Search Results - (( pre selection method algorithm ) OR ( parallel optimization path algorithm ))

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  1. 1
    Tool path generation of contour parallel based on ant colony optimisation

    Tool path generation of contour parallel based on ant colony optimisation by Abdullah, Haslina, Ramli, Rizauddin, Abd Wahab, Dzuraidah, Abu Qudeiri, Jaber

    Published 2016
    “…An Ant Colony Optimisation (ACO) method is used to optimize the tool path length because of its capability to find the shortest tool path length. …”
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  2. 2
    Minimizing machining airtime motion with an ant colony algorithm

    Minimizing machining airtime motion with an ant colony algorithm by Abdullah, Haslina, Ramli, Rizauddin, Abd Wahab, Dzuraidah, Abu Qudeiri, Jaber

    Published 2016
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  3. 3
    OPTIMAL DATAPATH DESIGN FOR A CRYPTOGRAPHIC PROCESSOR: THE BLOWFISH ALGORITHM

    OPTIMAL DATAPATH DESIGN FOR A CRYPTOGRAPHIC PROCESSOR: THE BLOWFISH ALGORITHM by Zain Ali, Noohul Basheer, Noras, James

    Published 2001
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  4. 4
    Restoration planning strategy of transmission system based on optimal energizing time of sectionalizing islands / Dian Najihah Abu Talib

    Restoration planning strategy of transmission system based on optimal energizing time of sectionalizing islands / Dian Najihah Abu Talib by Dian Najihah , Abu Talib

    Published 2019
    “…There are two discrete optimization techniques used in this work, which are the Artificial Bee Colony algorithm and Evolutionary Programming. …”
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  5. 5
    A partition based feature selection approach for mixed data clustering / Ashish Dutt

    A partition based feature selection approach for mixed data clustering / Ashish Dutt by Ashish , Dutt

    Published 2020
    “…One such pre-processing algorithm in EDM is clustering. It is a widely used method in data mining to discover unique patterns in underlying data. …”
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  6. 6
    A novel large-bit-size architecture and microarchitecture for the implementation of Superscalar Pipeline VLIW microprocessors

    A novel large-bit-size architecture and microarchitecture for the implementation of Superscalar Pipeline VLIW microprocessors by Lee, Weng Fook

    Published 2008
    “…Different adder architectures are investigated for suitability on synthesis implementation of large data bus size adder for efficient usage within the ALU. An adder algorithm using repetitive constructs in a parallel algorithm that allows for efficient and optimal synthesis for large data bus size is proposed as a suitable implementation for the adder within the ALU. …”
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  7. 7
    Case Slicing Technique for Feature Selection

    Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

    Published 2004
    “…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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  8. 8
    The Significant Effect of Feature Selection Methods in Spam Risk Assessment Using Dendritic Cell Algorithm

    The Significant Effect of Feature Selection Methods in Spam Risk Assessment Using Dendritic Cell Algorithm by Zainal, K, Jali, MZ

    Published 2024
    “…This feature selection method then further fed in conjunction with the Dendritic Cell Algorithm (DCA) as the classifier to measure the risk concentration of a spam message. …”
    Proceedings Paper
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  9. 9
    Discovering optimal clusters using firefly algorithm

    Discovering optimal clusters using firefly algorithm by Mohammed, Athraa Jasim, Yusof, Yuhanis, Husni, Husniza

    Published 2016
    “…Existing conventional clustering techniques require a pre-determined number of clusters, unluckily; missing information about real world problem makes it a hard challenge.A new orientation in data clustering is to automatically cluster a given set of items by identifying the appropriate number of clusters and the optimal centre for each cluster.In this paper, we present the WFA_selection algorithm that originates from weight-based firefly algorithm.The newly proposed WFA_selection merges selected clusters in order to produce a better quality of clusters.Experiments utilising the WFA and WFA_selection algorithms were conducted on the 20Newsgroups and Reuters-21578 benchmark dataset and the output were compared against bisect K-means and general stochastic clustering method (GSCM).Results demonstrate that the WFA_selection generates a more robust and compact clusters as compared to the WFA, bisect K-means and GSCM.…”
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  10. 10
    Automatic selection of initial points for exploratory vessel tracing in fluoroscopic images

    Automatic selection of initial points for exploratory vessel tracing in fluoroscopic images by Boroujeni, Farsad Zamani, O. K. Rahmat, Rahmita Wirza, Mustapha, Norwati, Affendey, Lilly Suriani, Maskon, Oteh

    Published 2011
    “…This paper presents a new method for efficient selection of initial points for exploratory tracing algorithms. …”
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  11. 11
    The significant effect of feature selection methods in spam risk assessment using dendritic cell algorithm

    The significant effect of feature selection methods in spam risk assessment using dendritic cell algorithm by Zainal K., Jali M.Z.

