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The karst process acts as carbon sequestration for atmospheric CO2. The amount of karst carbon sequestration (KCS) depends on the discharge of karst catchment and inorganic carbon concentration of the water body. Based on the data from the monitoring station on Banzhai subterranean stream located in Maolan National Nature Reserve of Guizhou province, the process and influence factors of KCS have been analyzed. It shows that the amount of KCS is about 353 t C per year in the catchment of Banzhai subterranean stream, and there is good linear relationship between the strength of KCS and discharge of the stream at various time scales. Therefore, how to monitor the discharge accurately is the key to the estimation of KCS. And stations with real-time monitoring function are very important for KCS calculation because of strong seasonal variability of the karst water cycle. Citation He, S.-Y., Z.-Q. Kang, Q.-Y. Li, et al., 2012: The utilization of real-time high resolution monitoring techniques in karst carbon sequestration: A case study of the station in Banzhai subterranean stream catchment. Adv. Clim. Change Res., 3(1), doi: 10.3724/SP.J.1248.2012.00054.

In order to overcome the difficulty in real-time effectively acquiring the target parameters of differential game guidance in a complex underwater environment,the differential game guidance of underwater nonlinear tracking control based on continuous time generalised predictive correction is proposed.Since the target parameter and the detection precision are seriously affected by the acoustic homing device detection period,noise,and interference,it is easy to lose or misjudge the target signal.Hence a combination of the dynamic tracking game model for differential games and the acoustic homing detection method of underwater tracking is used for making the on-line prediction and compensation correction to the deviation tendency of target manoeuvres deviating from the self-guided sound zero axis.This is carried out by using a continuous time generalized predictive control algorithm,according to the discrepancy between the predicted advance> and the expected value.The manoeuvring target can then be located in the maximum capture probability sector of the tracker device in real time.In order to solve the estimation difficulty problem of the remaining time of the dynamic differential game antagonism,and improve the response speed and the control precision of the system,the zero-efficiency control parameter and the predictive control algorithm are introduced to optimize the differential game.In this way,the infinite time domain differential game can be transformed into a multiple-time domain differential game with feedback correction.Through the complementing advantages of dynamic programming and predictive optimization,the real-time compensation and correction to the interceptor differential game guidance is realised,and the disadvantages of the differential game in the process constraints and stochastic disturbance are overcome. In order to adjust the favourable advance> of the self-guided detection rapidly,the learning prediction function of rolling optimization feedback correction is adopted.The initial moment of the differential response is pushed forward along with the entire forecast period by rolling optimization.To verify the validity of the algorithm,this is applied to the underwater nonlinear tracking game,and the guidance performance is compared with the differential game guidance and the integrated control algorithm of differential game and discrete predictive control.The results show that this can achieve the optimum control of the high precision underwater manoeuvring target on-line tracking and prediction correction with the detection mode limited in uncertain disturbances,because this is flexible in the choosing of sampling time and does not need control weighting for non-minimum phase system.This can also solve the problem of the initial bias and random disturbance taking into account the control constraints and interference suppression performance,and can improve the robustness to environmental interference.

To quickly detect the defection of moving object, base on the experiments and analysis of the advantages and disadvantages of the classical operator, a new detection method of SUSAN Opertor and K-means clustering algorithm fusion is presented in this paper. This method integrates the advantages of the high precision of edge detection of the SUSAN Opertor and the accurate online detection of K-Means clustering, the surface defect of the moving target can be detected effectively and accurately.