Comprehensive security risk factor identification for small reservoirs with heterogeneous data based on grey relational analysis model

Identification of security risk factors for small reservoirs is the basis for implementation of early warning systems.The manner of identification of the factors for small reservoirs is of practical significance when data are incomplete.The existing grey relational models have some disadvantages in measuring the correlation between categorical data sequences.To this end,this paper introduces a new grey relational model to analyze heterogeneous data.In this study,a set of security risk factors for small reservoirs was first constructed based on theoretical analysis,and heterogeneous data of these factors were recorded as sequences.The sequences were regarded as random variables,and the information entropy and conditional entropy between sequences were measured to analyze the relational degree between risk factors.Then,a new grey relational analysis model for heterogeneous data was constructed,and a comprehensive security risk factor identification method was developed.A case study of small reservoirs in Guangxi Zhuang Autonomous Region in China shows that the model constructed in this study is applicable to security risk factor identification for small reservoirs with heterogeneous and sparse data.

Fisher discriminant analysis model and its application for prediction of classification of rockburst in deep-buried long tunnel

A Fisher discriminant analysis （FDA） model for the prediction of classification of rockburst in deep-buried long tunnel was established based on the Fisher discriminant theory and the actual characteristics of the project. First, the major factors of rockburst, such as the maximum tangential stress of the cavern wall σθ, uniaxial compressive strength σc, uniaxial tensile strength or, and the elastic energy index of rock Wet, were taken into account in the analysis. Three factors, Stress coefficient σθ/σc, rock brittleness coefficient σc/σt, and elastic energy index Wet, were defined as the criterion indices for rockburst prediction in the proposed model. After training and testing of 12 sets of measured data, the discriminant functions of FDA were solved, and the ratio of misdiscrimina- tion is zero. Moreover, the proposed model was used to predict rockbursts of Qinling tunnel along Xi＇an-Ankang railway. The results show that three forecast results are identical with the actual situation. Therefore, the prediction accuracy of the FDA model is acceptable.

Research on spatial calculating analysis model of landuse change

The spatial calculating analysis model is based on GIS overlay. It will compartmentalize the land in research district into three spatial types: unchanged parts, converted parts and increased parts. By this method we can evaluate the numerical model and dynamic degree model for calculating land-use change rates. Furthermore, the paper raises the possibility of revising the calculating analysis model of spatial information in order to predicate more precisely the dynamic changing level of all types of land uses. In the most concrete terms, the model is used mainly to understand changed area and changed rates (increasing or decreasing) of different land types from microcosmic angle and establish spatial distribution and spatio-temporal principles of the changing urban lands. And we will try to find out why the situation can take place by combining social and economic situations. The result indicates the calculating analysis model of spatial information can derive more accurate procedure of spatial transference and increase of all kinds of land from microcosmic angle. By this model and technology we can conduct the research of land-use spatio-temporal structure evolution more systematically and more deeply, and can obtain a satisfactory result. The result will benefit the rational planning and management of urban land use of developed coastal areas in China in the future.

Performance analysis model for real-time Ethernet-based computer numerical control system

In order to optimize the embedded system implementation for Ethernet-based computer numerical control （CNC） system, it is very necessary to establish the performance analysis model and further adopt the codesign method from the control, communication and computing perspectives. On the basis of analyzing real-time Ethemet, system architecture, time characteristic parameters of control-loop ere, a performance analysis model for real-time Ethemet-based CNC system was proposed, which is able to include the timing effects caused by the implementation platform in the simulation. The key for establishing the model is accomplished by designing the error analysis module and the controller nodes. Under the restraint of CPU resource and communication bandwidth, the experiment with a case study was conducted, and the results show that if the deadline miss ratio of data packets is 0.2%, then the percentage error is 1.105%. The proposed model can be used at several stages of CNC system development.

An Analysis Model of Sports Human Body Based on Computer Vision Tracking Technology

This paper proposes the analysis model of sports human body based on computer vision tracking technology. Visual target tracking is an important research field of the computer vision, motion trajectory and it can provide not only the goal, to provide the initial data movement analysis, scene understanding, behavior or the event detection in intelligent surveillance, human-computer interaction, robot visual navigation and motion recognition based on field has a broad application prospect. For this reason, it is possible to consider the use of a large number of unlabeled samples to assist the training classifier to improve its performance. This type of machine learning method using both labeled and that unlabeled samples is called the semi-supervised learning. This paper proposes the novel idea of the related research topics to propose the new perspective of the model that will be later give us the novel idea of making it efficient for further development of sport science.

