MedTrad＋ is an expert system for African Traditional Medicine where actors are often illiterate. Its originality lies in the use of icons instead of textual content of facts. It has been created by GExpert＋ which is...MedTrad＋ is an expert system for African Traditional Medicine where actors are often illiterate. Its originality lies in the use of icons instead of textual content of facts. It has been created by GExpert＋ which is An Expert system Generator based on the use of icons in a Web environment. With its iconic interface GExpert＋ allows any user to overcome any intermediary for the management and the use of its knowledge base. Traditional healers from Yamoussoukro region are working toward its validation.展开更多
In the context of power generation companies, vast amounts of specialized data and expert knowledge have been accumulated. However, challenges such as data silos and fragmented knowledge hinder the effective utilizati...In the context of power generation companies, vast amounts of specialized data and expert knowledge have been accumulated. However, challenges such as data silos and fragmented knowledge hinder the effective utilization of this information. This study proposes a novel framework for intelligent Question-and-Answer (Q&A) systems based on Retrieval-Augmented Generation (RAG) to address these issues. The system efficiently acquires domain-specific knowledge by leveraging external databases, including Relational Databases (RDBs) and graph databases, without additional fine-tuning for Large Language Models (LLMs). Crucially, the framework integrates a Dynamic Knowledge Base Updating Mechanism (DKBUM) and a Weighted Context-Aware Similarity (WCAS) method to enhance retrieval accuracy and mitigate inherent limitations of LLMs, such as hallucinations and lack of specialization. Additionally, the proposed DKBUM dynamically adjusts knowledge weights within the database, ensuring that the most recent and relevant information is utilized, while WCAS refines the alignment between queries and knowledge items by enhanced context understanding. Experimental validation demonstrates that the system can generate timely, accurate, and context-sensitive responses, making it a robust solution for managing complex business logic in specialized industries.展开更多
Remote driving,an emergent technology enabling remote operations of vehicles,presents a significant challenge in transmitting large volumes of image data to a central server.This requirement outpaces the capacity of t...Remote driving,an emergent technology enabling remote operations of vehicles,presents a significant challenge in transmitting large volumes of image data to a central server.This requirement outpaces the capacity of traditional communication methods.To tackle this,we propose a novel framework using semantic communications,through a region of interest semantic segmentation method,to reduce the communication costs by transmitting meaningful semantic information rather than bit-wise data.To solve the knowledge base inconsistencies inherent in semantic communications,we introduce a blockchain-based edge-assisted system for managing diverse and geographically varied semantic segmentation knowledge bases.This system not only ensures the security of data through the tamper-resistant nature of blockchain but also leverages edge computing for efficient management.Additionally,the implementation of blockchain sharding handles differentiated knowledge bases for various tasks,thus boosting overall blockchain efficiency.Experimental results show a great reduction in latency by sharding and an increase in model accuracy,confirming our framework's effectiveness.展开更多
The“Opinions on Comprehensively Deepening Curriculum Reform to Fulfill the Fundamental Task of Strengthening Moral Education”,issued by China’s Ministry of Education in 2015,explicitly identified Project-Based Lear...The“Opinions on Comprehensively Deepening Curriculum Reform to Fulfill the Fundamental Task of Strengthening Moral Education”,issued by China’s Ministry of Education in 2015,explicitly identified Project-Based Learning(PBL)as a key strategy for cultivating students’core competencies.Since then,PBL has been widely implemented as a pilot initiative in primary and secondary schools,gaining increasing influence.Analyzing the intellectual foundations of PBL research in China can offer valuable insights into its theoretical and practical dimensions.This study uses CiteSpace to examine 156 PBL-related articles from the CSSCI database,revealing that the knowledge base of PBL research is primarily built on two major domains.The first is the theoretical foundation,characterized by frequently cited literature focusing on the conceptual framework,educational value,interdisciplinary approaches,core competency cultivation,and instructional objectives of PBL.The second is empirical research,where highly cited studies include case analyses across K–12 settings,general high schools,and higher education institutions.Moving forward,future research on PBL should explore its meaning and value from a dual-subject and integrated perspective,expand case studies to include vocational education,and further promote the interdisciplinary development of core competencies through PBL.展开更多
