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p50
fuzzy algorithm very simila to use
- 2010-08-02 10:09:38下载
- 积分：1
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brownianbridge
An example case is considered to price an option at a maturity of T years - prices are simulated for Geometric brownian motion process at 2*T maturity, and Brownian Bridge is used to obtain prices at T maturity. Finally option prices are compared to Black Scholes values to verify results(An example case is considered to price an option at a maturity of T years- prices are simulated for Geometric brownian motion process at 2*T maturity, and Brownian Bridge is used to obtain prices at T maturity. Finally option prices are compared to Black Scholes values to verify results)
- 2009-03-23 22:29:02下载
- 积分：1
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wfPNN
说明： PNN的程序，经过验证的，很好使，希望对大家有所帮助！(PNN procedure, proven, well so, we want to help!
)
- 2011-04-13 22:16:30下载
- 积分：1
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137611
convetible bond pricing , use different code to price, crr model
- 2012-05-30 16:40:14下载
- 积分：1
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lab-1
Power World simulation
- 2013-04-26 04:50:43下载
- 积分：1
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mat
matlab simulink 模糊控制器模型(matlab simulink fuzzy controller model)
- 2014-01-17 10:21:25下载
- 积分：1
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MATLABimage
matlab image process，很是不错的，兴旺对大家有所参考，大家共享下呵(matlab image process, it is a good and prosperous for all of us have a reference, we share Oh)
- 2008-01-28 12:06:08下载
- 积分：1
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col2im
用C语言编写MATLAB 函数， 以用于DSP芯片上(Use the programming language C to write MATLAB function, col2im )
- 2014-12-17 12:22:12下载
- 积分：1
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csvs
基于改进差分演化算法的石油层评价指标的特征选择(Feature improved oil layer evaluation based on differential evolution algorithm choice)
- 2013-12-12 19:25:00下载
- 积分：1
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Main
Abstract—Demand Response (DR) and Time-of-Use (TOU)
pricing refer to programs which offer incentives to customers
who curtail their energy use during times of peak demand. In this
paper, we propose an integrated solution to predict and re-engineer
the electricity demand (e.g., peak load reduction and shift) in
a locality at a given day/time. The system presented in this paper
expands DR to residential loads by dynamically scheduling and
controlling appliances in each dwelling unit. A decision-support
system is developed to forecast electricity demand in the home and
enable the user to save energy by recommending optimal run time
schedules for appliances, given user constraints and TOU pricing
the utility company. The schedule is communicated to the
smart appliances over a self-organizing home energy network
and d by the appliance control interfaces developed in this
- 2020-09-23 09:57:52下载
- 积分：1
