Search Results - (( java segmentation using algorithm ) OR ( using practical evolutionary algorithm ))

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  1. 1

    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…Finally, the algorithm found, which would solve the image segmentation problem.…”
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    Thesis
  2. 2

    Evolutionary multi-objective optimization of autonomous mobile robots in neural-based cognition for behavioural robustness by Chin, Kim On, Teo, Jason Tze Wi, Azali Saudi

    Published 2009
    “…It explains the comparison performances among the elitism without archive and elitism with archive used in the evolutionary multi-objective optimization (EMO) algorithm in an evolutionary robotics study. …”
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    Chapter In Book
  3. 3

    Automatic Number Plate Recognition on android platform: With some Java code excerpts by ., Abdul Mutholib, Gunawan, Teddy Surya, Kartiwi, Mira

    Published 2016
    “…On the other hand, the traditional algorithm using template matching only obtained 83.65% recognition rate with 0.97 second processing time. …”
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    Book
  4. 4

    A comprehensive comparison of evolutionary optimization limited by number of evaluations against time constraints by Jia, Hui Ong, Teo, Jason Tze Wi

    Published 2016
    “…In this study, the importance of optimization problems constrained by time is highlighted. Practically allevolutionary optimization studies have focused exclusively on the use of number of fitness evaluations as the constraining factor when comparing different evolutionary algorithms (EAs). …”
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    Article
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    Multi -Objective Economic Dispatch Using Evolutionary Programming by Noor Azlan Bin Adnan

    Published 2023
    “…This study focused on solving multi-objectives economic dispatch using Heuristic Optimization (HO) technique which is Multi-Objective Evolutionary Programming (MOEP). …”
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    Enhanced multi-objective evolutionary mating algorithm with improved crowding distance and levy flight for optimizing comfort index and energy consumption in smart buildings by Muhammad Naim, Nordin, Mohd Herwan, Sulaiman, Nor Farizan, Zakaria, Zuriani, Mustaffa

    Published 2025
    “…These enhancements enable MOEMA to effectively navigate complex multi-objective landscapes, leading to more diverse and well-converged Pareto-optimal solutions. The algorithm's performance is thoroughly assessed using the chosen benchmark functions and validated through practical applications in smart building environments. …”
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    Article
  9. 9

    Automatic generation of neural game controller using single and bi-objective evolutionary optimization algorithms for RTS Game by Chang, Kee Tong

    Published 2015
    “…After determine the rates another single objectives algorithm is tested. Hence, the second sub-objective is 2) to evolve RTS controllers using DE and FFNN. …”
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    Thesis
  10. 10

    Artificial Neural Controller Synthesis in Autonomous Mobile Cognition by Kim On Chin, Jason Teo

    Published 2009
    “…The testing results also showed that the robot was robust to these different environments used during the testing phases. Hence, the results demonstrated that the utilization of the evolutionary multi-objective approach in evolutionary robotics can be practically used to generate controllers for phototaxis and RF-localization behaviors in autonomous mobile robots.…”
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    Article
  11. 11

    Artificial Neural Controller Synthesis in Autonomous Mobile Cognition by Chin Kim On, Jason Teo

    Published 2009
    “…The testing results also showed that the robot was robust to these different environments used during the testing phases. Hence, the results demonstrated that the utilization of the evolutionary multi-objective approach in evolutionary robotics can be practically used to generate controllers for phototaxis and RF-localization behaviors in autonomous mobile robots…”
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    Article
  12. 12

    An efficient anomaly intrusion detection method with feature selection and evolutionary neural network by Sarvari, Samira, Mohd Sani, Nor Fazlida, Mohd Hanapi, Zurina, Abdullah @ Selimun, Mohd Taufik

    Published 2020
    “…A proposed model has been practically used to the problem of intrusion detection as well as been validated using the NSL-KDD dataset. …”
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    Article
  13. 13

    Development of a Bioinspired optimization algorithm for the automatic generation of multiple distinct behaviors in simulated mobile robots by Hanafi Ahmad Hijazi, Patricia Anthony

    Published 2006
    “…As a result, this study has thus shown that the multi-objective approach to evolutionary robotics in the form of the elitist PDE-EMO algorithm can be practically used to automatically generate controllers for RF-Iocalization behavior in autonomous mobile robots.…”
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    Research Report
  14. 14

    Optimizing LSTM S2S models with Evolutionary Mating Algorithm (EMA) for direct multi-step forecasting of household electrical power consumption by Al Mamun, Md Habib, Zuriani, Mustaffa, Junaida, Sulaiman, Mohd Herwan, Sulaiman

    Published 2026
    “…Future work will expand the scope using diverse datasets, longer forecast horizons, and integration of renewable energy sources for more practical and scalable solutions.…”
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    Conference or Workshop Item
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    Two level Differential Evolution algorithms for ARMA parameters estimatio by Salami, Momoh Jimoh Emiyoka, Tijani, Ismaila, Aibinu, Abiodun Musa

    Published 2013
    “…The performance of the algorithm is evaluated using both simulated ARMA models and practical rotary motion system. …”
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    Proceeding Paper
  17. 17

    Hybrid evolutionarybarnacles mating optimisation-artificial neural network based technique for solving economic power dispatch planning and operation / Nor Laili Ismail by Ismail, Nor Laili

    Published 2024
    “…In this study, a new optimisation algorithm termed Hybrid Evolutionary-Barnacles Mating Optimisation (HEBMO) was initially formulated to solve optimisation problems. …”
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    Thesis
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    An efficient anomaly intrusion detection method with evolutionary neural network by Sarvari, Samira

    Published 2020
    “…The third proposed method is a new Evolutionary Neural Network (ENN) algorithm with a combination of Genetic Algorithm and Multiverse Optimizer (GAMVO) as a training part of ANN to create efficient anomaly-based detection with low false alarm rate. …”
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    Thesis
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