Mixed Kernel Functions for Multivariate Statistical Monitoring of Nonlinear Processes

Machine learning techniques have now become pervasive in the field of process condition monitoring. In particular, kernel methods are those that use kernel functions to allow for the efficient nonlinear analysis of process data by projecting them onto high-dimensional spaces. A widely used kernel machine in multivariate process monitoring is kernel principal components analysis (KPCA). Many choices of kernel functions were used in previous KPCA studies. However, the use of single kernels alone was recently shown to give only limited expressive ability. In this work, we explored the impact of combining various kernel functions to the performance of KPCA for condition monitoring. Fault detection performance is defined by percent correct detection of faulty states and non-detection of normal states. Optimal kernel parameters were obtained using the genetic algorithm (GA). Visualizations of the boundary between normal and faulty states are provided for demonstration in a chemical process case study. This work can inform the development of mixed kernels for nonlinear process monitoring, not only in KPCA, but also in other kernel machines

Can triad forestry reconcile Europe’s biodiversity and forestry strategies? A critical evaluation of forest zoning

Balancing increasing demand for wood products while also maintaining forest biodiversity is a paramount challenge. Europe’s Biodiversity and Forest Strategies for 2030 attempt to address this challenge. Together, they call for strict protection of 10% of land area, including all primary and old growth forests, increasing use of ecological forestry, and less reliance on monocultural plantations. Using data on country wide silvicultural practices and a new database on strict forest reserves across Europe, we assess how triad forest zoning could help meet these goals. Our analysis reveals that zoning in Europe is overwhelmingly focused on wood production, while there has been little concomitant protection of forests in strict reserves. Moreover, most strict forest reserves are < 50 ha in size, likely too small to capture the minimum dynamic area necessary to sustain many taxa. We outline research priorities to meet future demands for timber while minimizing the impact on native biodiversity. © The Author(s) 2024