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‎docs/source/Footer.rst

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@@ -840,11 +840,7 @@ PyGAD 2.16.1
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Release Date: 28 September 2021
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1. Reuse the fitness of previously explored solutions rather than
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recalculating them. This feature only works if
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``save_solutions=True``.
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2. The user can use the ``tqdm`` library to show a progress bar.
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1. The user can use the ``tqdm`` library to show a progress bar.
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https://github.com/ahmedfgad/GeneticAlgorithmPython/discussions/50.
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..code::python
@@ -924,14 +920,14 @@ progress bar.
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``solutions_fitness`` array.
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https://github.com/ahmedfgad/GeneticAlgorithmPython/issues/64
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2. There was an issue of getting the length of these 4 variables
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1. There was an issue of getting the length of these 4 variables
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(``solutions``, ``solutions_fitness``, ``best_solutions``, and
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``best_solutions_fitness``) doubled after each call of the ``run()``
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method. This is solved by resetting these variables at the beginning
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of the ``run()`` method.
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https://github.com/ahmedfgad/GeneticAlgorithmPython/issues/62
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3. Bug fixes when adaptive mutation is used
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2. Bug fixes when adaptive mutation is used
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(``mutation_type="adaptive"``).
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https://github.com/ahmedfgad/GeneticAlgorithmPython/issues/65
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@@ -1471,6 +1467,34 @@ A number of research papers used PyGAD and here are some of them:
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Cobertura em Redes Militarizadas 4G/LTE. In *Anais do XXVI Workshop
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de Gerência e Operação de Redes e Serviços* (pp. 152-165). SBC.
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- M. Yani, F. Ardilla, A. A. Saputra and N. Kubota, "Gradient-Free Deep
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Q-Networks Reinforcement learning: Benchmark and Evaluation," *2021
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IEEE Symposium Series on Computational Intelligence (SSCI)*, 2021,
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pp. 1-5, doi: 10.1109/SSCI50451.2021.9659941.
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- Yani, Mohamad, and Naoyuki Kubota. "Deep Convolutional Networks with
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Genetic Algorithm for Reinforcement Learning Problem."
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- Mahendra, Muhammad Ihza, and Isman Kurniawan. "Optimizing
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Convolutional Neural Network by Using Genetic Algorithm for COVID-19
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Detection in Chest X-Ray Image." *2021 International Conference on
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Data Science and Its Applications (ICoDSA)*. IEEE, 2021.
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- Glibota, Vjeko. *Umjeravanje mikroskopskog prometnog modela primjenom
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genetskog algoritma*. Diss. University of Zagreb. Faculty of
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Transport and Traffic Sciences. Division of Intelligent Transport
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Systems and Logistics. Department of Intelligent Transport Systems,
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2021.
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- Zhu, Mingda. *Genetic Algorithm-based Parameter Identification for
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Ship Manoeuvring Model under Wind Disturbance*. MS thesis. NTNU,
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2021.
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- Abdalrahman, Ahmed, and Weihua Zhuang. "Dynamic pricing for
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differentiated pev charging services using deep reinforcement
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learning." *IEEE Transactions on Intelligent Transportation Systems*
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(2020).
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More Links
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==========
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