多维度数据建模方法在中医药人才岗位胜任力匹配的应用分析

现如今,为满足人们对中医药人才的需求,需基于人工智能、复杂网络、深度学习以及大数据等先进技术的领域进行思考,通过对电子病历、移动医疗、智慧医疗以及智慧健康等内容的建设,挖掘社会内中医药人才的潜力,保证医学领域内的数据关系能够更加良好,进而强化中医药人才的岗位胜任力。基于此本文结合实际思考,首先简要分析了多维度数据建模方法,其次提出了多维度数据建模方法在中医药人才岗位胜任力匹配的应用措施。

斜拉桥损伤诊断有限元建模与数据提取方法研究

为便于斜拉桥损伤诊断的快速建模和分析,在已有研究方法基础上,基于ABAQUS有限元软件提供的PYTHON语言接口和GUI程序,提出了一种斜拉桥有限元建模与数据提取的方法。利用RSG构造器和调用Mdb对象中Part与Assembly对象编写程序,提出批量和点选相结合交互生成空间三维钢筋、预应力钢筋和斜拉索的方法;利用RSG构造器和调用Odb数据库中模型数据与结果数据的对象编写程序,提出点选、节点或单元集及编号3种形式相结合提取Odb数据库静力与动力瞬态响应数据到Excel表格的方法。通过算例展示了所提出方法的应用过程,表明了所提出方法的实用与高效。

电网调度业务主数据应用研究

对电网调度业务主数据管理现状进行了调查,分析了调度、方式等八大领域的业务、系统及其数据,梳理和提出了调度专业主数据,形成调度业务主数据建模方法,提出调度主数据管理内容,并设计了主数据管理组件的结构及功能。

Alternative 3D Modeling Approaches Based on Complex Multi-Source Geological Data Interpretation

Due to the complex nature of multi-source geological data, it is difficult to rebuild every geological structure through a single 3D modeling method. The multi-source data interpretation method put forward in this analysis is based on a database-driven pattern and focuses on the discrete and irregular features of geological data. The geological data from a variety of sources covering a range of accuracy, resolution, quantity and quality are classified and integrated according to their reliability and consistency for 3D modeling. The new interpolation-approximation fitting construction algorithm of geological surfaces with the non-uniform rational B-spline(NURBS) technique is then presented. The NURBS technique can retain the balance among the requirements for accuracy, surface continuity and data storage of geological structures. Finally, four alternative 3D modeling approaches are demonstrated with reference to some examples, which are selected according to the data quantity and accuracy specification. The proposed approaches offer flexible modeling patterns for different practical engineering demands.

DEM Production/Updating Based on Environmental Variables Modeling and Conflation of Data Sources

Availability of digital elevation models （DEMs） of a high quality is becoming more and more important in spatial studies. Standard methods for DEM creation use only intentionally acquired data sources. Two approaches which employ various types of data sets for DEM production are proposed： （1） Method of weighted sum of different data sources with morphological enhancement that conflates any additional data sources to principal DEM, and （2） DEM updating methods of modeling absolute and relative temporal changes, considering landslides, earthquakes, quarries, watererosion, building and highway constructions, etc. Spatial modeling of environmental variables concerning both approaches for （a） quality control of data sources, considering regions, （b） pre-processing of data sources, and （c） processing of the final DEM, have been applied. The variables are called rate of karst, morphologic roughness （modeled from slope, profile curvature and elevation）, characteristic features, rate of forestation, hydrological network, and rate of urbanization. Only the variables evidenced as significant were used in spatial modeling to generate homogeneous regions in spatial modeling a-c. The production process uses different regions to define high quality conflation of data sources to the final DEM. The methodology had been confirmed by case studies. The result is an overall high quality DEM with various well-known parameters.

QoS Evaluation for Web Service Recommendation

Web service recommendation is one of the most important fi elds of research in the area of service computing. The two core problems of Web service recommendation are the prediction of unknown Qo S property values and the evaluation of overall Qo S according to user preferences. Aiming to address these two problems and their current challenges, we propose two efficient approaches to solve these problems. First, unknown Qo S property values were predicted by modeling the high-dimensional Qo S data as tensors, by utilizing an important tensor operation, i.e., tensor composition, to predict these Qo S values. Our method, which considers all Qo S dimensions integrally and uniformly, allows us to predict multi-dimensional Qo S values accurately and easily. Second, the overall Qo S was evaluated by proposing an efficient user preference learning method, which learns user preferences based on users' ratings history data, allowing us to obtain user preferences quantifiably and accurately. By solving these two core problems, it became possible to compute a realistic value for the overall Qo S. The experimental results showed our proposed methods to be more efficient than existing methods.

Selection model of trip time for rural population

Referring to the 1 248 survey data of rural population in 14 provinces of China, the influencing factors of trip time choice were analyzed. Based on the basic theory of disaggregate model and its modelling method, nine grades were selected as the alternatives of trip time, the variables affecting time choice and the method getting their values were determined, and a multinomial logit (MNL) model was developed. Another 1 200 trip data of rural population were selected to testify the model's validity. The result shows that the maximum absolute error of each period between calculated value and statistic is 3.6%, so MNL model has high calculation accuracy.

