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In this paper, the grey theory, three type of artificial neural network (back-propagation neural network, radial basis function neural network, and generalized regression neural network) and their combination were used to predict the pH values in the evaluation of water quality. Based on the measured data from the Xielugang in Jiaxin with the post-hoc analysis for the c and p values of the prediction, the results showed that the prediction by using the generalized regression neural network has the averaged relative error 0.61%, and c <0.65, p>0.7.

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We consider online scheduling with bi-criteria on parallel batch machines, where the batch capacity is unbounded. In this paper, online means that jobs’ arrival is over time. The objective is to minimize the maximum machine cost subject to the makespan being at its minimum. In unbounded parallel batch scheduling, a machine can process several jobs simultaneously as a batch. The processing time of a job and a batch is equal to 1. When job J j is processed on machine M i , it results cost c i j . We only consider two types of cost functions: c i j = a + c j and c i j = a · c j , where a is the fixed cost of machines and c j is the cost of job J j . The number of jobs is n and the number of machines is m. For this problem, we provide two online algorithms, which are showed to be the best possible with a competitive ratio of ( 1 + β m , ⌈ n m ⌉ ) , where β m is the positive root of the equation ( 1 + β m ) m + 1 = β m + 2 .