Search Results - (( parallel distribution mining algorithm ) OR ( data implication means algorithm ))

  • Showing 1 - 16 results of 16
Refine Results
  1. 1
  2. 2

    Random sampling method of large-scale graph data classification by Rashed Mustafa, Mohammad Sultan Mahmud, Mahir Shadid

    Published 2024
    “…Mining a large number of graphs becomes a challenging task because state-of-the-art methods are not scalable due to the memory limit. …”
    Get full text
    Get full text
    Get full text
    Article
  3. 3

    K Nearest Neighbor Joins And Mapreduce Process Enforcement For The Cluster Of Data Sets In Bigdata by Md Shah, Wahidah, Othman, Mohd Fairuz Iskandar, Hussian Hassan, Ali Abdul, Talib, Mohammed Saad, Mohammed, Ali Abdul Jabbar

    Published 2018
    “…K Nearest Neighbor Joins (KNN join) are regarded as highly primitive and expensive operations in the data mining.The efficient use of KNN join has proven good results in finding the objects from two data sets prevailed in the huge databases.This has been achieved with the combination of K-Nearest Neighbor query and join operation to find the distinct objects from different data sets.MapReduce is a newly introduced program with the combination of Map Procedure method and Reduce Method widely used in BigData.MapReduce is enriched with parallel distributed algorithm to find the results on a cluster of data sets in BigData.In this paper,the combination of KNN join and MapReduce methods are utilized on the cluster of data sets in BigData for knowledge discovery.Exploring the pinpoint data from huge data sets stored in Big Data demands the distributed large scale data processing.The present research paper is focusing on generic steps for KNN joins exploration operations on MapReduce.The operations of KNN Join are targeted to perform the data partitioning and data pre-processing and necessary calculations.By utilizing the combination of KNN joins with MapReduce methods on BigData data sets will demonstrate a solution for complex computational analysis. …”
    Get full text
    Get full text
    Get full text
    Article
  4. 4

    Forecasting and Trading of the Stable Cryptocurrencies With Machine Learning and Deep Learning Algorithms for Market Conditions by Shamshad, H., Ullah, F., Ullah, A., Kebande, V.R., Ullah, S., Al-Dhaqm, A.

    Published 2023
    “…Thus, this proposed system employs a data science-based framework and six highly advanced data-driven Machine learning and Deep learning algorithms: Support Vector Regressor, Auto-Regressive Integrated Moving Average (ARIMA), Facebook Prophet, Unidirectional LSTM, Bidirectional LSTM, Stacked LSTM. …”
    Get full text
    Get full text
    Article
  5. 5

    An investigation of structural breaks on spot and futures crude palm oil returns by Zainudin, Rozaimah, Shaharudin, Roselee Shah

    Published 2011
    “…We provide some internal and external explanations for the cause of these structural shifts in both mean and variance. Then, the study continues to investigate the implication of structural breaks in crude palm oil volatility clustering estimation process. …”
    Get full text
    Get full text
    Article
  6. 6
  7. 7

    Modified Harris Hawks Optimization Algorithm For Protein Multiple Sequence Alignment by Ibrahim, Al-Zaidi Mohammed Khaleel

    Published 2024
    “…Multiple sequence alignment (msa) is a vital tool in bioinformatics for analyzing growing amounts of sequence data. However, finding similarities across large databases is an np-hard problem, meaning it is extremely difficult and time-consuming to solve exactly in real time. …”
    Get full text
    Get full text
    Thesis
  8. 8
  9. 9

    Pemahaman guru matematik Tahun Enam tentang pembahagian nombor bulat / Hoi Sim Min by Hoi , Sim Min

    Published 2018
    “…The study also found that teachers have four interpretations of the meaning of division, four interpretations of the meaning of divisor, six interpretations of the meaning of quotient, and five interpretations of the meaning of dividend respectively. …”
    Get full text
    Get full text
    Get full text
    Thesis
  10. 10

    Novel approach for streamflow forecasting using a hybrid ANFIS-FFA model by Yaseen, Z.M., Ebtehaj, I., Bonakdari, H., Deo, R.C., Danandeh Mehr, A., Mohtar, W.H.M.W., Diop, L., El-Shafie, A., Singh, V.P.

    Published 2017
    “…The present results have wider implications not only for streamflow forecasting purposes, but also for other hydro-meteorological forecasting variables requiring only the historical data input data, and attaining a greater level of predictive accuracy with the incorporation of the FFA algorithm as an optimization tool in an ANFIS model.…”
    Get full text
    Get full text
    Article
  11. 11

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

    Published 2024
    “…This thesis investigates contextual text classification, which is the process of categorising textual data into different classes or categories based on its meaning within a given context. …”
    Get full text
    Get full text
    Thesis
  12. 12
  13. 13

    Cognitive load assessment through EEG: a dataset from arithmetic and stroop tasks by Nirabi, Ali, Abd Rahman, Faridah, Habaebi, Mohamed Hadi, Sidek, Khairul Azami, Yusoff, Siti Hajar

    Published 2025
    “…This study’s foundation is crucial for advancing stress classification research, with significant implications for cognitive function and well-being.…”
    Get full text
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  14. 14

    How social media crisis response and social interaction is helping people recover from Covid-19: an empirical investigation by Bukar, Umar Ali, A. Jabar, Marzanah, Sidi, Fatimah, Nor, R. N. H., Abdullah, Salfarina, Ishak, Iskandar

    Published 2022
    “…Thus, the study offers theoretical and practical implications in the field of social media-based crisis communication and crisis informatics.…”
    Get full text
    Get full text
    Article
  15. 15
  16. 16

    Chiller power consumption forecasting for commercial building based on hybrid convolution neural networks-long short-term memory model with barnacles mating optimizer by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

    Published 2025
    “…The study compares the proposed CNN-LSTM-BMO against other metaheuristic optimization algorithms, including Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Differential Evolution (DE). …”
    Get full text
    Get full text
    Get full text
    Article