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  1. 1
    The Implementation of Genetic Algorithm in Path Optimization

    The Implementation of Genetic Algorithm in Path Optimization by Jumali, Suriana

    Published 2005
    “…Therefore, the implementation ofGA in path optimization can be ascertained offering a compelling result.…”
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  2. 2
    Path optimization using genetic algorithm in laser scanning system

    Path optimization using genetic algorithm in laser scanning system by Chen, Chai Phing, Koh, Johnny Siaw Paw, Aris, Ishak, Fong, Albert Yu Chooi, Tiong, Sieh Kiong

    Published 2008
    “…In this paper, the genetic algorithm (GA) has been proposed to optimize the scanning sequence, thus shortening the required laser scanning path. …”
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  3. 3
    Path optimization using genetic algorithm in laser scanning system

    Path optimization using genetic algorithm in laser scanning system by Chen C.P., Koh S.P., Aris I.B., Albert F.Y.C., Tiong S.K.

    Published 2023
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  4. 4
    A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments

    A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments by Khaksar, Weria

    Published 2013
    “…Finally, an adaptive neuro-fuzzy inference system (ANFIS) was designed which constructs and optimizes a fuzzy logic controller using a given dataset of input/output variables in order to increase the optimality and stability rates of the proposed path planning algorithm. …”
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  5. 5
    Systematic design of chemical reactors with multiple stages via multi-objective optimization approach

    Systematic design of chemical reactors with multiple stages via multi-objective optimization approach by Mohd Fuad, Mohd Nazri, Hussain, Mohd Azlan

    Published 2015
    “…Following the identification of path-dependent design variables, several (possibly conflicting) design objectives will be selected and solutions of the corresponding problem will be generated from multi-objective optimization algorithm. …”
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  6. 6
    Runtime reduction in optimal multi-query sampling-based motion planning

    Runtime reduction in optimal multi-query sampling-based motion planning by Khaksar W., Sahari K.S.B.M., Ismail F.B., Yousefi M., Ali M.A.

    Published 2023
    Conference Paper
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  7. 7
    Differential evolution for neural networks learning enhancement

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

    Published 2008
    “…Evolutionary computation is the name given to a collection of algorithms based on the evolution of a population toward a solution of a certain problem. …”
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  8. 8
    A New Quadratic Binary Harris Hawk Optimization For Feature Selection

    A New Quadratic Binary Harris Hawk Optimization For Feature Selection by Abdullah, Abdul Rahim, Too, Jing Wei, Mohd Saad, Norhashimah

    Published 2019
    “…In this study, twenty-two datasets collected from the UCI machine learning repository are used to validate the performance of proposed algorithms. A comparative study is conducted to compare the effectiveness of QBHHO with other feature selection algorithms such as binary differential evolution (BDE), genetic algorithm (GA), binary multi-verse optimizer (BMVO), binary flower pollination algorithm (BFPA), and binary salp swarm algorithm (BSSA). …”
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  9. 9
    Algorithmic design issues in adaptive differential evolution schemes: Review and taxonomy

    Algorithmic design issues in adaptive differential evolution schemes: Review and taxonomy by Al-Dabbagh, Rawaa Dawoud, Neri, Ferrante, Idris, Norisma, Baba, Mohd Sapiyan

    Published 2018
    “…A trend that has emerged recently is to make the algorithm parameters automatically adapt to different problems during optimization, thereby liberating the user from the tedious and time-consuming task of manual setting. …”
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  10. 10
    Feature selection optimization using hybrid relief-f with self-adaptive differential evolution

    Feature selection optimization using hybrid relief-f with self-adaptive differential evolution by Zainudin, Muhammad Noorazlan Shah, Sulaiman, Md. Nasir, Mustapha, Norwati, Perumal, Thinagaran, Ahmad Nazri, Azree Shahrel, Mohamed, Raihani, Abd Manaf, Syaifulnizam

