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knowledge model for Electric Power Big Data Based on Ontology and Semantic Web

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CSEE Journal of Power and Energy Systems 2015年第1期1卷 19-27页

作者： Yanhao Huang Xiaoxin Zhou China Electric Power Research Institute China

It is very important for the development of electric power big data technology to use the electric power knowledge.A new electric power knowledge theory model is proposed here to solve the problem of normalized modeled electric power knowledge for the management and analysis of electric power big data.Current modeling techniques of electric power knowledge are viewed as inadequate because of the complexity and variety of the relationships among electric power system data.Ontology theory and semantic web technologies used in electric power systems and in many other industry domains provide a new kind of knowledge modeling method.Based on this,this paper proposes the structure,elements,basic calculations and multidimensional reasoning method of the new knowledge model.A modeling example of the regulations defined in electric power system operation standard is demonstrated.Different forms of the model and related technologies are also introduced,including electric power system standard modeling,multi-type data management,unstructured data searching,knowledge display and data analysis based on semantic expansion and reduction.Research shows that the new model developed here is powerful and can adapt to various knowledge expression requirements of electric power big data.With the development of electric power big data technology,it is expected that the knowledge model will be improved and will be used in more applications.

关键词： Electric power big data knowledge model ontology semantic web

Adaptive learning path recommendation model for examination-oriented education

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The Journal of China Universities of Posts and Telecommunications 2022年第4期29卷 77-88页

作者： Wang Jian Qiao Kuoyuan Yuan Yanlei Liu Xiaole Yang Jian School of Computer and Artificial Intelligence Zhengzhou UniversityZhengzhou 450001China Research and Development Department Tongfang Knowledge Network Technology Company LimitedBeijing 100192China The Teaching Affaires Office Zhengzhou Hi-Tech Zone Langyuehui Foreign Language Middle SchoolZhengzhou 450001China Yunnan Key Laboratory of Smart City in Cyberspace Security Yuxi Normal UniversityYuxi 653100China

Adaptive learning paths provide individual learning objectives that best match a learner’s characteristics.This is especially helpful when learners need to balance limited available learning time and multiple learning objectives.The automatic generation of personalized learning paths to improve learning efficiency has therefore attracted significant interest.However,most current research only focuses on providing learners with adaptive objects and sequences according to their own interests or learning goals given a normal amount of time or ordinary conditions.There is little research that can help learners to obtain the most important knowledge for a test in the shortest time possible,which is a typical scenario in exanimation-oriented education systems.This study aims to solve this problem by introducing a new approach that builds on existing methods.First,the eight properties in Gardner’s multiple intelligence theory are introduced into the present knowledge and learner models to define the relationship between learning objects(LOs)and learners,thereby improving recommendation accuracy rates.Then,a novel adaptive learning path recommendation model is presented where viable knowledge topologies,knowledge bases and the previously-established properties relating to a learner’s ability are combined by Dempster-Shafer(D-S)evidence theory.A series of practical experiments were performed to assess the approach’s adaptability,the appropriateness of the selected evidence and the effectiveness of the recommendations.In the results,it was found that the proposed learning path recommendation model helped learners learn the most important elements and obtain superior test grades when confronted with limited time for learning.

关键词： adaptive learning learning path recommendation Dempster-Shaferevidence theory knowledge model learner model

A knowledge model-and Growth model-Based Decision Support System for Wheat Management

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Agricultural Sciences in China 2003年第11期2卷 1212-1220页

作者： ZHU Yan, CAO Wei-xing, WANG Qi-meng, TIAN Yong-chao and PAN Jie(Key Laboratory of Crop Growth Regulation , Ministry of Agriculture/Nanjing Agricultural University, Nanjing 210095 , P. R. China) Key Laboratory of Crop Growth Regulation Ministry of Agriculture/Nanjing Agricultural University Nanjing 210095 P. R. China

By applying the system analysis principle and mathematical modeling technique to knowledge expression system for crop cultural management, the fundamental relationships and quantitative algorithms of wheat growth and management indices to variety types, ecological environments and production levels were analysed and extracted, and a dynamic knowledge model with temporal and spatial characters for wheat management(WheatKnow)was developed. By adopting the soft component characteristics as non language relevance , re-utilization and portable system maintenance. and by further integrating the wheat growth simulation model(WheatGrow)and intelligent system for wheat management, a comprehensive and digital knowledge model, growth model and component-based decision support system for wheat management(MBDSSWM)was established on the platforms of Visual C++ and Visual Basic. The MBDSSWM realized the effective integration and coupling of the prediction and decision-making functions for digital crop management.

关键词： Wheat management knowledge model Growth model Soft component Decision support system

A Dynamic knowledge model for Design of Suitable Sowing Date and Sowing Rate in Winter Wheat

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Agricultural Sciences in China 2002年第10期1卷 1116-1124页

作者： ZHU Yan, CAO Wei-xing, JIANG Dong and DAI Ting-bo(Key Laboratory of Crop Growth Regulation , Ministry of Agriculture /Nanjing Agricultural University,Nanjing 210095 , P. R . China) Key Laboratory of Crop Growth Regulation Ministry of Agriculture/Nanjing Agricultural University Nanjing 210095 P.R.China

Based on research concerning dynamic relationships of winter wheat growth to environments and production conditions, a winter wheat model for selecting suitable sowing date, population density and sowing rate under different varieties, spatial and temporal environments was developed. Case studies on sowing date with the data sets of five different eco-sites, three climatic years and soil fertility levels, and on population density and sowing rate with the data sets of two different variety types, three different soil types, soil fertility levels, sowing dates and grain yield levels indicate a good model performance for decision-making.

