Search Results - (( evolution classification system algorithm ) OR ( data equalization based algorithm ))

Refine Results
  1. 1

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

    Published 2012
    “…The proposed system utilizes Biased ARTMAP for pattern learning and classification. …”
    Get full text
    Get full text
    Conference or Workshop Item
  2. 2
  3. 3

    Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals by Too, Jing Wei

    Published 2020
    “…Therefore, this thesis aims to solve the feature selection problem in EMG signals classification and improve the classification performance of EMG pattern recognition system. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  4. 4
  5. 5
  6. 6
  7. 7

    An improved method using fuzzy system based on hybrid boahs for phishing attack detection by Noor Syahirah, Nordin

    Published 2022
    “…The algorithms involved were Genetic Algorithm, Differential Evolution Algorithm, Particle Swarm Optimization, Butterfly Optimization Algorithm, Teaching-Learning-Based Optimization Algorithm, Harmony Search Algorithm and Gravitational Search Algorithm. …”
    Get full text
    Get full text
    Thesis
  8. 8
  9. 9

    Reduced rank technique for joint channel estimation and joint data detection in TD-SCDMA systems by Marzook, Ali Kamil, Ismail, Alyani, Mohd Ali, Borhanuddin, Sali, Aduwati, Khalaf, Mohannad H., Khatun, Sabira

    Published 2013
    “…The detectors: zero forcing block linear equalizer and minimum mean square error block linear equalizer algorithms are considered in this paper to recover the data. …”
    Get full text
    Get full text
    Article
  10. 10

    Fault tolerance structures in Wireless Sensor Networks (WSNs): survey, classification, and future directions by Adday, Ghaihab Hassan, K. Subramaniam, Shamala, Ahmad Zukarnain, Zuriati, Samian, Normalia

    Published 2022
    “…Thus, the respective underlying Fault Tolerance (FT) structure is a critical requirement that needs to be considered when designing any algorithm in WSNs. Moreover, with the exponential evolution of IoT systems, substantial enhancements of current FT mechanisms will ensure that the system constantly provides high network reliability and integrity. …”
    Get full text
    Get full text
    Article
  11. 11

    Reduced Rank Technique for Joint Channel Estimation and Joint Data Detection in TD-SCDMA Systems by Sabira, Khatun, Ali K., Marzook, Alyani, Ismail, Aduwati, Sali, Mohannad Hamed, Khalaf, Borhan, M. Ali

    Published 2012
    “…The detectors: zero forcing block linear equalizer and minimum mean square error block linear equalizer algorithms are considered in this paper to recover the data. …”
    Get full text
    Get full text
    Article
  12. 12

    Deep learning detector for pests and plant disease recognition by Ileladewa, Oluwatimilehin Adekunle

    Published 2020
    “…And developing a quick and accurate model could help in detecting pests and diseases in plants. Meanwhile, evolution in deep convolutional neural networks for image classification has rapidly improved the accuracy of object detection, classification and system recognition. …”
    Get full text
    Get full text
    Final Year Project / Dissertation / Thesis
  13. 13

    Reduced-rank technique for joint channel estimation in TD-SCDMA systems. by Ismail, Alyani, Sali, Aduwati, Mohd Ali, Borhanuddin, Khatun, Sabira

    Published 2013
    “…The detectors: zero forcing block linear equalizer and minimum mean square error block linear equalizer algorithms are considered in this paper to recover the data. …”
    Get full text
    Get full text
    Article
  14. 14

    Improved power output forecastingtechnique for effective battery management in photovoltaic system / Utpal Kumar Das by Utpal, Kumar Das

    Published 2019
    “…A PSO-based algorithm is adopted for the appropriate selection of dominated parameters of SVR-based model to achieve better performance. …”
    Get full text
    Get full text
    Get full text
    Thesis
  15. 15

    Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam, Sallehuddin, Roselina

    Published 2011
    “…Artificial Neural Network (ANN) is a new information processing system with large quantity of highly interconnected neurons or elements processing parallel to solve problems.Recently, evolutionary computation technique, Artificial Fish Swarm Algorithm (AFSA) is chosen to optimize global searching of ANN.In optimization process, each Artificial Fish (AF) represents a neural network with output of fitness value.The AFSA is used in this study to analyze its effectiveness in enhancing Multilayer Perceptron (MLP) learning compared to Particle Swarm Optimization (PSO) and Differential Evolution (DE) for classification problems.The comparative results indeed demonstrate that AFSA show its efficient, effective and stability in MLP learning.…”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  16. 16

    Segmentation of MRI brain images using statistical approaches by Balafar, Mohammad Ali

    Published 2011
    “…Therefore, these algorithms can be improved upon. A neighbourhood-based noise-reduction algorithm which uses the edges of an image is proposed. …”
    Get full text
    Get full text
    Thesis
  17. 17

    Enhanced handover decision algorithm in heterogeneous wireless network by Abdullah, Radhwan Mohammed, Ahmad Zukarnain, Zuriati

    Published 2017
    “…It also employs three types of vertical handover decision algorithms: equal priority, mobile priority and network priority. …”
    Get full text
    Get full text
    Get full text
    Article
  18. 18

    A comparison of watermarking image quality based on dual intermediate significant bit with genetic algorithm by Yasin, Azman, M. Zeki, Akram, Mohammed, Ghassan N.

    Published 2013
    “…In this case, when the two hidden bits are equal to the original bits, there will be no change to the other remaining bits.However, if the original value is not equal to the embedded one, the nearest pixel to the original one will be chosen as the watermarked image.The second method, GA method is used to embed two bits of watermarking data within every pixel of the original image and to find the optimal value based on the existing DISB.On the other hand, if the two embedded bits are equal to the original bits then this means the watermarked image is still the same as the original one without any changes, while in the other case GA is used in determining the minimum fitness value in which the fittest is the absolute value between the pixel and chromosome and the value of chromosome between 0-255.The results indicate that the two methods produce a high quality watermarked image, but there is a big difference in the processing time, so the DISB method is faster than the GA method.…”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  19. 19
  20. 20