    Published 2017
    “…Hence, feature selection is embedded to select the most meaningful features based on their rank. Differential evolution (DE) is one of the evolutionary algorithms that are widely used in various classification domains. …”
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  11. 11
    Artificial fish swarm optimization for multilayer network learning in classification problems

    Artificial fish swarm optimization for multilayer network learning in classification problems by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam

    Published 2012
    “…Artificial Fish Swarm Algorithm (AFSA) as one of the NIC methods is widely used for optimizing the global searching of ANN.In this study, we applied the AFSA method to improve the Multilayer Perceptron (MLP) learning for promising accuracy in various classification problems.The parameters of AFSA: AFSA prey, AFSA swarm and AFSA follow are implemented on the MLP network for improving the accuracy of various classification datasets from UCI machine learning. …”
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  12. 12
    Artificial Fish Swarm Optmization for Multilayernetwork Learning in Classification Problems

    Artificial Fish Swarm Optmization for Multilayernetwork Learning in Classification Problems by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam, Sallehuddin, Roselina

    Published 2012
    “…In this study, we applied the AFSA method to improve the Multilayer Perceptron (MLP) learning for promising accuracy in various classification problems. The parameters of AFSA: AFSA prey, AFSA swarm and AFSA follow are implemented on the MLP network for improving the accuracy of various classification datasets from UCI machine learning. …”
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  13. 13
    A multi-objective parametric algorithm for sensor-based navigation in uncharted terrains

    A multi-objective parametric algorithm for sensor-based navigation in uncharted terrains by Khaksar W., Sahari K.S.M.

    Published 2023
    “…However, these approaches only focus on one single objective, i.e. path optimality, path safety, efficiency or trajectory smoothness. …”
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  14. 14
    Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals

    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. …”
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  15. 15
    Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh

    Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh by Rawaa Dawoud Hassan, Al-Dabbagh

    Published 2015
    “…Differential evolution (DE) is a simple yet powerful evolutionary algorithm (EA). …”
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  16. 16
    Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm

    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.…”
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  17. 17
    Improving Ant Swarm Optimization With Embedded Vaccination For Optimum Reducts Generation

    Improving Ant Swarm Optimization With Embedded Vaccination For Optimum Reducts Generation by Pratiwi, Lustiana, Choo, Yun Huoy, Draman @ Muda, Azah Kamilah, Draman @ Muda, Noor Azilah

    Published 2011
    “…Unlike a conventional PSOIACO algorithm, this hybrid algorithm shows improvement of the classification accuracy in its generated rough reducts to solve NP-Hard problem. …”
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  18. 18
    Literature Review of Optimization Techniques for Chatter Suppression In Machining

    Literature Review of Optimization Techniques for Chatter Suppression In Machining by A. R., Yusoff, Mohamed Reza Zalani, Mohamed Suffian, Mohd Yusof, Taib

    Published 2011
    “…In this paper, it can be observed that for chatter suppression, optimization focuses on spindle design, tool path, cutting process, and variable pitch. …”
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  19. 19
    Interference avoidance routing and scheduling using multiple transceivers for IEEE 802.16 mesh network

    Interference avoidance routing and scheduling using multiple transceivers for IEEE 802.16 mesh network by Qasem, Yaaqob Ali Ahmed

    Published 2010
    “…Here, a routing tree is constructed based on the energy/bit minimization routing (EbMR). This algorithm looks for a short path from the subscriber station (SS) node to BS, while the optimal path is achieved when the whole path has the lowest EbMR. …”
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  20. 20
    A New Co-Evolution Binary Particle Swarm Optimization With Multiple Inertia Weight Strategy For Feature Selection

    A New Co-Evolution Binary Particle Swarm Optimization With Multiple Inertia Weight Strategy For Feature Selection by Too, Jing Wei, Abdullah, Abdul Rahim, Mohd Saad, Norhashimah

    Published 2019
    “…Therefore, this study aims to solve the feature selection problem using binary particle swarm optimization (BPSO). …”
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