{\rtf1\ansi\ansicpg1252\cocoartf1187\cocoasubrtf400 {\fonttbl\f0\fswiss\fcharset0 Helvetica;} {\colortbl;\red255\green255\blue255;} \paperw11900\paperh16840\margl1440\margr1440\vieww10800\viewh8400\viewkind0 \pard\tx566\tx1133\tx1700\tx2267\tx2834\tx3401\tx3968\tx4535\tx5102\tx5669\tx6236\tx6803\pardirnatural \f0\fs24 \cf0 1) What is self organisation? Properties? Name 2 Examples\ \ 2) \ a)Calculate 7 steps for 01011 with the rule that a cell survives if exactly 1 cell in the neighbourhood is alive..\ b)Gosper glider gun?\ c) 3 types of rules in CA\ \ 3)\ a) Name 3 genetic operators that are used in Genetic Algorithms\ b) Name 2 examples of problems that CA are often applied to.\ \ 4) Explain the reason for the following characteristics of the SOM training process, how they can be detected, how they can be used/interpreted during data analysis: \ a) magnification factors\ b)border effect\ \ 5) Explain the rationale for picking the size of the SOM and its impact on subsequent parameter setting (neighborhood rate, learning rate) How sensitive are these parameter settings, which aspects need to be considered, what is the impact of picking a wrong setting? \ \ }