Search Results - (( evolution evaluation method algorithm ) OR ( parameter active learning algorithm ))

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  1. 1
    Enhancing Wearable-Based Human Activity Recognition with Binary Nature-Inspired Optimization Algorithms for Feature Selection

    Enhancing Wearable-Based Human Activity Recognition with Binary Nature-Inspired Optimization Algorithms for Feature Selection by Norfadzlan, Yusup, Izzatul Nabila, Sarbini, Dayang Nurfatimah, Awang Iskandar, Azlan, Mohd Zain, Didik Dwi, Prasetya

    Published 2026
    “…The experiment results show how these algorithms could be used to improve methods for recognizing human activities using wearables technology, such as feature selection, parameter adjustment, and model optimization.…”
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  2. 2
    Voltage stability margin identification using evolution programming learning algorithm / Zamzuhairi Darus

    Voltage stability margin identification using evolution programming learning algorithm / Zamzuhairi Darus by Darus, Zamzuhairi

    Published 2003
    “…This project proposed on an investigation on the voltage stability margin identification using evolution programming learning algorithm. A multilayer feed-forward artificial neural network (ANN) with evolution programming learning algorithm for calculation of voltage stability margins (VSM). …”
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  3. 3
    Parameter extraction of photovoltaic module using hybrid evolutionary algorithm

    Parameter extraction of photovoltaic module using hybrid evolutionary algorithm by Muhsen D.H., Ghazali A.B., Khatib T.

    Published 2023
    Conference Paper
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  4. 4
    Optimisation of Biochemical Systems Production using Hybrid of Newton Method, Differential Evolution Algorithm and Cooperative Coevolution Algorithm

    Optimisation of Biochemical Systems Production using Hybrid of Newton Method, Differential Evolution Algorithm and Cooperative Coevolution Algorithm by Mohd Arfian, Ismail, Mezhuyev, Vitaliy, Kohbalan, Moorthy, Shahreen, Kasim, Ashraf Osman, Ibrahim

    Published 2017
    “…This paper present a hybrid method of Newton method, Differential Evolution Algorithm (DE) and Cooperative Coevolution Algorithm (CCA). …”
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  5. 5
    A harmony search-based learning algorithm for epileptic seizure prediction

    A harmony search-based learning algorithm for epileptic seizure prediction by Kee, Huong Lai, Zainuddin, Zarita, Ong, Pauline

    Published 2016
    “…The learning phase of wavelet neural network entails the task of finding the optimal set of parameter, which includes wavelet activation function, translation centers, dilation parameter, synaptic weight values, and bias terms. …”
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  6. 6
    The effect of adaptive parameters on the performance of back propagation

    The effect of adaptive parameters on the performance of back propagation by Abdul Hamid, Norhamreeza

    Published 2012
    “…The activation functions are adjusted by the adaptation of gain parameters together with adaptive momentum and learning rate value during the learning process. …”
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  7. 7
    Modeling time series data using Genetic Algorithm based on Backpropagation Neural network

    Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

    Published 2018
    “…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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  8. 8
    Acceleration Strategies For The Backpropagation Neural Network Learning Algorithm

    Acceleration Strategies For The Backpropagation Neural Network Learning Algorithm by Zainuddin, Zarita

    Published 2001
    “…The backpropagation algorithm has proven to be one of the most successful neural network learning algorithms. …”
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  9. 9
    Class binarization with self-adaptive algorithm to improve human activity recognition

    Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…WISDM consists of six different types physical activity, while PAMAP2 covers eighteen activities comprising various simple and complex activities. …”
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  10. 10
    Active force control with iterative learning control algorithm for a vehicle suspension

    Active force control with iterative learning control algorithm for a vehicle suspension by Rosmazi, Rosli

    Published 2013
    “…The new control scheme named active force control with iterative learning control algorithm (AFCIL) is complemented by the classic proportionalintegral-derivative (PID) control incorporated and designed as the outermost control loop. …”
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  11. 11
    Multi-objective Optimization of Biochemical System Production Using an Improve Newton Competitive Differential Evolution Method