Application of synthetic principal component analysis model to mine area farmland heavy metal pollution assessment

Referring to GB5618-1995 about heavy metal pollution,and using statistical analysis SPSS,the major pollutants of mine area farmland heavy metal pollution were identified by variable clustering analysis.Assessment and classification were done to the mine area farmland heavy metal pollution situation by synthetic principal components analysis (PCA).The results show that variable clustering analysis is efficient to identify the principal components of mine area farmland heavy metal pollution.Sort and clustering were done to the synthetic principal components scores of soil sample,which is given by synthetic principal components analysis.Data structure of soil heavy metal contaminations relationships and pollution level of different soil samples are discovered.The results of mine area farmland heavy metal pollution quality assessed and classified with synthetic component scores reflect the influence of both the major and compound heavy metal pol- lutants.Identification and assessment results of mine area farmland heavy metal pollution can provide reference and guide to propose control measures of mine area farmland heavy metal pollution and focus on the key treatment region.

Study on Analysis Model of Millet Yield Loss Caused by Weeds in Summer Season Millet Field

Weed management in summer season foxtall millet field was studied by evaluating weed damage and exploring competition between weeds and foxtail millet, and a few fitting models were simulated and compared by employing field plot experiment and nonlinear regression analysis. The results showed that the millet yield losses and weed density were extremely significantly correlated. Among the tested models, the determination coefficient （ R2 ） of hyperbolic model was 0.997 12, and minimum residual sum of squares was 16.174, which was considered the optimal model to simulate the competition relation between weeds and millet. The predicted equation was Y = d/（ 1. 733 ＋ 0. 018d） ; the interspecific competitiveness of weeds was 0. 577 0 and the intraspecific competitiveness was 0.010 3 ; the maximum loss rate of millet yield was 55.56%. This study had established an analysis model with high gcodness-of-fit and practical prediction which could help weed management in summer season millet field.

Research on the Land Consolidation Strategy of Dalian City Based on PESTEL Analysis Model

Standing at the starting point of the"13 th Five-Year Plan",the general situation of Dalian City,the current status and characteristics of land use,and the strategy of land consolidation planning during the"12 th Five-Year Plan"period are analyzed,and then the political,economic,social,technological,environmental and legal factors that influence the land consolidation of Dalian City are analyzed based on the PESTEL model.Afterwards,measures of land consolidation in Dalian City during the"13 th Five-Year Plan"period are proposed,such as transforming the concept of land consolidation,coordinating opinions of agricultural departments and making scientific decisions,reasonably arranging agricultural space,optimizing the layout of rural residential areas and encouraging moderate scale management of land,broadening the content of land consolidation,and implementing soil testing fertilization.

Security Risk Analysis Model for Identification and Resolution System of Industrial Internet

Identification and resolution system of the industrial Internet is the“neural hub”of the industrial Internet for coordination.Catastrophic damage to the whole industrial Internet industry ecology may be caused if the identification and resolution system is attacked.Moreover,it may become a threat to national security.Therefore,security plays an important role in identification and resolution system of the industrial Internet.In this paper,an innovative security risk analysis model is proposed for the first time,which can help control risks from the root at the initial stage of industrial Internet construction,provide guidance for related enterprises in the early design stage of identification and resolution system of the industrial Internet,and promote the healthy and sustainable development of the industrial identification and resolution system.

A Requirements Analysis Model Based on QFD

The enterprise resource planning (ERP) system has emerged to offer an integrated IT solution and more and more enterprises are increasing by adopting this system and regarding it as an important innovation. However, there is already evidence of high failure risks in ERP project implementation, one major reason is poor analysis of the requirements for system implementation. In this paper, the importance of requirements analysis for ERP project implementation is highlighted, and a requirements analysis model by applying quality function deployment (QFD) is presented, which will support to conduct requirements analysis for ERP project.

Modeling Analysis of Factors Influencing Wind-Borne Seed Dispersal: A Case Study on Dandelion

A weed is a plant that thrives in areas of human disturbance, such as gardens, fields, pastures, waysides, and waste places where it is not intentionally cultivated. Dispersal affects community dynamics and vegetation response to global change. The process of seed disposal is influenced by wind, which plays a crucial role in determining the distance and probability of seed dispersal. Existing models of seed dispersal consider wind direction but fail to incorporate wind intensity. In this paper, a novel seed disposal model was proposed in this paper, incorporating wind intensity based on relevant references. According to various climatic conditions, including temperate, arid, and tropical regions, three specific regions were selected to establish a wind dispersal model that accurately reflects the density function distribution of dispersal distance. Additionally, dandelions growth is influenced by a multitude of factors, encompassing temperature, humidity, climate, and various environmental variables that necessitate meticulous consideration. Based on Factor Analysis model, which completely considers temperature, precipitation, solar radiation, wind, and land carrying capacity, a conclusion is presented, indicating that the growth of seeds is primarily influenced by plant attributes and climate conditions, with the former exerting a relatively stronger impact. Subsequently, the remaining two plants were chosen based on seed weight, yielding consistent conclusion.