关键词： Winter wheat Sowing date Population density Sowing rate knowledge model

A Dynamic knowledge model for Nitrogen Fertilizationin Wheat Management

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Agricultural Sciences in China 2003年第8期2卷 850-858页

作者： ZHU Yan, CAO Wei-xing, DAI Ting-bo and SUN Chuan-fan(Key Laboratory of Crop Growth Regulation , Ministry of Agriculture/Nanjing Agricultural University , Nanjing 210095 , P.R.China) Key Laboratory of Crop Growth Regulation Ministry of Agriculture/Nanjing Agricultural University Nanjing 210095 P.R.China

By analyzing and extracting the research progress on nitrogen fertilization in wheat, a dynamic knowledge model for management decision-making on total nitrogen rate, ratios of organic to inorganic and of basal to dressing nitrogen under different environments and cultivars in wheat was developed with principle of nutrient balance and by integrating the quantitative effects of grain yield and quality targets, soil characters, variety traits and water management levels. Case studies on the nitrogen fertilization model with the data sets of different eco-sites, cultivars, soil fertility levels, grain yield and quality targets and water management levels indicate a good performance of the model system in decision-making and wide applicability.

关键词： Wheat Nutrient balance Nitrogen fertilization management knowledge model Digital decision-making

An OWL-Based Specification of Database Management Systems

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Computers, Materials & Continua 2022年第3期70卷 5537-5550页

作者： Sabin C.Buraga Daniel Amariei Octavian Dospinescu Alexandru Ioan Cuza University Faculty of Computer ScienceIasi700706Romania Alexandru Ioan Cuza University Faculty of Economics and Business AdministrationIasi700706Romania

In the context of a proliferation of DatabaseManagement Systems(DBMSs),we have envisioned and produced an OWL 2 ontology able to provide a high-level machine-processable description of the DBMSs domain.This conceptualization aims to facilitate a proper execution of various software engineering processes and database-focused administration tasks.Also,it can be used to improve the decision-making process for determining/selecting the appropriate DBMS,subject to specific requirements.The proposed model describes the most important features and aspects regarding the DBMS domain,including the support for various paradigms(relational,graph-based,key-value,tree-like,etc.),query languages,platforms(servers),plus running environments(desktop,Web,cloud),specific contexts—i.e.,focusing on optimizing queries,redundancy,security,performance,schema vs.schema-less approaches,programming languages/paradigms,and others.The process of populating the ontology with significant individuals(actual DBMSs)benefits from the existing knowledge exposed by free and open machine-processable knowledge bases,by using structured data fromWikipedia and related sources.The pragmatic use of our ontology is demonstrated by two educational software solutions based on current practices in Web application development,proving support for learning and experimenting key features of the actual semantic Web technologies and tools.This approach is also an example of using multiple knowledge from database systems,semanticWeb technologies,and software engineering areas.

关键词： Database management systems knowledge model web engineering

A knowledge model-AND GROWTH model-BASED MANAGEMENT SYSTEM FOR CORN

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A KNOWLEDGE MODEL-AND GROWTH MODEL-BASED MANAGEMENT SYSTEM F...

Modular Design of Complex Product Based on the Triple Fusion of Function/Feature/knowledge

The 3rd International Symposium on Intelligent Information Technology in Agriculture(ISIITA)

作者： Dingchun Yan Yeping Zhu Shijuan Li Institute of Agricultural Information Chinese Academy of Agricultural Sciences Beijing 100081 China

＜正＞By analyzing and extracting of the results of research on corn（Zeamays L.）cultural theories and technologies,a growth model（GM）and a knowledge model（KM）for corn management have been developed using the system’s analysis principle and mathematical modeling technique and which are driven by dynamic relationships and quantitative algorithms of corn growth and management indices to variety traits, eco-environments and production levels.Based on the platforms of Microsoft Visual C++.NET,a comprehensive and digital knowledge model- and growth model-based management system for corn （KMGMSC）has been established using soft component Case studies on the KMGMSC with the data sets of different climatic years,soil types and cultivars at different coo-sites,and comparative field experiments indicated a good performance of the model system in decision-making and guidance for corn management.

关键词： corn knowledge model growth model soft component

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Journal of Shanghai Jiaotong university(Science) 2010年第5期15卷 563-570页

作者：李宝童洪军李婷邱志惠陈玉宝 State Key Laboratory for Manufacturing Systems Engineering Xi'an Jiaotong University Department of Industrial Engineering University of Michigan-Dearborn

The modular design technology is of importance increasingly,as product structure is more and more complex.Modular design systems face challenging problems as the design information tends to be dynamic,redundant,and very large.This paper describes a novel approach for handling them.In this approach,a partition is firstly performed for the complex structural components by mapping functions to the structures layer by layer.Based on this partition,a comprehensive design matrix is then developed to identify the key design mode which is driven by a special function.The design process is also programmed by analyzing the coupled information on both the functional and structural hierarchies.Then,the integrated knowledge model based on object-oriented method and hybrid inference method is constructed.In this model,knowledge can be organized at hierarchical classification and expressed with different forms.Finally,the methodology developed has been applied to a real application in automobile cylinder block design and the results are presented.

关键词： modular design functional feature partition comprehensive design matrix knowledge model

Mechanism modeling and Nonlinear model adaptive-predictive control of Multiple Evaporators System in Sugar Mill

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Mechanism Modeling and Nonlinear model adaptive-predictive c...