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Title: Chaotic neural networks for optimization
Authors: Feng, Jiancong
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2021
Publisher: Nanyang Technological University
Source: Feng, J. (2021). Chaotic neural networks for optimization. Master's thesis, Nanyang Technological University, Singapore.
Abstract: 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
Schools: School of Electrical and Electronic Engineering 
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Theses

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