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Data clustering is an unsupervised data analysis and data mining technique, which offers refined and more abstract views to the inherent structure of a data set by partitioning it into a number of disjoint or overlapping (fuzzy) groups. Hundreds of clustering algorithms have been developed by researchers from a number of different scientific disciplines.(More)
Modern process and condition monitoring systems produce a huge amount of data which is hard to analyze manually. Previous analyzing techniques disregard time information and concentrate only for the indentification of normal and abnormal operational states. We present a new method for visualizing operational states and overall order of the transitions(More)
Fuel feeding and inhomogeneity of fuel typically cause process fluctuations in the circulating fluidized bed (CFB) process. If control systems fail to compensate for the fluctuations, the whole plant will suffer from fluctuations that are reinforced by the closed-loop controls. This phenomenon causes a reduction of efficiency and lifetime of process(More)
High gait-induced knee frontal plane moment is linked with the development of knee osteoarthritis. Gait patterns across the normal population exhibit large inter-individual variabilities especially at the knee sagittal plane moment profile during loading response and terminal stance phase. However, the effects of different gait patterns on this moment(More)
Experiences in the field of Monte Carlo methods indicate that the quality of a random number generator is exceedingly significant for obtaining good results. This result has not been demonstrated in the field of evolutionary optimization, and many practitioners of the field assume that the choice of the generator is superfluous and fail to document this(More)
The task of decision making can be divided into three steps (Simon 1976): (1) the identification and listing of all the alternatives; (2) the determination of all the consequences resulting from each of the alternatives; and (3) the comparison of the accuracy and efficiency of each of these sets of consequences. Simon (1965) refers to the first of these as(More)
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