Design of adaptive, multidimensional information and control systems

数据收集（遥感、传感器网络等）的急剧增加，当今计算系统的处理和联网能力意味着现在可以访问大量数据，并在设计和控制多样化的、通常是复杂的系统时有效地使用它们。这些发展对智能信息和控制系统领域的发展产生了深远的影响。在拟议的研究计划中，主要目标是开发一种综合方法，解决自适应，自组织系统的设计和控制中的问题，这些问题在动态，不确定的环境中分布式处理大量数据的背景下至关重要。- 为设计系统奠定理论和方法基础，使系统能够根据功能和性能要求结合不同类型的信息处理技术，调整其结构。- 满足处理大量多维信息（降维、性能标准等）的要求。 - 开发主要结合神经网络、模糊逻辑、选定统计技术和自适应索引的混合技术，并将其应用于最需要适应性和学习能力的非线性、时变、不确定系统。该研究计划的结果，同时有助于控制系统和模式识别领域的理论发展，同时将适用于几个不同的领域，如遥感，地理信息学，智能制造系统，分布式测量和控制系统，决策支持系统。

The sharp increase in data gathering (remote sensing, sensor networks, etc.), processing and networking capabilities of today's computing systems means that it is now possible to access vast amounts of data and to efficiently use them in the design and control of diversified, often complex systems. These developments have had a profound impact on the evolution of the area of intelligent information and control systems. In the proposed research program, the main objective is the development of an integrated methodology that addresses those issues in the design and control of adaptive, self-organizing systems that are critical in the context of distributed processing of large quantities of data in dynamic, uncertain environments. Specific long-term objectives include: - Development of theoretical and methodological foundations for the design of systems that adapt their structure by combining different types of information processing technique according to functional and performance requirements. - Addressing the requirements imposed by the fact of dealing with large amounts of multi-dimensional information (dimensionality reduction, performance criteria, etc.).   - Development of hybrid technologies integrating mainly neural networks, fuzzy logic, selected statistical techniques and adaptive indexing, and their application in non-linear, time-variable, uncertain systems, where the need for adaptability and learning capabilities is most pronounced. The results of this research program, while contributing to theoretical developments in the areas of control systems and pattern recognition, will at the same time be applicable in several diversified domains, such as remote sensing, geomatics, Intelligent Manufacturing Systems, distributed measurement and control systems, and decision support systems.