This paper presents a framework called logical knowledge object (LKO),which is taken as a basis of the dependable development of knowledge based systems(KBSs). LKO combines logic programming and object-oriented progra...This paper presents a framework called logical knowledge object (LKO),which is taken as a basis of the dependable development of knowledge based systems(KBSs). LKO combines logic programming and object-oriented programming paradigms, where objects are viewed as abstractions with states,constraints, behaviors and inheritance. The operational semantics defined in the style of natural semantics is simple and clear. A hybrid knowledge represen-tation amalgamating rule, frame, semantic network and blackboard is available for both most structured and flat knowledge. The management of knowledge bases has been formally specified. Accordingly, LKO is well suited for the formal representation of knowledge and requirements of KBSs. Based on the framework, verification techniques are also explored to enhance the analysis of requirement specifications and the validation of KBSs. In addition, LKO pro-vides a methodology for the development of KBSs, applying the concepts of rapid prototyping and top-down design to deal with changing and incomplete requirements, and to provide multiple abstract models of the domain, where formal methods might be used at each abstract level.展开更多
To increase efficiency in fierce competition,it is necessary and urgent to improve the standard of production planning for shipbuilding.The construction of curved blocks is the bottleneck to improve the efficiency of ...To increase efficiency in fierce competition,it is necessary and urgent to improve the standard of production planning for shipbuilding.The construction of curved blocks is the bottleneck to improve the efficiency of shipbuilding.Thus it is a key breakthrough for higher shipbuilding productivity to study the curved block production.By analyzing the scheduling problem in curved blocks production,we propose an intelligent curved block production scheduling method and its system based on a knowledge base,and show the main process of the system.The functions of the system include data management,assembly plan generation,plan adjustment,and plan evaluation.In order to deal with the actual situation and inherit the empirical knowledge,the system extracts some rules to control block selecting,algorithm selection,and evaluation thresholds to build a production decision-making knowledge base in the curved block scheduling system.The proposed knowledge base could be referred and modified by users,especially after a few interactions between the users and the knowledge base.The final assembly plan can be visualized and evaluated to facilitate the observation of plan implementation and effects of the decisions in the process.Finally,the system is verified by a large shipyard in Shanghai using real data and the results illustrate that the proposed method can perform the knowledge-based scheduling for curved blocks construction effectively.展开更多
In order to enhance the intelligent level of system and improve the interaetivity with other systems, a knowledge and XML based computer aided process planning （CAPP） system is implemented. It includes user manageme...In order to enhance the intelligent level of system and improve the interaetivity with other systems, a knowledge and XML based computer aided process planning （CAPP） system is implemented. It includes user management, bill of materials（BOM） management, knowledge based process planning, knowledge management and database maintaining sub-systems. This kind of nesting knowledge representation method the system provided can represent complicated arithmetic and logical relationship to deal with process planning tasks. With the representation and manipulation of XML based technological file, the system solves some important problems in web environment such as information interactive efficiency and refreshing of web page. The CAPP system is written in ASP VBScript, JavaScript, Visual C＋＋ languages and Oracle database. At present, the CAPP system is running in Shenyang Machine Tools. The functions of it meet the requirements of enterprise production.展开更多
In this paper, the structure characteristics of open complex giant systems are concretely analysed in depth, thus the view and its significance to support the meta synthesis engineering with manifold knowledge models...In this paper, the structure characteristics of open complex giant systems are concretely analysed in depth, thus the view and its significance to support the meta synthesis engineering with manifold knowledge models are clarified. Furthermore, the knowledge based multifaceted modeling methodology for open complex giant systems is emphatically studied. The major points are as follows: (1) nonlinear mechanism and general information partition law; (2) from the symmetry and similarity to the acquisition of construction knowledge; (3) structures for hierarchical and nonhierarchical organizations; (4) the integration of manifold knowledge models; (5) the methodology of knowledge based multifaceted modeling.展开更多
A new structure of ESKD (expert system based on knowledge discovery system KD (D&K)) is first presented on the basis of KD (D&K)-a synthesized knowledge discovery system based on double-base (database and know...A new structure of ESKD (expert system based on knowledge discovery system KD (D&K)) is first presented on the basis of KD (D&K)-a synthesized knowledge discovery system based on double-base (database and knowledge base) cooperating mechanism. With all new features, ESKD may form a new research direction and provide a great probability for solving the wealth of knowledge in the knowledge base. The general structural frame of ESKD and some sub-systems among ESKD have been described, and the dynamic knowledge base based on double-base cooperating mechanism has been emphased on. According to the result of demonstrative experi- ment, the structure of ESKD is effective and feasible.展开更多
