China-ASEAN and Guangxi Multiple-Regions Cooperative Low-Carbon Logistics Internet of Things Service System Hidden Markov Optimization Model
By analysis on the characteristic of low-carbon logistics, Internet of Things (IOT) Service System and economic zone, provides Multiple-Regions cooperative low-carbon logistics intelligent control optimization model. The low-carbon logistics IOT service system Hidden Markov optimization Model is in the IOT environment to use Hidden Markov Model algorithm to implement characteristic state transition monitoring on cross-region cooperative logistics process, based on network information aggregation, common distribution and cooperative control and other variations of IOT monitoring targets, determine prioritized state sequence by forward and backward algorithms as well as Viterbi algorithm, realize establishment of China-ASEAN and Guangxi Multiple-Regions cooperative low-carbon logistics optimization model and achieve intelligent control. Facts prove that on the premise of meeting IOT network variation state monitoring requirements, low-carbon logistics optimization model state selection identification rate could be improved.
KeywordsChina-ASEAN and Guangxi Multiple-Regions Internet of Things Low-carbon logistics HMM
Unable to display preview. Download preview PDF.
- 1.Ren, Q.-Q., Wu, Y.-F.: Low-carbon Logistics Measures in Low-carbon era. Logistics Engineering and Management (06), 21–23, 178 (2011)Google Scholar
- 5.Jian, X.: The Probability Calculation of Observation Sequence based on the Extended HMM. Computer Development & Applications (02), 7–8 (2011)Google Scholar