Using neural networks for sustainable construction business development

The authors look at the application of neural networks to sustainable business development in construction industry. actual work self-learning with statistical data tables is studied. possibilities managing scheduling and material supply requirements from point view execution participation are shown. Appropriate indicators can be used subsequent numerical calculations. Tables above all allow for systematisation information. study large number by allows not only collective as a whole, i.e., totality objects phenomena - macro-units, but also subdivided collectives, separate parts whole micro units complex (united one attribute). Therefore, subject sentence-table may population (macro units), aggregate dissected (separate observation units) units. This quite understandable, because judgement refer object any stage this process, i.e. result dissection into units, combination latter small populations (complex generalization concept macro units.According results implementation automated control systems based on high purity quality design solutions processing production economic activity organisation achieved. Their efficiency calculated.