Effects of Initial and Boundary Conditions on Heavy Rainfall Simulation over the Yellow Sea and the Korean Peninsula:Comparison of ECMWF and NCEP Analysis Data Effects and Verification with Dropsonde Observation

This study evaluated the simulation performance of mesoscale convective system(MCS)-induced precipitation,focusing on three selected cases that originated from the Yellow Sea and propagated toward the Korean Peninsula.The evaluation was conducted for the European Centre for Medium-Range Weather Forecasts(ECMWF)and National Centers for Environmental Prediction(NCEP)analysis data,as well as the simulation result using them as initial and lateral boundary conditions for the Weather Research and Forecasting model.Particularly,temperature and humidity profiles from 3D dropsonde observations from the National Center for Meteorological Science of the Korea Meteorological Administration served as validation data.Results showed that the ECMWF analysis consistently had smaller errors compared to the NCEP analysis,which exhibited a cold and dry bias in the lower levels below 850 hPa.The model,in terms of the precipitation simulations,particularly for high-intensity precipitation over the Yellow Sea,demonstrated higher accuracy when applying ECMWF analysis data as the initial condition.This advantage also positively influenced the simulation of rainfall events on the Korean Peninsula by reasonably inducing convective-favorable thermodynamic features(i.e.,warm and humid lower-level atmosphere)over the Yellow Sea.In conclusion,this study provides specific information about two global analysis datasets and their impacts on MCS-induced heavy rainfall simulation by employing dropsonde observation data.Furthermore,it suggests the need to enhance the initial field for MCS-induced heavy rainfall simulation and the applicability of assimilating dropsonde data for this purpose in the future.

Analysis and Modeling of the Central Air-Conditioning System in Intelligent Buildings

The central air conditioning system in an intelligent building (IB) was analyzed and modeled in order to perform the optimization scheduling strategy of the central air conditioning system. A set of models proposed and a type of periodically autoregressive model (PAR) based on the improved genetic algorithms (IGA) were used to perform the optimum energy saving scheduling. The example of the Liangmahe Plaza was taken to show the effectiveness of the methods.

Prototyping an open environment for sharing geographical analysis models on cloud computing platform

The sharing of geographical analysis models is of crucial importance for simulating geographic processes and phenomena in the current geographical information systems(e.g.Digital Earth),but there remain some issues that have not been completely resolved.The challenges include,eliminating model heterogeneity and searching for suitable infrastructures to support the open sharing and effective execution of models.Taking advantage of cloud computing,this article aims to address the above issues and develop an open environment for geographical analysis model sharing.On the basis of the analysis of the applicability of cloud computing,the architecture of the open environment is proposed.More importantly,key strategies designed for heterogeneous model description,model encapsulating as well as model deploying and transparent accessing in the cloud are discussed in detail to establish such an environment.Finally,the prototype environment is implemented,and experiments were conducted to verify the environment’s feasibility to support the sharing of geographical analysis models.

Operating mechanism and set pair analysis model of a sustainable water resources system

There is no altemative to the world＇s water resources, and their increasing scarcity is making it difficult to meet the world population＇s water needs. This paper presents a sustainable water resources system （SWRS） and analyzes the operating mechanism that makes it possible to evaluate the status of such a system. A SWRS can be described as a complex coupling system that integrates water resources, social, economic and ecological systems into a whole. The SWRS＇s operating mechanism is composed of dynamic, resistance and coordination components, and it interacts with and controls the system＇s evolution process. The study introduces a new approach, set pair analysis theory, to measure the state of a SWRS, and an evaluation index system is established using the subsystems and operating mechanism of a SWRS. The evaluation index system is separated into three levels （goal level, criteria level and index level） and divides the index standard into five grades. An evaluation model of the SWRS based on set pair analysis theory is constructed, and an example of SWRS evaluation in Shanghai is presented. The connection degrees of the index in the three levels are calculated, and the connection degree of the goal index is calculated to be 0.342, which classifies the city＇s SWRS condition as grade 2. The sustainable use of water resources in the region is determined to be at a relatively adequate level that meets the requirements of sustainable development.

