Operational Evaluation of the Quantitative Precipitation Estimation by a CINRAD-SA Dual Polarization Radar System

In this paper,a quantitative precipitation estimation based on the hydrometeor classification(HCA-QPE)algorithm was proposed for the first operational S band dual-polarization radar upgraded from the CINRAD/SA radar of China.The HCA-QPE algorithm,localized Colorado State University-Hydrometeor Identification of Rainfall(CSUHIDRO)algorithm,the Joint Polarization Experiment(JPOLE)algorithm,and the dynamic Z-R relationships based on variational correction QPE(DRVC-QPE)algorithm were evaluated with the rainfall events from March 1 to October 30,2017 in Guangdong Province.The results indicated that even though the HCA-QPE algorithm did not use the observed rainfall data for correction,its estimation accuracy was better than that of the DRVC-QPE algorithm when the rainfall rate was greater than 5 mm h-1;and the stronger the rainfall intensity,the greater the QPE improvement.Besides,the HCA-QPE algorithm worked better than the localized CSU-HIDRO and JPOLE algorithms.This study preliminarily evaluated the improved accuracy of QPE by a dual-polarization radar system modified from CINRAD-SA radar.

Comprehensive Evaluation Model of Reservoir Operation Based on Improved Set Pair Analysis

A comprehensive evaluation model based on improved set pair analysis is established. Considering the complexity in decision-making process, the model combines the certainties and uncertainties in the schemes, i.e., identical degree, different degree and opposite degree. The relations among different schemes are studied, and the traditional way of solving uncertainty problem is improved. By using the gray correlation to determine the difference degree, the problem of less evaluation indexes and inapparent linear relationship is solved. The difference between the evaluation parameters is smaller in both the fuzzy comprehensive evaluation model and fuzzy matter-element method, and the dipartite degree of the evaluation result is unobvious. However, the difference between each integrated connection degree is distinct in the improved set pair analysis. Results show that the proposed method is feasible and it obtains better effects than the fuzzy comprehensive evaluation method and fuzzy matter-element method.

Tide forecasting method based on dynamic weight distribution for operational evaluation

Through analysis of operational evaluation factors for tide forecasting, the relationship between the evaluation factors and the weights of forecasters was examined. A tide forecasting method based on dynamic weight distribution for operational evaluation was developed, and multiple-forecaster synchronous forecasting was realized while avoiding the instability cased by only one forecaster. Weights were distributed to the forecasters according to each one＇s forecast precision. An evaluation criterion for the professional level of the forecasters was also built. The eligibility rates of forecast results demonstrate the skill of the forecasters and the stability of their forecasts. With the developed tide forecasting method, the precision and reasonableness of tide forecasting are improved. The application of the present method to tide forecasting at the Huangpu Park tidal station demonstrates the validity of the method.

Operational effectiveness evaluation based on the reduced conjunctive belief rule base

To address the issue of rule premise combination explosion in the construction of the traditional complete conjunctive belief rule base(BRB),this paper introduces an orthogonal design method to reduce the conjunctive BRB.The reasoning method based on reduced conjunctive BRB is designed with the help of the conversion technology from conjunctive BRB to disjunctive BRB.Finally,the operational mission effectiveness evaluation is taken as an example to verify the proposed method.The results show that the method proposed in this paper is feasible and effective.

Validation of the Chinese system for cardiac operative risk evaluation (SinoSCORE):the experience from Guangdong Cardiovascular Institute

Objective To validate of the Chinese system for cardiac operative risk evaluation (SinoSCORE) in Cantonese surgery patients. Methods Data from Guangdong Cardiovascular Institute in the period January 2004 through December 2008 were analyzed on 2462 Cantonese heart surgery patients. First,compared risk factors of this series and database of SinoSCORE,and then calculated

Evaluation of rope shovel operators in surface coal mining using a Multi-Attribute Decision-Making model

Rope shovels are used to dig and load materials in surface mines. One of the main factors that influence the production rate and energy consumption of rope shovels is the performance of the operator. This paper presents a method for evaluating rope shovel operators using the Multi-Attribute Decision-Making （MADM） model. Data used in this research were collected from an operating surface coal mine in the southern United States. The MADM model consists of attributes, their weights of importance, and alter- natives. Shovel operators are considered the alternatives, The energy consumption model was developed with multiple regression analysis, and its variables were included in the MADM model as attributes. Preferences with respect to min/max of the defined attributes were obtained with multi-objective opti- mization. Multi-objective optimization was conducted with the overall goal of minimizing energy con- sumption and maximizing production rate. Weights of importance of the attributes were determined by the Analytical Hierarchy Process （AHP）, The overall evaluation of operators was performed by one of the MADM models, i.e., PROMETHEE If. The research results presented here may be used by mining professionals to held evaluate the performance of rode shovel operators in surface mining.

