Search Results - (( data optimization methods algorithm ) OR ( data interactive learning algorithm ))

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  1. 1

    A fast learning network with improved particle swarm optimization for intrusion detection system by Ali, Mohammed Hasan

    Published 2019
    “…In these experiments, it was demonstrated that the FLN optimization method achieved 0.9964 which is a higher accuracy than most of the existing paradigms for classifying network intrusion detection data.…”
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    Thesis
  2. 2

    Social media mining: a genetic based multiobjective clustering approach to topic modelling by Alfred, Rayner, Loo, Yew Jie, Obit, Joe Henry, Lim, Yuto, Haviluddin, Haviluddin, Azman, Azreen

    Published 2021
    “…However, less works have been conducted in applying multiobjective based algorithm for topic extraction. Most of these algorithms are not optimized, even if they are, they are only optimized by using a single objective method and may underperform when solving real-world problems which are typically multi-objectives in nature. …”
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    Article
  3. 3

    A review unveiling various machine learning algorithms adopted for biohydrogen productions from microalgae by Mohamad Zulfadhli Ahmad Sobri, Alya Redhwan, Fuad Ameen, Lim, Jun Wei, Liew, Chin Seng, Mong, Guo Ren, Hanita Daud, Rajalingam Sokkalingam, Ho, Chii-Dong, Anwar Usman, D. H. Nagaraju, Pasupuleti Visweswara Rao

    Published 2023
    “…The complex natures of the biological processes involved have afflicted the accuracy of traditional modelling and optimization, besides being costly. Accordingly, machine learning algorithms have been employed to overcome setbacks, as these approaches have the capability to predict nonlinear interactions and handle multivariate data from microalgal biohydrogen studies. …”
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    Article
  4. 4

    Social media mining: a genetic based multiobjective clustering approach to topic modelling by Rayner Alfred, Loo Yew Jie, Joe Henry Obit, Yuto Lim, Haviluddin Haviluddin, Azreen Azman

    Published 2021
    “…However, less works have been conducted in applying multiobjective based algorithm for topic extraction. Most of these algorithms are not optimized, even if they are, they are only optimized by using a single objective method and may underperform when solving real-world problems which are typically multi-objectives in nature. …”
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    Article
  5. 5

    Improving neural networks training using experiment design approach by Chong, Wei Kean

    Published 2005
    “…One more data (m+ 1) is entered to train the NN again. This data is selected by two methods: random and Experiment Design Approach (D-optimal and Maxmin Distance). …”
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    Thesis
  6. 6

    Framework for stream clustering of trajectories based on temporal micro clustering technique by Abdulrazzaq, Musaab Riyadh

    Published 2018
    “…The minimum description length is an important concept in information theory and computational learning in which the best hypothesis for a given data set is the one that leads to the best compression of the data. …”
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    Thesis
  7. 7

    Customer mobile behavioral segmentation and analysis in telecom using machine learning by Sharaf Addin, Eman Hussein, Admodisastro, Novia Indriaty, Mohd Ashri, Siti Nur Syahirah, Kamaruddin, Azrina, Chew, Yew Chong

    Published 2021
    “…Unsupervised machine learning algorithm K-means was used to cluster the data, and these results were analyzed and labeled with labels and descriptions. …”
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    Article
  8. 8

    Brewing perfection: real-time monitoring of arabic coffee using iot and machine learning by Abuzaraida, Mustafa Ali, A. L. gaud, Sarah, Abrahim Hneish, Hamza, Attarbashi, Zainab

    Published 2026
    “…The system demonstrated high efficiency and accuracy in performance, mimicking human coffee brewing methods. The results demonstrate the potential of the YOLOv8 algorithm to automate and optimize routine tasks with high accuracy.…”
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    Proceeding Paper
  9. 9

    Genetic ensemble biased ARTMAP method of ECG-Based emotion classification by Loo, C.K., Liew, W.S., Sayeed, M.S.

    Published 2012
    “…The ARTMAP system is dependent on training sequence presentation to determine the effectiveness of the learning processes, as well as the strength of the biasing parameter, lambda λ. The optimal combination of λ and training sequence can be computed efficiently using a genetic permutation algorithm. …”
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    Conference or Workshop Item
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    Microalgae biomass and biomolecule quantification: Optical techniques, challenges and prospects by Thiviyanathan V.A., Ker P.J., Hoon Tang S.G., Amin E.P., Yee W., Hannan M.A., Jamaludin Z., Nghiem L.D., Indra Mahlia T.M.

    Published 2025
    “…This review also elucidates the potential of machine learning and big data analytics algorithms in understanding the growth and interaction of microalgae strains as well as to aid in decision making, which can possibly encourage the participation of small-scale and large-scale farmers in microalgae cultivation. …”
    Review
  12. 12

    Mean of correlation method for optimization of affective states detection in children by Rusli, Nazreen, Sidek, Shahrul Na'im, Md Yusuf, Hazlina, Ishak, Nor Izzati

    Published 2018
    “…Result from the fine k-NN classifier obtained promises the efficacy of the proposed approach to be applied in our future work in human–robot interaction for autistic children learning and training.…”
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    Article
  13. 13

    Production and characterization of biochar derived from oil palm wastes, and optimization for zinc adsorption by Zamani, Seyed Ali

    Published 2015
    “…The incremental back propagation algorithm demonstrated the best results and which has been used as learning algorithm for ANN in combination with Genetic Algorithm in the optimization. …”
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    Thesis
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    Wifi-based location-independent human activity recognition and localization using deep learning by Abuhoureyah, Fahd Saad Amed

    Published 2024
    “…First, we employ the advanced Seq2Seq Recurrent Neural Network (RNN) technique to achieve high accuracy in HAR with few layers of the Long Short-Term Memory (LSTM) algorithm. Precise activity recognition and incorporation of through-wall sensing capabilities are achieved within the deep learning framework. …”
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    Thesis
  17. 17

    Comparative study of machine learning algorithms in data classification by Tan, Kai Jun

    Published 2025
    “…This research conducts a comparative study of various machine learning algorithms for dataset classification to identify the most accurate and reliable classifier. …”
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    Final Year Project / Dissertation / Thesis
  18. 18

    Characterizing land use/land cover change dynamics by an enhanced random forest machine learning model: a Google Earth Engine implementation by Pande C.B., Srivastava A., Moharir K.N., Radwan N., Mohd Sidek L., Alshehri F., Pal S.C., Tolche A.D., Zhran M.

    Published 2025
    “…Additionally, the study incorporated the random forest (RF) algorithm. This study aimed to generate continuous LULC maps for 2014 and 2020 for the Shrirampur area of�Maharashtra, India. …”
    Article
  19. 19

    Virtual reality in algorithm programming course: practicality and implications for college students by Dewi, Ika Parma, Ambiyar, Mursyida, Lativa, Effendi, Hansi, Giatman, Muhammad, Efrizon, Hanafi, Hafizul Fahri, Ali, Siti Khadijah

    Published 2024
    “…The analysis of learning problems shows the unavailability of interactive learning media that can support various learning styles of students in programming algorithm materials. …”
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    Article
  20. 20

    VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern by Angeline Teoh, Szu Fern

    Published 2012
    “…These two models are based on topological placement method. DM is optimized using genetic algorithm (GA). …”
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    Thesis