Xiaoyi Wang

Research on Water Bloom Prediction Based on Least Squares Support Vector Machine

An intelligent prediction model for water bloom of rivers and lakes based on least squares support vector machine (LSSVM) is proposed, in which main influence factor of outbreak of water bloom is analyzed by rough set theory first, and this model is compared with artificial neural network prediction model. The comparison result indicates: in the aspect of medium-term water bloom prediction in rivers and lakes, the accuracy of prediction with least squares support machine is higher than that of artificial neural network. Least squares support machine, which has long prediction period and high degree of prediction accuracy, needs a small amount of sample and can predict the medium-term change discipline of chlorophyll well. The results of simulation and application show that: LSSVM improves the algorithm of support vector machine (SVM)¿ it has long-term prediction period, strong generalization ability and high prediction accuracy; and this model provides an efficient new way for medium-term water bloom prediction.

Research on wastewater treatment system based on ADRC

Considering the characteristics of the time-delay, inertia and time-varying of DO control in the wastewater treatment, and on the basis of analyzing the defects on general PID control and Fuzzy Smith-PID control, one kind of ADRC controller is proposed in the wastewater treatment control system, Through the simulation experiment and comparing with general PID and Fuzzy Smith-PID control, the result shows that ADRC control strategy has lesser adjust-time and overshoot than other two control strategies. In addition, this control strategy not only can adapt the system change commendably under different working conditions, but also has good robustness and stability existing outside interference, and then provides an effective control way of solving the problem in the time-delay and inertia system.

Study on moving-objects detection technique in video surveillance system

A new method of moving-objects detection based on fusion of background subtraction and temporal differencing is proposed in this paper. The method constructs the adaptive background model by Gaussian model for each pixel in the image sequences, combined with temporal difference to update the background selectively, and simultaneous used background subtraction method extract movement areas from the background model. Then integration the two foreground regions segmented for object recognition, together with utilization of the median filter and mathematical morphology operation to eliminate noise and the small area of non-human movement parts. Finally obtain the complete reliable moving-objects. Experimental results show that the approach identifies targets accuracy, and can satisfy the needs of real-time in visual surveillance system.

A Control Method of Dissolved Oxygen in Sewage Treatment Based on Fuzzy-Smith

According to the characteristics of long time-delays, large inertia and time-variation in the dissolved oxygen control method of sewage treatment, one Fuzzy-Smith control model on dissolved oxygen control is presented in this paper. This model has the merits of a high robustness in fuzzy controller and a compensation for time delay in Smith predictor. After simulation experiment, the result is shown that this control model has both good robustness and stability when it matches the model or not, which is provided an effective approach to solve time-variation system of long time-delays and large inertia.

An AHP-fuzzy synthetic evaluation model based on evidence theory

Considering the indefinite and fuzzy characters existing in index weighs of complex system, a method confirming index weights based on evidence theory was put forward. On the basis of it, an efficiency evaluation model for complex system integrating Analytical Hierarchy Process (AHP) with fuzzy synthetic evaluation method has been set up, which can obtain more reasonable and objective evaluation result for complex system. Through analyzing an example of the system fighting efficiency for missile and gun integration weapon, the result shows the validity and feasibility of this method.

The lake water bloom intelligent prediction method and water quality remote monitoring system

According to the lagging state of water quality monitoring and problems of difficulty to predict water bloom, one water bloom prediction method based on grey-BP neural network is proposed and a system on water environmental remote monitoring and water bloom early warning based on GPRS wireless communication technology is built, which can obtain the automatic real-time monitoring information for the change of water quality and occurrence of water bloom, then provide a kind of efficient and practical system for water environment control.

Research on the online monitor of BOD based on process neural network

For the online monitor of BOD in sewage treatment process, a improved process neural network algorithm, included function momentum adjustment item and learning rate automatic adjustment, was introduced, which was used to establish the BOD soft sending model. The main controller about ATMEGA1280 singlechip was designed, the software was programmed by using the blocking software designing method and the integrated development environment of AVR Studio. The online monitor of BOD has many functions such as data acquisition, soft sensing computing, LCD display, data storing, printing, et al. The instrument is being applied on the industrial working field, and the result indicates the average relative forecasting error is less than 4.1%.

Application of gray correlation analysis in eutrophication evaluative of water bloom

The monitoring data for water quality of Beijing Beihai between May and October in 2007 have been analyzed with gray correlation. In order to overcome the defects of the traditional method, this way consider the interzone form of the water quality evaluation standard, use centralization dimensionless functions, and combine the integrated nutritional status index with const weight. The thread system can reflect multi factors and is easy to use. The results showed that the improved gray correlation analysis is an active tool in environmental assessment and administration.

Prediction technique for water-bloom in lakes based on elman network

The outbreak of water-bloom is the result of coactions of water bodys physical, chemical, biologic and other progresses. It is very difficult to establish uniform mathematical model to efficiently evaluate and predict the water-bloom because of the water bodys biodiversity and nonlinearity. Based on the foundation of research in the mechanism of water-bloom and the main component analysis in rivers and lakes, modeling method, fundamental theory, principle and technique established for water-bloom prewarning system which is based on artificial neural network is specially researched. Elman network has the characters of good dynamic characteristics, fast approaching speed, high degree of accuracy and so on. In this paper, combined with the basic features of outbreak of water-bloom, Elman network is studied from the angles of theory and experiment and a water-bloom prewarning system in short term based on Elman network is established. Considering the defect of classical BP algorithm, improved BP algorithm is used for the training and study of network. Example analysis shows that Elman network model established in this paper is reliable and practical. Moreover, water-bloom prewarning system in short term in long river water system is also established by MATLAB in this paper which proposes a new method for intelligent research in water-bloom prewarning.

Optimization of water quality monitoring section based on comprehensive hierarchical clustering

In order to optimize the section layout of water quality monitoring, this paper proposes a new method based on comprehensive hierarchical clustering (CHC). Firstly, the method calculated the affinity-disaffinity relationship among the monitoring variables through 5 distance algorithms. Afterwards, the data set could be clustered automatically through 4 connection algorithms. Then taking the correlation coefficient as evaluation criteria, optimal hierarchical clustering algorithm was selected. Finally, with the corresponding optimal clustering tree matrix, the monitoring sections can be set optimally. In addition, the paper used students t test to verify the result of optimization. The experimental results show that this method can reflect the water quality of whole area more efficiently, thus has good prospect.