Cephalosporin C fed-batch cultivation undergoes great fluctuations. Some key state variables, such as product concentration and carbon source consumption, are very difficult to measure on-line, while these variables a...
详细信息
Cephalosporin C fed-batch cultivation undergoes great fluctuations. Some key state variables, such as product concentration and carbon source consumption, are very difficult to measure on-line, while these variables are essential to process monitoring and control.A neural network based software prediction of the key state variables for cephalosporin C fed-batch fermentation was investigated. A rolling learning-prediction procedure was used to deal with the time variant property of the process, and was also demonstrated to be beneficial to improving prediction *** successful prediction of the product formation enabled on-line evaluation of the economic performance of a charge and made optimal scheduling *** prediction approach was validated with the data of 49 industrial charges.
根据网格动态、异构的特点,提出了一种基于效益函数的网格资源调度算法,并根据时间、代价限制以及用户QOS(quality of service)建立效益函数,将传统静态的调度算法转变为面向用户的动态的调度算法,符合经济市场对于"买"、&qu...
详细信息
根据网格动态、异构的特点,提出了一种基于效益函数的网格资源调度算法,并根据时间、代价限制以及用户QOS(quality of service)建立效益函数,将传统静态的调度算法转变为面向用户的动态的调度算法,符合经济市场对于"买"、"卖"双方的要求。采用GridSim进行了模拟实验,并将该算法同Optimise-Cost和Optimise-Time算法进行了对比,结果表明该调度算法在任务的完成率、时间耗费及费用等方面具有一定的优越性。
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