Sizing of spheroidal and cylindrical particles in a binary mixture by measurement of scattered light intensity: application of neural networks

The problem on the retrieval of sizes of an individual optically soft particle taken from binary mixtures of either oblate and prolate spheroids or cylinders and oblate spheroids is considered. It is based on multiangle scattered light intensity data. The multilevel neural networks method with a linear activation function and the method of the discrimination functions are used. Neural networks to retrieve characteristics of cylinders, oblate and prolate spheroids are designed. The errors in retrieved particle characteristics are investigated for the radius of an equivolume sphere in the range of 0.3-1.5μm, shape parameter of spheroidal and cylindrical particles from -0.5 to 0.5 and 0 to 0.5, respectively.