Cooperative Communication with Asymmetric Channel State Information: A Contract Theoretic Modeling Approach

In relay-assisted cooperative communication,relay nodes help forwarding the information of a source node in case of link failure between the source and a destination.Although user cooperation improves the overall efficiency of the network,it requires incentive to stimulate potential relay nodes to assist the source by forwarding its data to the destination.Moreover,the potential relays are better informed than the source about their channel conditions to destination,which results in asymmetric information between the source and the relays.In this paper,we study the problem of lack of forwarding incentive in cooperative communication when channel state information of relays is private information and not known by the source.To tackle this problem,we apply the principle of contract theory to a cooperative wireless system.Source first designs incentive compatible and individually rational contract,consisting of a set of power-credit pairs.Then it broadcasts contract items to nearby nodes.Once the source node receives reply messages from the volunteer relays,it chooses one or more relays based on its requirements and communication starts.Simulation results show how credit assignment works in order to stimulate relays to cooperate and prevents relays from cheating behavior.

The Application of Computer Simulation Technology in Building Design

From the simulation software selection, meteorological data collection, model, boundary conditions, calculation setting and evaluation indicators, the paper summarize simulation method of wind, light and sound, summarize three kinds of environmental. The paper study on optimization analysis method of green building from four aspects of building orientation, architectural form, architectural layout and indoor environment, and puts forward the optimization scheme of the typical simulation analysis of simple questions; provide guidance for optimizing the design of green building. Finally, ECOTECT can adapt to the current domestic engineering design and consulting on green building simulation and design requirements, and has a broad application prospect.

Automated Design and Visualization System of a House Foundation from Blocks

This article analyzes creation methods of automated design system, presents design system of a house foundation from blocks. The creation methods of automated design system of a house foundation from blocks are discovered with Unified Modeling Language. Analyzed objects-classes： block, specification, model. Graphical system can design foundation, form specification of objects and create 3D model of house foundation. There are several types and different dimensions of concrete blocks. The program optimally arranges selected blocks so that monolithic parts will be minimal volume. Program selects a house foundation blocks from database by using ActiveX Data Objects technology, which by programming method connects drawing and database. Drawing＇s graphical objects have additional data from which exchange of data between graphical system and database is executed. Visualization system and example of house foundation from blocks project with specifications is presented. Creation problems of automated design system are discussed and conclusions are made.

A time-series modeling method based on the boosting gradient-descent theory

The forecasting of time-series data plays an important role in various domains. It is of significance in theory and application to improve prediction accuracy of the time-series data. With the progress in the study of time-series, time-series forecasting model becomes more complicated, and consequently great concern has been drawn to the techniques in designing the forecasting model. A modeling method which is easy to use by engineers and may generate good results is in urgent need. In this paper, a gradient-boost AR ensemble learning algorithm (AREL) is put forward. The effectiveness of AREL is assessed by theoretical analyses, and it is demonstrated that this method can build a strong predictive model by assembling a set of AR models. In order to avoid fitting exactly any single training example, an insensitive loss function is introduced in the AREL algorithm, and accordingly the influence of random noise is reduced. To further enhance the capability of AREL algorithm for non-stationary time-series, improve the robustness of algorithm, discourage overfitting, and reduce sensitivity of algorithm to parameter settings, a weighted kNN prediction method based on AREL algorithm is presented. The results of numerical testing on real data demonstrate that the proposed modeling method and prediction method are effective.

Three-dimensional geological modeling and its application in Digital Mine

The 3D geological modeling is the prerequisite and core foundation for Digital Mine.Although this new technology brings new opportunities and motivation for the mineral exploration industry,it still has many difficulties to be solved in this area.Based on the characteristics of mine data and the aim of Digital Mine construction,this paper introduces a theory including multi-source data coupling,multi-modeling methods integration,multi-resolution visualization and detection,and multidimensional data analysis and application.By analyzing problems such as the uncertainty in each step of the modeling process,we designed a novel modeling method that can be applied to the complex geological body modeling,mineral resource/reserve estimation,and the mining exploration engineering.Along with the process of mine exploration,development,and reclamation,3D modeling undergoes the process of"construction-simulation-revision"during which the 3D model is able to be dynamically updated and gradually improved.Based on the result of practical utilization,it is proven that the methodology introduced by this paper can be used to build an effective 3D model by fully using the mining data under the control of spatial information quality evaluation.Our experiments show that such a 3D model can be used to evaluate the mine resource and provide the scientific evidence to improve mining efficiency during the various stages of evolvement process in mine.

Research and application of flood detention modeling for ponds and small reservoirs based on remote sensing data

This paper proposes a method of small reservoir flood detention modeling that utilizes data from the American land resources satellite Landsat TM/ETM+. Precipitation and potential evapotranspiration are taken as the control conditions in this method on the basis of basin terrain classification. The objective of this method is to solve the question of a small-scale water conservancy project’s influence on flood forecasting precision, which can be used in the basin with multitudinous small reservoirs in the upstream region and can help estimate non-runoff data for small reservoir runoff. Taking the 20060826 flood as an example, the flood detention quantity of 19 small reservoirs is modeled. The results show that the absolute error of the total flood detention quantity is 0.2×10 4 m 3 , and the relative error is 0.12%. The flood detention quantity of small reservoirs in the entire basin is then modeled using this method, and the primary flood forecasting model is adjusted. After adjustment, the precision is significantly improved, with the relative error decreasing from 31.8% to 10.1%.