Introduction | Literature Search | Purpose and Objective | Expected Significance | Organization, Qualification and Staffing | Expected results | Scope of Activities | Technical Methodology | Foreign Collaborators

Project Title: Cognitive, Genetic and Neural Integrated Models for the Sustainable Development of the Regions

Research manager of the project: Oleg M. Namicheishvili, Professor, Dr. Sci. (Tech.)

Leading organization: Georgian Technical University          

What’s the problem?


Sustainable development and related issues has come to the political agenda since 1987 with the Brundtland Commision report (WCED - World Commission on Environment and Development, 1987). Different sustainability aims and targets are expressed in numerous international documents (Agenda 21 [1992], Johannesburg Implementation Plan [2002]) and regional as well as national sustainable development strategies (EU sustainable development strategy [2001, 2006], and other documents. Attention to sustainable and even development of the regions is given at all policy levels and is one of the main aims of sustainable development,  however, a national strategy for sustainable development does not exist in Georgia for the present.

Together with policy development, the need to assess the current situation and the achieved progress in sustainability has arisen. However, the development of Georgian regions has been evaluated only on descriptive separate indicators basis or rather short period of time. And very often only economic issues are stressed then comparing the regions, especially on the political level.

However, at present, there is no evidence that the problem of sustainable development explored enough. Their complexity and diversity at the regional and global levels require further study to develop economic and social mechanisms for optimal balancing economic, environmental and social components. The first thing to do in this respect science to create an effective instrumental and methodological apparatus of systems analysis and modeling of sustainable development and decision-making that will ensure in practice its real functioning. To achieve the desired environmental and economic balance, the public should actively carry out the regulation of production and the environment.

The main methods of this regulation are legal rules, economic mechanisms and technical or technological support. Relationship and interdependence these methods are obvious, but to achieve practical effect require them timely and optimal implementation. Theoretical foundations and algorithms for efficient interaction of nature with industrial and economic processes are a modern science and state-of-the-practice. In this structure the methodological and methodical approaches of the regulation includes global, regional and local levels.

At the global level, the main task is to develop a theoretical framework for environmental protection and the functioning of human society. Regional level provides adaptation tasks to specific regions and economies. At the local level the regulations are designed for macro and micro levels of activity.

Because a national strategy for sustainable development does not exist in Georgia, it is very important to know the factors that impede the stable political and economic  development of Georgia, notably: the ethnic-territorial conflicts on its territory, as well as their  possible roots, the poverty and related migration, the shadow economy and associated corruption, an incorrect  process of environmental planning at the national and regional level, as well as the other sectors related to environmental protection and the use of natural resources.The elimination of these factors is the prerequisite for the sustainable development of the country. Thus, the role of science in the resolution of problems of sustainable development is extremely high, but a special place among the scientific methodology here is cognitive, genetic and neural integrated models for the sustainable development of the Georgian regions and experimentation and modeling by the Networks of Artificial Neurons of various interactions.