A novel hybrid-genetic-algorithm process applied in blood-glucose soft sensing

A novel hybrid-genetic-algorithm process in multi-objective parallel mode (NHMGA), operated for tracking a 2-period-BP model-mapping, supported by optimally equipped Grid-computing framework, is proposed. This NHMGA is specially designed for personal on-line and real-time bio-information modeling which is successfully applied in soft-sensing of blood-glucose. The related application example and its result analysis are described. Owing to the non-invasive soft-sensing based on the NHMGA which possesses the advantages, such as resource-sharing, high speed and accuracy of function approach, flexible real-time model-tracking, the number of blood-taking-times of every patient with serious diabetes can be reduced onto 30% of the original one per day, thus the on-line-diagnosis-medical-measurement based on the NHMGA is very strongly valued in Asia and Europe, and sequentially developed in the CAD-grid (CAD-G) 2# (¿China-Austria-Data-Grid¿-cooperation-project) which supports the NHMGA using a Grid-computing framework optimally equipped by workflow engine WEEP, and CEFSP 200805# (Chinese Education Foundation Science Project) which developed the NHMGA tool-software realized in a PC-embedded-FPGA-system (PEF) , thus, the NHMGA is facing a wide application future linked with the fields such as real-time tracking, analyzing, diagnosis and control of bio-information process, industrial automation process, natural synusiologic process.