    Multi-objective Optimization of Biochemical System Production Using an Improve Newton Competitive Differential Evolution Method by Mohd Arfian, Ismail, Mezhuyev, Vitaliy, Safaai, Deris, Mohd Saberi, Mohamad, Shahreen, Kasim, Saedudin, Rd Rohmat

    Published 2017
    “…Due to that, this study proposed and improved a method that comprises with Newton method, differential evolution algorithm (DE) and competitive co-evolutionary algorithm(ComCA). …”
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  12. 12
    LEMABE: a novel framework to Improve analogy-based software cost estimation using learnable evolution model

    LEMABE: a novel framework to Improve analogy-based software cost estimation using learnable evolution model by Dashti, Maedeh, Gandoman, Taghi Javdani, Adeh, Dariush Hasanpoor, Zulzalil, Hazura, Md Sultan, Abu Bakar

    Published 2021
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  13. 13
    Channel-aware downlink scheduling for quality of service in long term evolution network

    Channel-aware downlink scheduling for quality of service in long term evolution network by Najim, Alaa Omer

    Published 2018
    “…The proposed algorithm using system-level simulation experiments with performance comparison with DBWPF in terms of end-to-end delay, fairness, system throughput, Packet Loss Ratio (PLR), and spectral efficiency was evaluated. …”
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  14. 14
    Intelligent adaptive active force control of a robotic arm with embedded iterative learning algorithms

    Intelligent adaptive active force control of a robotic arm with embedded iterative learning algorithms by Mailah, Musa, Ong, Miaw Yong

    Published 2001
    “…The paper highlights a novel and robust method to control a robotic arm using an iterative learning technique embedded in an active force control strategy. …”
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  15. 15
    Activity recognition using optimized reduced kernel extreme learning machine (OPT-RKELM) / Yang Dong Rui

    Activity recognition using optimized reduced kernel extreme learning machine (OPT-RKELM) / Yang Dong Rui by Yang , Dong Rui

    Published 2019
    “…One of the major research problems is the computation resources required by machine learning algorithm used for classification for HAR. …”
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  16. 16
    Adaptive active force control of a robotic arm employing twin iterative learning algorithms / Musa Mailah and Ong Miaw Yong

    Adaptive active force control of a robotic arm employing twin iterative learning algorithms / Musa Mailah and Ong Miaw Yong by Mailah, Musa, Ong, Miaw Yong

    Published 2004
    “…The paper highlights a novel and robust method to control a robotic arm using iterative learning technique embedded in an active force control strategy. …”
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  17. 17
    PROPOSED METHODOLOGY FOR OPTIMIZING THE TRAINING PARAMETERS OF A MULTILAYER FEED-FORWARD ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM

    PROPOSED METHODOLOGY FOR OPTIMIZING THE TRAINING PARAMETERS OF A MULTILAYER FEED-FORWARD ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM by ABDALLA, OSMAN AHMED

    Published 2011
    “…To overcome these limitations, there have been attempts to use genetic algorithm (GA) to optimize some of these parameters. …”
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  18. 18
    Differential evolution for neural networks learning enhancement

    Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

    Published 2008
    “…In ANN, there are many elements need to be considered, and these include the number of input nodes, hidden nodes, output nodes, learning rate, momentum rate, bias parameter, minimum error and activation/transfer functions. …”
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  19. 19
    Data depublication using : Hashing algorithm / Naimah Nayan

    Data depublication using : Hashing algorithm / Naimah Nayan by Nayan, Naimah

    Published 2019
    “…The recommendation for future work is to evaluate various type of data and different type of hashing algorithm.…”
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  20. 20
    Particle swarm optimization for neural network learning enhancement

    Particle swarm optimization for neural network learning enhancement by Abdull Hamed, Haza Nuzly

    Published 2006
    “…To overcome this problem, Genetic Algorithm (GA) has been used to determine optimal value for BP parameters such as learning rate and momentum rate and also for weight optimization. …”
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