A systematic approach for estimating water losses in irrigation canals

In order to determine water losses in irrigation canals,a systematic approach was developed,consisting of two main components:a seepage simulation model and a hydraulic simulation model.The SEEP/W module of the Geo-Studio software was used to simulate the seepage rate,and the Hydrologic Engineering Center-River Analysis System(HEC-RAS)hydrodynamic model was used for hydraulic simulation.Different operation scenarios were designed to investigate all possible situations in daily operation of water distribution and delivery systems.The seepage simulation results show that the seepage losses were higher at the bottom and corners of the canal,because the hydraulic gradient was affected by the hydraulic load.The hydraulic simulation results show that due to physical and management infrastructure(using non-automated and operator-based regulation structures),operational losses accounted for a significant volume of losses compared to seepage losses.In most operation scenarios,the maximum seepage loss was 10%,and the remaining 90%was related to operational losses.It is concluded that any factor(decrease or increase of inflow to the canal)that causes an increase or decrease of operational losses is ultimately a determining factor in reducing or increasing total losses.Therefore,management approaches should be adopted to improve performance of the system and reduce losses,especially operational losses,by improving the operation methods of water level regulation and off-take structures.

Study on the Evaluation of the New Line of Urban Rail Transit Based on Analytic Hierarchy Process

The basic conditions of Urban rail transit line test operation are mainly based on Basic condition for trial operation of urban rail transit （GB/T30013-2013） the basic conditions of the relevant provisions, but the status and standard of trial operation of the basic conditions for assessment of the operating departments are still inadequate, during the three mouth of trial running operations, the specific work of trial operation and exercise are not clear about what this study focuses. This study emphasizes on the methods of operation assessment, through the Analysis Hierarchy Process （AHP） to make the commissioning work carry out smoothly and effectively, making the running exercise Rally, and the emergency and safety follow-up operation process can be quickly handled properly, and it is also helpful to the sustainable development of urban raft transit.

Impact of Down Spinning Reserve on Operation Reliability of Power Systems

The development of renewable energy and the increasing peak-valley difference of load demand lead to an increasing requirement of spinning reserve(SR).However,the traditional operation reliability analysis of power system mainly focuses on the up SR and neglects the down SR.Therefore,the operation reliability of power system considering the impacts of down SR is investigated in this paper.Firstly,the constraints of down SR are incorporated into the day-ahead unit commitment(UC)model to obtain the generation scheduling and reserve allocation of power systems.Based on the dispatch results of UC model,the re-dispatched energy and load interruption can be determined using optimal power flow(OPF)model in the realtime operation in various contingency states.Operation reliability indices are calculated based on the load curtailment to represent the reliability performances of power systems.The proposed approaches are validated using the modified IEEE reliability test system.Case studies demonstrate that down SR can improve the operation reliability of power systems.

Is the European System for Cardiac Operative Risk Evaluation useful in Chinese patients undergoing heart valve surgery？

Background The European System for Cardiac Operative Risk Evaluation （EuroSCORE） is one of the most widely used risk models for the predicting mortality after cardiac surgery. The aim of this study was to validate the EuroSCORE model for predicting operative mortality in heart valve surgery on a Chinese multicenter database and comparing the performance of EuroSCORE with our new risk stratification system, the Sino System for Coronary Operative Risk Evaluation （SinoSCORE）. Methods Data from patients undergoing heart valve surgery between January 2007 and December 2008 were retrospectively collected, from 43 hospitals in China. The EuroSCORE and the SinoSCORE were calculated for each patient. Mortality was defined as any in-hospital death. Area under the receiver operating characteristics curve （AUC） was used to study the discriminatory abilities of the models. The Hosmer-Lemeshow （H-L） goodness-of-fit test was used to study the calibration of the predictive models. Results A total of 15 367 patients were analyzed. For the entire cohort, the observed mortality was 2.34%, the predicted mortality was 3.71% （additive）, 3.19% （logistic） and 3.66% （SinoSCORE）. AUC was 0.747 for SinoSCORE, 0.699 additive and 0.696 for logistic EuroSCORE. Calibration of SinoSCORE and additive EuroSCORE was good （H-L： P=-0.250 and P=0.051, respectively）, but the logistic EuroSCORE model had a poor calibration （H-L： P〈0.05）. The discriminatory ability and calibration of the SinoSCORE were good in low- and high-risk patients, However, the discriminatory ability of the EuroSCORE model was poor in all risk deciles. Conclusions The EuroSCORE does not accurately predict mortality in Chinese patients with heart valve surgery, and the SinoSCORE is superior to the EuroSCORE at predicting in-hospital mortality in Chinese heart valve surgery patients.

Application research of multivariate linkage fluctuation analysis on condition evaluation in process industry

Abnormal conditions are hazardous in complex process systems, and the aim of condition recognition is to detect abnormal conditions and thus avoid severe accidents. The relationship of linkage fluctuation between monitoring variables can characterize the operation state of the system. In this study,we present a straightforward and fast computational method, the multivariable linkage coarse graining(MLCG) algorithm, which converts the linkage fluctuation relationship of multivariate time series into a directed and weighted complex network. The directed and weighted complex network thus constructed inherits several properties of the series in its structure. Thereby, periodic series convert into regular networks, and random series convert into random networks. Moreover, chaotic time series convert into scale-free networks. It demonstrates that the MLCG algorithm permits us to distinguish, identify, and describe in detail various time series. Finally, we apply the MLCG algorithm to practical observations series, the monitoring time series from a compressor unit, and identify its dynamic characteristics. Empirical results demonstrate that the MLCG algorithm is suitable for analyzing the multivariable linkage fluctuation relationship in complex electromechanical system. This method can be used to detect specific or abnormal operation condition, which is relevant to condition identification and information quality control of complex electromechanical system in the process industry.