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小波混沌神经网络模拟退火参数研究 被引量:6
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作者 徐耀群 岳海燕 《计算机工程与应用》 CSCD 北大核心 2008年第2期80-82,189,共4页
小波混沌神经网络已经成功地解决了函数优化和组合优化问题。研究了分段指数退火函数的Morlet小波混沌神经元模型,给出了分段小波混沌神经元的倒分岔图和Lyapunov指数图。在小波混沌神经网络的基础上,加入了分段指数退火函数,提出了一... 小波混沌神经网络已经成功地解决了函数优化和组合优化问题。研究了分段指数退火函数的Morlet小波混沌神经元模型,给出了分段小波混沌神经元的倒分岔图和Lyapunov指数图。在小波混沌神经网络的基础上,加入了分段指数退火函数,提出了一种新的改进的小波混沌神经网络,并把它应用到函数优化和组合优化问题中。仿真结果表明,改善了小波混沌神经网络的寻优能力,改进的小波混沌神经网络优于原来的小波混沌神经网络。 展开更多
关键词 小波混沌神经网络 LYAPUNOV指数 模拟退火参数 TSP
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Parametric optimization and performance comparison of organic Rankine cycle with simulated annealing algorithm 被引量:3
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作者 王志奇 周乃君 +2 位作者 张家奇 郭静 王晓元 《Journal of Central South University》 SCIE EI CAS 2012年第9期2584-2590,共7页
Taking the ratio of heat transfer area to net power and heat recovery efficiency into account, a multi-objective mathematical model was developed for organic Rankine cycle (ORC). Working fluids considered were R123,... Taking the ratio of heat transfer area to net power and heat recovery efficiency into account, a multi-objective mathematical model was developed for organic Rankine cycle (ORC). Working fluids considered were R123, R134a, R141b, R227ea and R245fa. Under the given conditions, the parameters including evaporating and condensing pressures, working fluid and cooling water velocities were optimized by simulated annealing algorithm. The results show that the optimal evaporating pressure increases with the heat source temperature increasing. Compared with other working fluids, R123 is the best choice for the temperature range of 100--180℃ and R141 b shows better performance when the temperature is higher than 180 ℃. Economic characteristic of system decreases rapidly with the decrease of heat source temperature. ORC system is uneconomical for the heat source temperature lower than 100℃. 展开更多
关键词 parametric optimization organic Rankine cycle simulated annealing algorithm working fluid low-temperature source
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