The aim, characteristics and requirements of stampability evaluation are identified. As sampability evaluation is highly skill intensive and requires a wide variety of design expertise and knowledge, a knowledge based...The aim, characteristics and requirements of stampability evaluation are identified. As sampability evaluation is highly skill intensive and requires a wide variety of design expertise and knowledge, a knowledge based system is proposed for implementing the stampability evaluation. The stampability evaluation knowledge representation, and processing phases are illustrated. A case study demonstrates the feasibility of the knowledge based approach to stampability evaluation.展开更多
As legal cases grow in complexity and volume worldwide,integrating machine learning and artificial intelligence into judicial systems has become a pivotal research focus.This study introduces a comprehensive framework...As legal cases grow in complexity and volume worldwide,integrating machine learning and artificial intelligence into judicial systems has become a pivotal research focus.This study introduces a comprehensive framework for verdict recommendation that synergizes rule-based methods with deep learning techniques specifically tailored to the legal domain.The proposed framework comprises three core modules:legal feature extraction,semantic similarity assessment,and verdict recommendation.For legal feature extraction,a rule-based approach leverages Black’s Law Dictionary and WordNet Synsets to construct feature vectors from judicial texts.Semantic similarity between cases is evaluated using a hybrid method that combines rule-based logic with an LSTM model,analyzing the feature vectors of query cases against a legal knowledge base.Verdicts are then recommended through a rule-based retrieval system,enhanced by predefined legal statutes and regulations.By merging rule-based methodologies with deep learning,this framework addresses the interpretability challenges often associated with contemporary AImodels,thereby enhancing both transparency and generalizability across diverse legal contexts.The system was rigorously tested using a legal corpus of 43,000 case laws across six categories:Criminal,Revenue,Service,Corporate,Constitutional,and Civil law,ensuring its adaptability across a wide range of judicial scenarios.Performance evaluation showed that the feature extraction module achieved an average accuracy of 91.6%with an F-Score of 95%.The semantic similarity module,tested using Manhattan,Euclidean,and Cosine distance metrics,achieved 88%accuracy and a 93%F-Score for short queries(Manhattan),89%accuracy and a 93.7%F-Score for medium-length queries(Euclidean),and 87%accuracy with a 92.5%F-Score for longer queries(Cosine).The verdict recommendation module outperformed existing methods,achieving 90%accuracy and a 93.75%F-Score.This study highlights the potential of hybrid AI frameworks to improve judicial decision-making and streamline legal processes,offering a robust,interpretable,and adaptable solution for the evolving demands of modern legal systems.展开更多
In this paper, the knowledge based enterprise is considered as an organism, which possesses a set of capabilities. The organizational structure model of knowledge based enterprise organism is described in order to pos...In this paper, the knowledge based enterprise is considered as an organism, which possesses a set of capabilities. The organizational structure model of knowledge based enterprise organism is described in order to possess the essential capacity set. A dynamic capacity set is defined and analyzed based on the definition of the growth and development for knowledge based enterprise organism. The structure of the capacity base, a subset of the capacity set, is optimized for different periods of the organism ...展开更多
Aim To analyse the influence of knowledge base on the performance of the fuzzy controller of the electrohydraulic position control system,and to determine their selection cri- teria. Methods Experiments based on diffe...Aim To analyse the influence of knowledge base on the performance of the fuzzy controller of the electrohydraulic position control system,and to determine their selection cri- teria. Methods Experiments based on different membership functions,scaling factors and con-trol rules were done separately.The experiment results and the influence of different know- ledge base on the control performance were analysed in theory so that criteria of selcting knowledge base can be summarized correctly.Results Knowledge base,including membershipfunctions, scaling factors and control rules,has a crucial effect on the fuzzy control system.Suitably selected knowledge base can lead to good control performance of fuzzy control sys-tem. Conclusion Being symmetric,having an intersection ratio of 1 and satisfying width con- dition are three necessities for selecting membership functions.Selecting scaling factors dependson both the system requirement and a comprehensive analysis in the overshoot,oscillation, rising time and stability. Integrity and continuity must be guaranteed when determining control rules.展开更多
