Aging civil infrastructural facilities like long-span bridges, super-tall buildings, and large-scale space structures that form the life of a country's economy are facing a severe crisis in some countries. Long service lives, inadequate designs, and increasing extreme loads are responsible for the current state of affairs. Thus, knowledge about the in-service condition of the structures is one of the most essential parts required for the engineering community. This opens a wide field for structural health monitoring (SHM) systems which are set up to assure the safe operation of structures requiring linking sensors with computational tools able to interpret sensor data in terms of structural performance. Although intensive development continues on innovative sensor systems, there is still considerable uncertainty in deciding structural behavior since there are many factors in abundant measured data from the SHM system that may influence the health assessment of a structure. The most appropriate and efficient way to alleviate this multiple input problem is by the statistical and probabilistic approach including data normalization, feature extraction, statistical modeling, risk management, and so forth.

Therefore, in the light of the these considerations, we invite investigators to contribute original research papers as well as review papers for this special issue that aim at becoming an international forum for researchers and practitioners to summarize the most recent advances, progress, and ideas in the field of the statistical and probabilistic approach and its application in structure rating and risk assessment; more specifically, the focus will be on parametric tests, correlation analysis, regression analysis, cluster analysis, principal component analysis, factor analysis, correlation analysis, decision tree analysis, and Bayesian, rough set, and support vector machines, and so forth. Potential topics include, but are not limited to:

• Data compression and cleaning
• Data mining and fusing technology
• Pattern recognition and feature extraction
• Damage detection and condition assessment
• Performance prediction and risk management
• Other related issues

Before submission authors should carefully read over the journal’s Author Guidelines, which are located at http://www.hindawi.com/journals/mpe/guidelines/. Prospective authors should submit an electronic copy of their complete manuscript through the journal Manuscript Tracking System at http://mts.hindawi.com/submit/journals/mpe/spa/ according to the following timetable: