The Algorithm of Area Optimization by Layers and Binary Classification with use of Three State 2D Cellular Automata

In this paper is proposed a new method of optimization in the sense of the area. The proposed algorithm reduces the area to the optimal size. The proposed algorithm can also be used as an optimization tool, which indicates the area including the optimum. Proposed method joins a few issues. First one is utilizing data from the set of sensors monitoring the area put into optimization. The second one is using the classification method based on two-dimensional three-state cellular automata, working on the data reported by the sensors. This method classifies all points of the area based on the data received from the sensors and designates optimal subarea. The third issue is applying the categorization layers to the data received from sensors. Such, approach gives a possibility to specify the areas in the different levels and, in consequence, after analysis, optimal subarea or subarea including the optimal point can be designated. This method can be used in different optimization tasks, starting from simple one as optimization of n-dimensional function, through specifying the contaminated area utilizing data from mobile sensors and finally estimating the contamination source-term.