Equipment selection for industrial process usually requires the extensive participation of industrial experts and technologists, which causes a serious waste of resources. This work presents an equipment selection kno...Equipment selection for industrial process usually requires the extensive participation of industrial experts and technologists, which causes a serious waste of resources. This work presents an equipment selection knowledge base system for industrial styrene process(S-ESKBS) based on the ontology technology. This structure includes a low-level knowledge base and a top-level interactive application. As the core part of the S-ESKBS, the low-level knowledge base consists of the equipment selection ontology library, equipment selection rule set and Pellet inference engine. The top-level interactive application is implemented using S-ESKBS, including the parsing storage layer, inference query layer and client application layer. Case studies for the industrial styrene process equipment selection of an analytical column and an alkylation reactor are demonstrated to show the characteristics and implementability of the S-ESKBS.展开更多
After analyzing the welding procedure knowledge in Chinese national standards for welding procedure qualification of steel pressure vessel from the point of establishing expert system, it can be divided into five type...After analyzing the welding procedure knowledge in Chinese national standards for welding procedure qualification of steel pressure vessel from the point of establishing expert system, it can be divided into five types of knowledge, i. e. practice, definition, regularity, process and description knowledge. The knowledge expression methods are established according to the different type of welding procedure knowledge. The reasoning process based on rule is adopted. And the reasoning engine is embedded among objects integrated with the knowledge base.展开更多
Setting up a knowledge base is a helpful way to optimize the operation of the polyethylene process by improving the performance and the ef ciency of reuse of information and knowledge two critical ele- ments in polyet...Setting up a knowledge base is a helpful way to optimize the operation of the polyethylene process by improving the performance and the ef ciency of reuse of information and knowledge two critical ele- ments in polyethylene smart manufacturing. In this paper, we propose an overall structure for a knowl- edge base based on practical customer demand and the mechanism of the polyethylene process. First, an ontology of the polyethylene process constructed using the seven-step method is introduced as a carrier for knowledge representation and sharing. Next, a prediction method is presented for the molecular weight distribution (MWD) based on a back propagation (BP) neural network model, by analyzing the relationships between the operating conditions and the parameters of the MWD. Based on this network, a differential evolution algorithm is introduced to optimize the operating conditions by tuning the MWD. Finally, utilizing a MySQL database and the Java programming language, a knowledge base system for the operation optimization of the polyethylene process based on a browser/server framework is realized.展开更多
Aiming at the relation linking task for question answering over knowledge base,especially the multi relation linking task for complex questions,a relation linking approach based on the multi-attention recurrent neural...Aiming at the relation linking task for question answering over knowledge base,especially the multi relation linking task for complex questions,a relation linking approach based on the multi-attention recurrent neural network(RNN)model is proposed,which works for both simple and complex questions.First,the vector representations of questions are learned by the bidirectional long short-term memory(Bi-LSTM)model at the word and character levels,and named entities in questions are labeled by the conditional random field(CRF)model.Candidate entities are generated based on a dictionary,the disambiguation of candidate entities is realized based on predefined rules,and named entities mentioned in questions are linked to entities in knowledge base.Next,questions are classified into simple or complex questions by the machine learning method.Starting from the identified entities,for simple questions,one-hop relations are collected in the knowledge base as candidate relations;for complex questions,two-hop relations are collected as candidates.Finally,the multi-attention Bi-LSTM model is used to encode questions and candidate relations,compare their similarity,and return the candidate relation with the highest similarity as the result of relation linking.It is worth noting that the Bi-LSTM model with one attentions is adopted for simple questions,and the Bi-LSTM model with two attentions is adopted for complex questions.The experimental results show that,based on the effective entity linking method,the Bi-LSTM model with the attention mechanism improves the relation linking effectiveness of both simple and complex questions,which outperforms the existing relation linking methods based on graph algorithm or linguistics understanding.展开更多
