Chaotic neural networks for optimization
Optimization technology is a powerful tool for management modernization. In modern science and technology, many problems can be solved by chaotic neural networks (CNN). Many previous scholars have studied many excellent optimization algorithms. Nowadays, the optimization technology based on chaotic...
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Nanyang Technological University
2022
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sg-ntu-dr.10356-1556472023-07-04T17:36:17Z Chaotic neural networks for optimization Feng, Jiancong Anamitra Makur School of Electrical and Electronic Engineering EAMakur@ntu.edu.sg Engineering::Electrical and electronic engineering Optimization technology is a powerful tool for management modernization. In modern science and technology, many problems can be solved by chaotic neural networks (CNN). Many previous scholars have studied many excellent optimization algorithms. Nowadays, the optimization technology based on chaotic neural network has become one of the popular technologies. This dissertation takes chaotic neural networks as the main research object, understands the key indicators of CNN optimization, reviews the model development of Transient CNN, studies the improvement methods and principles of TCNN, and compares TCNN with Noisy CNN. The optimization mechanism of the TCNN is analyzed, and the simulation results of its application in the Traveling Salesman Problem are studied. Keywords: TCNN; optimization; TSP Master of Science (Signal Processing) 2022-03-10T04:16:29Z 2022-03-10T04:16:29Z 2021 Thesis-Master by Coursework Feng, J. (2021). Chaotic neural networks for optimization. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/155647 https://hdl.handle.net/10356/155647 en application/pdf Nanyang Technological University |
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Engineering::Electrical and electronic engineering Feng, Jiancong Chaotic neural networks for optimization |
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Optimization technology is a powerful tool for management modernization. In modern science and technology, many problems can be solved by chaotic neural networks (CNN). Many previous scholars have studied many excellent optimization algorithms. Nowadays, the optimization technology based on chaotic neural network has become one of the popular technologies.
This dissertation takes chaotic neural networks as the main research object, understands the key indicators of CNN optimization, reviews the model development of Transient CNN, studies the improvement methods and principles of TCNN, and compares TCNN with Noisy CNN. The optimization mechanism of the TCNN is analyzed, and the simulation results of its application in the Traveling Salesman Problem are studied.
Keywords: TCNN; optimization; TSP |
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Anamitra Makur |
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Anamitra Makur Feng, Jiancong |
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Thesis-Master by Coursework |
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Feng, Jiancong |
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Feng, Jiancong |
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Chaotic neural networks for optimization |
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Chaotic neural networks for optimization |
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Chaotic neural networks for optimization |
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Chaotic neural networks for optimization |
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Chaotic neural networks for optimization |
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chaotic neural networks for optimization |
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Nanyang Technological University |
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2022 |
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https://hdl.handle.net/10356/155647 |
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