Empirical studies have observed that the spectrum usage in practice follows regular patterns. Machine learning (ML)-based spectrum prediction techniques can thus be used jointly with cooperative sensing in cognitive radio networks (CRNs). In this paper, we propose a novel cluster-based sensing-after-prediction scheme and aim to reduce the total energy consumption of a CRN. An integer programming problem is formulated that minimizes the cluster size and optimizes the decision threshold, while guaranteeing the system accuracy requirement. To solve this challenging optimization problem, the relaxation technique is used which transforms the optimization problem into a tractable problem. The solution to the relaxed problem serves as a foundation for the solution to the original integer programming. Finally, a low-complexity search algorithm is proposed which achieves the global optimum, as it obtains the same performance with exhaustive search. Simulation results demonstrate that the total energy consumption of CRN is greatly reduced by applying our clustered sensing-after-prediction scheme.
Guoxia-silaotuo fault is a part of Longxian-Baoji fault zone. In previous studies, people only inferred the spatial distribution of the fault from the indirect evidences of geomorphology and geophysics. In this paper, through the detailed investigation of the fault, the outcrop of the fault plane is found; the trenching method is used to investigate the fault, and the activity scale of the fault is revealed. It is found that in the late Pleistocene, the activity intensity of the fault is relatively high.
This paper studied the regional seismic tectonic characteristics, regional seismic activity characteristics, the near-field seismic tectonic characteristics, near-field earthquake activity characteristics about the site of Seismic Microzonation in Shangluo City, seismic belts and potential seismic source zone were divided, calculating the seismic risk analysis of the bedrock of the site, surveying engineering geological conditions in the site, carrying out the seismic response analysis of the site, and zoning the ground motion parameters of the site. The above results provide a basis for the seismic fortification of the proposed general engineering in the site.
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