Currently,knowledge-based systems are generally updated manually,resulting in long cycles,low efficiency,and difficulty in ensuring comprehensive and systematic supplementary content.To address this issue,a knowledge-...Currently,knowledge-based systems are generally updated manually,resulting in long cycles,low efficiency,and difficulty in ensuring comprehensive and systematic supplementary content.To address this issue,a knowledge-based system automatic updating method based on webpage information and user files is proposed for combine harvesters.The knowledge storage structure in an electronic warehouse is analyzed,and knowledge and data types are determined.A crawler designed to locate the combine harvester-related information in the target webpage realizes the acquisition and sorting of webpage knowledge and data.The type of file uploaded by the user is set based on the knowledge base and data type;the content of the user file is extracted and filtered,and the knowledge and data of the knowledge-based system are user-defined.The organized knowledge and data are stored or updated in the knowledge base to achieve automatic updating of the knowledge-based system based on webpage information and user files.The test results show that based on user file updates,the knowledge and data of the knowledge-based system can be customized according to user needs.This meets user requirements and allows for effective automatic updates based on webpages after automatic updating of the knowledge base based on webpages.After the automatic updating of the knowledge base based on webpage information is triggered,the knowledge and data from the three webpages that were initially crawled and read are automatically updated to the knowledge base in 5.265 s.Realizing the automatic updating of knowledge and data can shorten the updating period,maintain the effectiveness and practicability of the knowledge-based system,ensure the scientific and advanced nature of the intelligent design process,and provide technical models and methods for the knowledge collection of similar knowledge-based systems.展开更多
Based on the knowledge representation and knowledge reasoning, this paper addresses the creation of the multi-attribute knowledge base on the basis of hybrid knowledge representation, with the help of object-oriented ...Based on the knowledge representation and knowledge reasoning, this paper addresses the creation of the multi-attribute knowledge base on the basis of hybrid knowledge representation, with the help of object-oriented programming language and relational database. Compared with general knowledge base, multi-attribute knowledge base can enhance the ability of knowledge processing and application; integrate the heterogeneous knowledge, such as model, symbol, case-based sample knowledge; and support the whole decision process by integrated reasoning.展开更多
The present work deals with the development of an Ontology-Based Knowledge Network of soil/water physicochemical & biological properties (soil/water concepts), derived from ASTM Standard Methods (ASTMi,n) and rele...The present work deals with the development of an Ontology-Based Knowledge Network of soil/water physicochemical & biological properties (soil/water concepts), derived from ASTM Standard Methods (ASTMi,n) and relevant scientific/applicable references (published papers—PPi,n) to fill up/bridge the gap of the information science between cited Standards and infiltration discipline conceptual vocabulary providing accordingly a dedicated/internal Knowledge Base (KB). This attempt constitutes an innovative approach, since it is based on externalizing domain knowledge in the form of Ontology-Based Knowledge Networks, incorporating standardized methodology in soil engineering. The ontology soil/water concepts (semantics) of the developed network correspond to soil/water physicochemical & biological properties, classified in seven different generations that are distinguished/located in infiltration/percolation process of contaminated water through soil porous media. The interconnections with arcs between corresponding concepts/properties among the consecutive generations are defined by the relationship of dependent and independent variables. All these interconnections are documented according to the below three ways: 1) dependent and independent variables interconnected by using the logical operator “<em>depends on</em>” quoting existent explicit functions and equations;2) dependent and independent variables interconnected by using the logical operator “<em>depends on</em>” quoting produced implicit functions, according to Rayleigh’s method of indices;3) dependent and independent variables interconnected by using the logical operator “<em>related to</em>” based on a logical dependence among the examined nodes-concepts-variables. The aforementioned approach provides significant advantages to semantic web developers and web users by means of prompt knowledge navigation, tracking, retrieval and usage.展开更多
文摘MedTrad＋ is an expert system for African Traditional Medicine where actors are often illiterate. Its originality lies in the use of icons instead of textual content of facts. It has been created by GExpert＋ which is An Expert system Generator based on the use of icons in a Web environment. With its iconic interface GExpert＋ allows any user to overcome any intermediary for the management and the use of its knowledge base. Traditional healers from Yamoussoukro region are working toward its validation.
