Abstract: Disclosed is a method for task planning of a space information network based on resource interchange. The method includes: initializing basic parameters of the space information network; dividing a planning horizon into K time slots of equal length, and constructing a resource time-varying graph for the space information network; sampling a feasible resource combination space of each task, and obtaining a candidate resource combination set comprised of the resource combinations with independence greater than or equal to a threshold n; calculating a conflict relation between resource combinations, and constructing a resource combination conflict graph; obtaining a maximum independent set of the resource combination conflict graph to obtain a global planning result; and searching a neighborhood of the global planning result, and completing a local adjustment of a task planning scheme through the resource interchange, to complete the task planning based on characteristics of the resource interchange.

Abstract: Disclosed is a method for task planning of a space information network based on resource interchange. The method includes: initializing basic parameters of the space information network; dividing a planning horizon into K time slots of equal length, and constructing a resource time-varying graph for the space information network; sampling a feasible resource combination space of each task, and obtaining a candidate resource combination set comprised of the resource combinations with independence greater than or equal to a threshold n; calculating a conflict relation between resource combinations, and constructing a resource combination conflict graph; obtaining a maximum independent set of the resource combination conflict graph to obtain a global planning result; and searching a neighborhood of the global planning result, and completing a local adjustment of a task planning scheme through the resource interchange, to complete the task planning based on characteristics of the resource interchange.

Abstract: A method for determining the probability that a biological molecule identification is incorrect for a chosen significance level is provided. The method includes comparing experimental mass data of an unknown biological molecule with theoretical mass data and calculating a score for each comparison; selecting at least two scores from the scores to form a primary data set; generating artificial data sets from the primary data set; calculating a sample mean for each artificial data set; estimating population mean and population standard deviation from the sample means wherein the population is based on the distribution underlying the primary dataset; computing a Z score from the population mean and population standard deviation for each score to standardize the scores; choosing a significance level; and comparing a test Z score to a Z score of the chosen significance level to determine the probability that the biological molecule identification is incorrect.

Abstract: A method for evaluating the performance of biopolymer identification algorithms, the method comprising a) generating noise and signal distributions, wherein the noise distribution comprises identification results obtained from the search of a database for arbitrarily generated sets of database mass data and wherein the signal distribution comprises identification results obtained from the search of a database for arbitrarily generated sets of database mass data which comprises mass data of a particular biopolymer of the database designated as a signal biopolymer; and b) calculating a performance index from the distributions which evaluates the performance of the algorithm.