    Published 2024
    conference output::conference proceedings::conference paper
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  12. 12
    A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification

    A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification by Talpur, N., Abdulkadir, S.J., Hasan, M.H., Alhussian, H., Alwadain, A.

    Published 2023
    “…To address this issue, various data pre-processing methods called Feature Selection (FS) techniques have been presented in the literature. …”
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  13. 13
    Variable block based motion estimation using hexagon diamond full search algorithm (HDFSA) via block subtraction technique

    Variable block based motion estimation using hexagon diamond full search algorithm (HDFSA) via block subtraction technique by Hardev Singh, Jitvinder Dev Singh

    Published 2015
    “…In the video and frame selection, pre-defined video which have different type of motion and size is used for the algorithm evaluation purpose. …”
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  14. 14
    Improving the efficiency of clustering algorithm for duplicates detection

    Improving the efficiency of clustering algorithm for duplicates detection by Emran, Nurul Akmar, Abdul Rahim, Abdulrazzak Ali Mohamed, Kamal Baharin, Safiza Suhana, Othman, Zahriah, Salem, Awsan Thabet, Abd Aziz, Maslita, Md. Bohari, Nor Mas Aina, Abdullah, Noraswaliza

    Published 2023
    “…In this paper, we propose a data pre-processing method that increases the efficiency of window algorithms in grouping similar records together. …”
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  15. 15
    A new ant based rule extraction algorithm for web classification

    A new ant based rule extraction algorithm for web classification by Ku-Mahamud, Ku Ruhana, Saian, Rizauddin

    Published 2011
    “…Web documents contain enormous number of attributes as compared to other type of data. Ant-Miner algorithm is also still lacking in efficiency, accuracy and rule simplicity because of the local minima problem.Therefore, the Ant-Miner algorithm needs to be improved by taking into consideration of the accuracy and rule simplicity criteria so that it could be used to classify Web documents data sets or any large data sets.The best attribute selection method for Web texts categorization is the combination of correlation-based evaluation with random search as the search method.However, this attribute selection method will not give the best performance in attributes reduction. …”
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    Monograph
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  16. 16
    Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm

    Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm by Yap K.S., Abidin I.Z., Ahmad A.R., Hussien Z.F., Pok H.L., Ismail F.I., Mohamad A.M.

    Published 2023
    “…The purpose of choosing parameters is to get the best generalization performance. Genetic Algorithm (GA) is used to search for the best parameter of SVM classification by using combination of random and pre-populated genomes from Pre-Populated Database (PPD). …”
    Conference Paper
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  17. 17
    Artificial intelligence to predict pre-clinical dental student academic performance based on pre-university results: a preliminary study

    Artificial intelligence to predict pre-clinical dental student academic performance based on pre-university results: a preliminary study by Lestari, Widya, Abdullah, Adilah Syahirah, Ahmad Amin, Afifah Munirah, faridah, Nur, Sukotjo, Cortino, Ismail, Azlini, mohamad ibrahim, mohamad shafiq, Insani, Nashuha, Utomo, Chandra Prasetyo

    Published 2024
    “…Methods: ML algorithms logistic regression (LR), decision tree (DT), random forest (RF), and support vector machine (SVM) models were applied. …”
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  18. 18
    Fireflyclust: an automated hierarchical text clustering approach

    Fireflyclust: an automated hierarchical text clustering approach by Mohammed, Athraa Jasim, Yusof, Yuhanis, Husni, Husniza

    Published 2017
    “…The proposed clustering method operates based on five phases: data pre-processing, clustering, item re-location, cluster selection and cluster refinement. …”
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  19. 19
    A 'snowflake' geometrical representation for optimised degree six 3-modified chordal ring networks

    A 'snowflake' geometrical representation for optimised degree six 3-modified chordal ring networks by Chien, Stephen Lim Een, Raja Maamor Shah, Raja Noor Farah Azura, Othman, Mohamed

    Published 2016
    “…A tree visualisation was constructed based on its connectivity to enable the generation of formulae for optimal diameter and average optimal path lengths. …”
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    Conference or Workshop Item
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  20. 20
    Detection of black hole nodes in mobile ad hoc network using hybrid trustworthiness and energy consumption techniques

    Detection of black hole nodes in mobile ad hoc network using hybrid trustworthiness and energy consumption techniques by Mustafa, Ahmed Sudad

    Published 2017
    “…In this thesis, a hybrid detection algorithm mechanism has been proposed which combines two detection algorithms based on nodes’ trustworthiness and energy consumption in a parallel manner in order to detect the black hole nodes. …”
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