Cost analysis model for catalytic conversion of syngas in to light hydrocarbon gases

Bio-gasification is a new technology and considered as a more efficient way to utilize bioenergy.The economic feasibility becomes one of the greatest issues when we apply this new technology.Evaluation of economic feasibility of a bio-gasification facility needs better understanding of its production unit cost under different capacities and different working shift modes.The objective of this study was to evaluate the unit cost of biofuel products(Liquid HCs,Light HCs and Oxygenates CxHyOz)under different capacities using a modeling method.The cost analysis model was developed using Visual Basic Microsoft 2008,computer programming language and mathematical equations.The modeling results showed that the unit costs of biofuel product from bio-gasification facility were significantly affected by production capacities of facilities.As the facility capacity increased from 65 to 10,000 N m^3 h^-1,the biofuel production unit cost of gas(Light HCs),oil(Liquid HCs),and aqueous(Oxygenates CxHyOz)decreased from$38.92 per MMBTU,$30.89 per gallon and$25.74 per gallon to$2.01 per MMBTU,$1.59 per gallon,and$1.33 per gallon,respectively.The results of the sensitivity analysis showed that feedstock cost was the most sensitive cost factor on unit costs for all biofuel products at high capacity.The cost analysis model developed in this study could be used to optimize production unit costs of bio-fuel products from bio-gasification facility.

Transient pressure analysis of polymer flooding fractured wells with oil-water two-phase flow

The oil-water two-phase flow pressure-transient analysis model for polymer flooding fractured well is established by considering the comprehensive effects of polymer shear thinning,shear thickening,convection,diffusion,adsorption retention,inaccessible pore volume and effective permeability reduction.The finite volume difference and Newton iteration methods are applied to solve the model,and the effects of fracture conductivity coefficient,injected polymer mass concentration,initial polymer mass concentration and water saturation on the well-test type curves of polymer flooding fractured wells are discussed.The results show that with the increase of fracture conductivity coefficient,the pressure conduction becomes faster and the pressure drop becomes smaller,so the pressure curve of transitional flow goes downward,the duration of bilinear flow becomes shorter,and the linear flow appears earlier and lasts longer.As the injected polymer mass concentration increases,the effective water phase viscosity increases,and the pressure loss increases,so the pressure and pressure derivative curves go upward,and the bilinear flow segment becomes shorter.As the initial polymer mass concentration increases,the effective water phase viscosity increases,so the pressure curve after the wellbore storage segment moves upward as a whole.As the water saturation increases,the relative permeability of water increases,the relative permeability of oil decreases,the total oil-water two-phase mobility becomes larger,and the pressure loss is reduced,so the pressure curve after the wellbore storage segment moves downward as a whole.The reliability and practicability of this new model are verified by the comparison of the results from simplified model and commercial well test software,and the actual well test data.

Experimental Study and Model Analysis of the Performance of IPMC Membranes with Various Thickness

Ionic Polymer-Metal Composite （IPMC） is a new electro-active polymer, which has the advantages of light weight, flexibility, and large stroke with low driving voltage. Because of these features, IPMC can be applied to bionic robotic actuators, artificial muscles, as well as dynamic sensors. However, IPMC has the major drawback of low generative blocking force. In this paper, in order to enhance the blocking force, the Nation membranes with thickness of 0.22 mm, 0.32 mm, 0.42 mm, 0.64 mm and 0.8 mm were prepared by casting from liquid solution. By employing these Nation membranes, IPMCs with varying thickness were fabricated by electroless plating. The elastic modulus of the casted Nation membranes were obtained by a nano-indenter, and the current, the displacement and the blocking force were respectively measured by the apparatus for actuation test. Finally, the effects of the thickness on the performance of IPMC were analyzed with an electromechanical model. Experimental study and theory analysis indicate that as the thickness increases, the elastic modulus of Nation membrane and the blocking force of IPMC increase, however, the current and the displacement decrease.

Parameter identification and global sensitivity analysis of Xin'anjiang model using meta-modeling approach

Parameter identification, model calibration, and uncertainty quantification are important steps in the model-building process, and are necessary for obtaining credible results and valuable information. Sensitivity analysis of hydrological model is a key step in model uncertainty quantification, which can identify the dominant parameters, reduce the model calibration uncertainty, and enhance the model optimization efficiency. There are, however, some shortcomings in classical approaches, including the long duration of time and high computation cost required to quantitatively assess the sensitivity of a multiple-parameter hydrological model. For this reason, a two-step statistical evaluation framework using global techniques is presented. It is based on （1） a screening method （Morris） for qualitative ranking of parameters, and （2） a variance-based method integrated with a meta-model for quantitative sensitivity analysis, i.e., the Sobol method integrated with the response surface model （RSMSobol）. First, the Morris screening method was used to qualitatively identify the parameters＇ sensitivity, and then ten parameters were selected to quantify the sensitivity indices. Subsequently, the RSMSobol method was used to quantify the sensitivity, i.e., the first-order and total sensitivity indices based on the response surface model （RSM） were calculated. The RSMSobol method can not only quantify the sensitivity, but also reduce the computational cost, with good accuracy compared to the classical approaches. This approach will be effective and reliable in the global sensitivity analysis of a complex large-scale distributed hydrological model.

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.