Abstract: A particle analyzing apparatus outputs a measurement result with high reliability with respect to a measurement item. The particle analyzing apparatus includes a measuring part, a judgement processing part, and an output part. The measuring part includes a fluid part, a control part, a first measuring part, a second measuring part, a hystogram preparing part, and a scattergram preparing part. The fluid part sucks up a blood sample in a test tube by a pipette. The control part controls the fluid part, the first measuring part, and the second measuring part. Measurement data measured by the first measuring part and the second measuring part are sent to the judgement processing part, and after judgement is made in the judgement processing part, a measurement result is outputted by the output part. The first measuring part makes measurement on the basis of an impedance system, and the second measuring part makes measurement on the basis of a flow cytometory system.

Abstract: When a mixture of different kinds of particles, such as blood, is passed through a particle detector such as a flow cytometer to measure various characteristics of each particle and the measurements of two characteristics are plotted oh a two-dimensional rectangular co-ordinate, for example, the resultant dots tend to part into groups (clusters) corresponding to the kinds of the particles. This invention relates to a method and a device for presuming informations of the position of center of gravity, variances, number of dots and likes of each cluster by learning and, based upon these informations, presuming a specific cluster or category to which each measured particle should belong from the corresponding measurements of the particle, and it intends to execute such information processing by a fuzzy clustering technique using a neural network.