Search Results - (( java application optimization algorithm ) OR ( sensing using optimisation algorithm ))

Refine Results
  1. 1
  2. 2

    Performance evaluation of real-time multiprocessor scheduling algorithms by Alhussian, H., Zakaria, N., Abdulkadir, S.J., Fageeri, S.O.

    Published 2016
    “…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
    Get full text
    Get full text
    Conference or Workshop Item
  3. 3

    Route Optimization System by Zulkifli, Abdul Hayy

    Published 2005
    “…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
    Get full text
    Get full text
    Final Year Project
  4. 4
  5. 5

    Speech enhancement based on compressive sensing algorithm by Sulong, Amart, Gunawan, Teddy Surya, Khalifa, Othman Omran, Chebil, Jalel

    Published 2013
    “…The performance of overall algorithms will be evaluated based on the speech quality by optimise using informal listening test and Perceptual Evaluation of Speech Quality (PESQ). …”
    Get full text
    Get full text
    Get full text
    Get full text
    Proceeding Paper
  6. 6
  7. 7

    Speech enhancement based on compressive sensing algorithm by Sulong, Amart, Gunawan, Teddy Surya, Khalifa, Othman Omran, Chebil , Jalel

    Published 2013
    “…The performance of overall algorithms will be evaluated based on the speech quality by optimise using informal listening test and Perceptual Evaluation of Speech Quality (PESQ). …”
    Get full text
    Get full text
    Get full text
    Article
  8. 8

    Ocean Colour Remote Sensing Of Case 2 Waters Using An Optimised Neural Network by Anwar, Saumi Syahreza

    Published 2016
    “…This study focused on the development of the new algorithm for retrieving ocean colour products of Case 2 water types using the neural network (NN) model and multiple types of remotely sensed data as inputs. …”
    Get full text
    Get full text
    Thesis
  9. 9
  10. 10
  11. 11

    Efficient and secured compression and steganography technique in wireless sensor network by Tuama, Ammar Yaseen

    Published 2016
    “…Second, an improved steganographic algorithm based on the infamous Least Significant Bit (LSB) is proposed for hiding the sensed data scheduled for transmission. …”
    Get full text
    Get full text
    Get full text
    Thesis
  12. 12

    Computer Lab Timetabling Using Genetic Algorithm Case Study - Unit ICT by Abdullah, Amran

    Published 2006
    “…Genetic Algorithm is one of the most popular optimization solutions used in various applications such as scheduling. …”
    Get full text
    Get full text
    Thesis
  13. 13
  14. 14
  15. 15

    Examination timetabling using genetic algorithm case study: KUiTTHO by Mohd Salikon, Mohd Zaki

    Published 2005
    “…Genetic Algorithm (GA) is one of the most popular optimization solutions. …”
    Get full text
    Get full text
    Thesis
  16. 16

    Examination Timetabling Using Genetic Algorithm Case Study : KUiTTHO by Mohd. Zaki, Mohd. Salikon

    Published 2005
    “…Genetic Algorithm (GA) is one of the most popular optimization solutions. …”
    Get full text
    Get full text
    Get full text
    Thesis
  17. 17

    Improving Class Timetabling using Genetic Algorithm by Qutishat, Ahmed Mohammed Ali

    Published 2006
    “…We have targeted the research on class timetabling problem. Hence, Genetic Algorithm (GA) is used as one of the most popular optimization solutions. …”
    Get full text
    Get full text
    Get full text
    Thesis
  18. 18
  19. 19
  20. 20

    Oil palm mapping over Peninsular Malaysia using Google Earth Engine and machine learning algorithms by Shaharum, Nur Shafira Nisa, Mohd Shafri, Helmi Zulhaidi, Wan Ab. Karim Ghani, Wan Azlina, Samsatli, Sheila, Al-Habshi, Mohammed Mustafa, Yusuf, Badronnisa

    Published 2020
    “…In this study, 30 m Landsat 8 data were processed using a cloud computing platform of Google Earth Engine (GEE) in order to classify oil palm land cover using non-parametric machine learning algorithms such as Support Vector Machine (SVM), Classification and Regression Tree (CART) and Random Forest (RF) for the first time over Peninsular Malaysia. …”
    Get full text
    Get full text
    Get full text
    Article