Search Results - (( java implementation bat algorithm ) OR ( missing problem based algorithm ))

Refine Results
  1. 1

    Fuzzy modeling using Bat Algorithm optimization for classification by Noor Amidah, Ahmad Sultan

    Published 2018
    “…A Sazonov Engine which is a fuzzy java engine is use to apply Bat Algorithm in the experiment. …”
    Get full text
    Get full text
    Get full text
    Undergraduates Project Papers
  2. 2

    Missing tags detection algorithm for radio frequency identification (RFID) data stream by Zainudin, Nur 'Aifaa

    Published 2019
    “…Thus in this research, an AC complement algorithm with hashing algorithm and Detect False Negative Read algorithm (DFR) is used to developed the Missing Tags Detection Algorithm (MTDA). …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  3. 3
  4. 4

    Auto-feed hyperparameter support vector regression prediction algorithm in handling missing values in oil and gas dataset by Amirruddin, A., Aziz, I.A., Hasan, M.H.

    Published 2020
    “…This problem inspires the idea to develop a prediction algorithm to predict the missing values in the dataset, where Support vector regression (SVR) has been proposed as a prediction method to predict missing values in several academic types of researches. …”
    Get full text
    Get full text
    Article
  5. 5

    Missing-values imputation algorithms for microarray gene expression data by Moorthy, Kohbalan, Jaber, Aws Naser, Mohd Arfian, Ismail, Ernawan, Ferda, Mohd Saberi, Mohamad, Safaai, Deris

    Published 2019
    “…By using local and global correlation of the data, we were able to focus mostly on the differences between the algorithms. We classified the algorithms as global, hybrid, local, or knowledge-based techniques. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Get full text
    Get full text
    Book Chapter
  6. 6
  7. 7

    New Learning Models for Generating Classification Rules Based on Rough Set Approach by Al Shalabi, Luai Abdel Lateef

    Published 2000
    “…Classification rules were generated based on the best reduct. For the problem of missing data, a new approach was proposed based on data partitioning and function mode. …”
    Get full text
    Get full text
    Thesis
  8. 8

    Development of an imputation technique - INI for software metric database with incomplete data by Wasito, Ito, Olanrewaju, Rashidah F.

    Published 2007
    “…In this paper, an imputation technique for imputing missing data based on global-local Modified Singular Value Decomposition (MSVD) algorithm, INI was proposed. …”
    Get full text
    Get full text
    Get full text
    Book Section
  9. 9
  10. 10

    Confidence intervals (CI) for concentration parameter in von Mises distribution and analysis of missing values for circular data / Siti Fatimah binti Hassan by Hassan, Siti Fatimah

    Published 2015
    “…The final part of this study is an analysis of missing values for circular variables. Missing values is a common problem that occurs in data collection. …”
    Get full text
    Get full text
    Thesis
  11. 11
  12. 12

    Compiler-based prefetching algorithm for recursive data structure by Anuar, Nurulhaini

    Published 2007
    “…This project investigates compiler-based prefetching for pointer based applications particularly those containing Recursive Data Structures (RDS) and designs the proposed algorithm. …”
    Get full text
    Get full text
    Get full text
    Thesis
  13. 13
  14. 14

    Estimating Missing Precipitation to Optimize Parameters for Prediction of Daily Water Level Using Artificial Neural Network by Dayang Suhaila, Awang Suhaili

    Published 2006
    “…It has been found that the ANN has the potential to solve the problems of estimation missing precipitatio in predicting daily water level. …”
    Get full text
    Get full text
    Get full text
    Final Year Project Report / IMRAD
  15. 15

    Hybrid Sine Cosine and Fitness Dependent Optimizer for global optimization by Chiu, Po Chan, Ali, Selamat, Ondrej, Krejcar, Kuok, King Kuok

    Published 2021
    “…Additionally, the SC-FDO was applied to the missing data estimation cases and refined the missingness as optimization problems. …”
    Get full text
    Get full text
    Get full text
    Article
  16. 16

    Enhanced utility accrual scheduling algorithms for adaptive real time system. by Othman, Muhammad Fauzan, Ahmad, Idawaty

    Published 2009
    “…These algorithms addressed the unnecessary abortion problem that was identified in the existing algorithm known as General Utility Scheduling (GUS). …”
    Get full text
    Article
  17. 17

    Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor by Adilah, Abdul Ghapor

    Published 2017
    “…In the final part of the study on the missing value problem in LFRM, the modern imputation techniques, namely the expectation-maximization (EM) algorithm and the expectation-maximization with bootstrapping (EMB) algorithm is proposed. …”
    Get full text
    Get full text
    Get full text
    Thesis
  18. 18

    An improved machine learning model of massive Floating Car Data (FCD) based on Fuzzy-MDL and LSTM-C for traffic speed estimation and prediction by Ahanin, Fatemeh

    Published 2023
    “…This behaviour of HMM makes it less effective in estimation of traffic data, because it might be necessary to consider several previous states when estimating a missing state. This thesis uses Fuzzy C-Mean and concept of MDL to constitute patterns and estimate the missing traffic state based on n previous states. …”
    Get full text
    Get full text
    Get full text
    Thesis
  19. 19

    A Novel Path Prediction Strategy for Tracking Intelligent Travelers by Motlagh, Omid Reza Esmaeili

    Published 2009
    “…Disconnection of the mobile terminal (MT) from the access points (AP) in WLAN-based systems is the example case of the problem. …”
    Get full text
    Get full text
    Thesis
  20. 20

    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.…”
    Get full text
    Get full text
    Article