsupervised Machine Learning by Lim, Wai Ping, Goh, Ching Pang

    Published 2023
    “…As a conclusion, KMeans clustering was presenting better cluster results using this particular dataset.…”
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