Papers by Keyword: Early-Warning

Abstract: The fluctuation of pork price has been the center of attention among residents in both suburban and urban Beijing. This study is based upon building a monitoring and early-warning system of pork market in Beijing, and is conducted through the following three aspects: (1) Study of the risk factors of the price fluctuations in Beijing pork market. The study will determine what the “risk factors” for the fluctuations are, through looking into the price fluctuations pattern within the past twenty years in Beijing’s pork market, as well as the influential factors for the pattern in both short term and long term. (2) Gathering multi-source data of pork supply and demand, and study of the integration technology. By gathering monitored data through multi-source collecting market, production and quarantine, the study gathers and organizes the collected data, and integrates the data into a collective multi-source data. (3) Building an early-warning model in the pork market in Beijing and visualized research. By using the early-warning theory method, the study builds an indicator system consisting of leading indicator, concurrent indicator and lagging indicator, and thus builds an early-warning system, calculates early-warning index, compares early-warning lines, determining an early-warning alarm, and realizing visualization through B/S structure as well as embedded development. The study intends to achieve three innovative goals: Revealing the price fluctuations pattern of the pork market in Beijing, and the risk factors in the market; building a real-time information monitoring place, and thus achieving the integration of multi-source data of the pork markets; building an early-warning indication system of Beijing’s pork market, and achieving the simulation as well as displaying of the early-warning index. This study has important meanings on guiding the pork production and consumption in Beijing.

Abstract: Through the analysis and elaboration on the research status, system design and main structure of the domestic and foreign traceability system, given that we failed to retrieve the related research of broccoli safety production early-warning and quality traceability systems in domestic till now, we establish the broccoli safety production early warning, control as well as the quality traceability management systems on the basis of previous organic vegetables quality traceability system by using the barcode/QR code and computer component technology. It fully embodies the public security concept that the safe agricultural products are produced and unsafe products are detected. This system has good extensibility in many fields, a variety of security labels and so on

Abstract: The occurrence of agglomeration in gas-solid fluidized bed can have a very negative impact on the efficiency of reactor operation. In order to overcome the agglomeration problem, an Agglomeration Early-Warning System (AEWS) is proposed. AEWS is able to detect the event of such undesired behavior and make it possible to operate more efficiently. The sensitivity and selectivity of AEWS is illustrated with experimental results. In order to minimize the false alarm, both moving time window method and minimizing value method were analyzed. The experimental results have shown that agglomeration can be recognized 30-60min earlier with AEWS than that with conventional methods based on changes in pressure drop or temperature difference over the bed.

Abstract: Forest eco-security was the core of ecosystem security. In order to make early warning on the forest eco-security in Chang-Zhu-Tan region, according to the forest eco-security indexes and under the support of MATLAB, a prediction model was constructed to make predictions based on the GM (1, 1) model. The results showed that the forest eco-security comprehensive situation in the study area would be in Safer State from 2012 to 2014 and the situations of the pressure, the state and the response of the forest eco-security would be respectively in Safety State, Relatively Safety State and Alert State. The actual value for evaluating the forest eco-security state was reduced by 15.64% than the predicted value in 2008.

Abstract: To ensure 120 years design life of the large marine environmental engineering concrete structures in South China, and assess the status of the development of durability of concrete structure in real time w a research has been performed on embedded-non-destructive corrosion monitoring sensor systems, data acquisition and software integration, combined exposure test of concrete under environment in South China more than 30 years and laboratory test. It is a new type of technology for corrosion monitoring, assessment and early warning, which based on electrochemical principle, network transmission, expert software system, integrated the durability of the project full set of intelligent real-time monitoring and early warning expert systems.

Abstract: The purpose of this thesis is to solve the issue that the development of the work safety usually falls behind of the development of the production, which is driven by methodology that evaluating the effectiveness of the safety management by ranking the accidents.The research provided a production accident early warning index to reflect the real time safety status in order to prevent the accident at the source, to control the process and to measure the performance. A correlation analysis was then conducted parameters that meet the requirement of confidence intervals were given. A forecasting method using both quantitative and qualitative tools was proposed and the weights of each early warning index and the correlation between the indexes were determined. Finally, a mathematical model of production accident early warning was established to generate the production accident risk index which could represent the status of work safety and its future trends to forecast and prevent the severe accidents.

Abstract: With regard to goafs where spontaneous combustion of coal is very likely to occur, wireless monitoring and early warning techniques in temperature field of goaf are raised. Wireless monitoring and early warning system in temperature field of goaf based on wireless sensor network is researched and developed. Comprehensive detection, identification and early warning in temperature field of goaf are realized. Key parameters of node deployment of wireless temperature sensor in goaf are figured out and the layout schemes are optimized. According to monitored temperature information, severity of coal spontaneous combustion in goaf is figured out; therefore, early warning methods at the position of fire source are determined. Results of industrial tests on site show that monitoring data acquisition, communication are of good timeliness and reliability, operation of the entire system is stable and key functions and technical specifications can meet the need of early identification and warning of coal spontaneous combustion.

Abstract: To develop a lift early warning infrared device, as a part of land or boat (ship) early warning system, the system has the ability to target pre-discovery and instructions invasion. Methods: In support of distant air situation, alerts the enemy aircraft, missiles and other long-range goals, obtain the target type and preliminary judgment of grade, deliver the alarm information to the command system. The infrared alarm device detects the target's own infrared radiation passively, alarms the incoming targets at low altitude and low altitude remote, when radar and other equipment is out of work. Results: The accuracy of entire system reached 20" according the analysis. Conclusions: The device has a full range of complex background, with high sensitivity, high resolution, anti-jamming, fast response time and other characteristics

Abstract: Resource economy sustainable development degree of Yulin, Shaanxi Province during Year 2000-2014 was estimated and pre-warned by building BP neural network early-warning model and applying the written Matlab7.1 calculation program and AHP method. The early-warning results indicated that, economy sustainable development tendency of Yulin, Shaanxi during Year 2000-2014 is under huge warning, serious warning, medium warning and light warning these four states, respectively; early-warning model based on BP neural network has strong simulation ability, which is more appropriate for non-linear system early-warning research of solving resource economy sustainable development.

Abstract: The Life Cycle Asset Management (LCAM) was implemented by the development of smart grid promoted Grid Corporation to change the style of asset management. The external environment of LCAM is a development and changing system which had some characteristic with multi-agent, multi-level and multi-dimensional structure. Therefore, it is imperative requirement of implementing LCAM to .correctly understand and grasp the changing trends of external environment. The purpose of this paper is to propose an external environment early-warning model with LCAM to address the problem with how to grasp the change trends of external environment. This paper first calculated the weight of external environments by TOPSIS based transfer-entropy with survey data. And some significant external environment factors would be selected to be as the input vector of BP Neural Networks. Then the BP Neural Networks model was employed to early warning the situation of external environment. The results showed the superiority of the above two approaches in external environment early warning.