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...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 accuracy.The successful prediction of the product formation enabled on-line evaluation of the economic performance of a charge and made optimal scheduling possible.The prediction approach was validated with the data of 49 industrial charges.展开更多
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...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。展开更多
文摘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 accuracy.The successful prediction of the product formation enabled on-line evaluation of the economic performance of a charge and made optimal scheduling possible.The prediction approach was validated with the data of 49 industrial charges.
文摘根据网格动态、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。