文摘In the context of power generation companies, vast amounts of specialized data and expert knowledge have been accumulated. However, challenges such as data silos and fragmented knowledge hinder the effective utilization of this information. This study proposes a novel framework for intelligent Question-and-Answer (Q&A) systems based on Retrieval-Augmented Generation (RAG) to address these issues. The system efficiently acquires domain-specific knowledge by leveraging external databases, including Relational Databases (RDBs) and graph databases, without additional fine-tuning for Large Language Models (LLMs). Crucially, the framework integrates a Dynamic Knowledge Base Updating Mechanism (DKBUM) and a Weighted Context-Aware Similarity (WCAS) method to enhance retrieval accuracy and mitigate inherent limitations of LLMs, such as hallucinations and lack of specialization. Additionally, the proposed DKBUM dynamically adjusts knowledge weights within the database, ensuring that the most recent and relevant information is utilized, while WCAS refines the alignment between queries and knowledge items by enhanced context understanding. Experimental validation demonstrates that the system can generate timely, accurate, and context-sensitive responses, making it a robust solution for managing complex business logic in specialized industries.
基金supported in part by the National Natural Science Foundation of China under Grant No.62062031in part by the MIC/SCOPE#JP235006102+2 种基金in part by JST ASPIRE Grant Number JPMJAP2325in part by ROIS NII Open Collaborative Research under Grant 24S0601in part by collaborative research with Toyota Motor Corporation,Japan。
文摘Remote driving,an emergent technology enabling remote operations of vehicles,presents a significant challenge in transmitting large volumes of image data to a central server.This requirement outpaces the capacity of traditional communication methods.To tackle this,we propose a novel framework using semantic communications,through a region of interest semantic segmentation method,to reduce the communication costs by transmitting meaningful semantic information rather than bit-wise data.To solve the knowledge base inconsistencies inherent in semantic communications,we introduce a blockchain-based edge-assisted system for managing diverse and geographically varied semantic segmentation knowledge bases.This system not only ensures the security of data through the tamper-resistant nature of blockchain but also leverages edge computing for efficient management.Additionally,the implementation of blockchain sharding handles differentiated knowledge bases for various tasks,thus boosting overall blockchain efficiency.Experimental results show a great reduction in latency by sharding and an increase in model accuracy,confirming our framework's effectiveness.
基金Provincial-Level Quality Engineering Project,Preschool Education Teacher Training Base of Fuyang Normal University(Project No.:2023cyts023)University-Level Research Team Project,Collaborative Innovation Center for Basic Education in Northern Anhui(Project No.:kytd202418)。
文摘The“Opinions on Comprehensively Deepening Curriculum Reform to Fulfill the Fundamental Task of Strengthening Moral Education”,issued by China’s Ministry of Education in 2015,explicitly identified Project-Based Learning(PBL)as a key strategy for cultivating students’core competencies.Since then,PBL has been widely implemented as a pilot initiative in primary and secondary schools,gaining increasing influence.Analyzing the intellectual foundations of PBL research in China can offer valuable insights into its theoretical and practical dimensions.This study uses CiteSpace to examine 156 PBL-related articles from the CSSCI database,revealing that the knowledge base of PBL research is primarily built on two major domains.The first is the theoretical foundation,characterized by frequently cited literature focusing on the conceptual framework,educational value,interdisciplinary approaches,core competency cultivation,and instructional objectives of PBL.The second is empirical research,where highly cited studies include case analyses across K–12 settings,general high schools,and higher education institutions.Moving forward,future research on PBL should explore its meaning and value from a dual-subject and integrated perspective,expand case studies to include vocational education,and further promote the interdisciplinary development of core competencies through PBL.
文摘This paper presents a framework called logical knowledge object (LKO),which is taken as a basis of the dependable development of knowledge based systems(KBSs). LKO combines logic programming and object-oriented programming paradigms, where objects are viewed as abstractions with states,constraints, behaviors and inheritance. The operational semantics defined in the style of natural semantics is simple and clear. A hybrid knowledge represen-tation amalgamating rule, frame, semantic network and blackboard is available for both most structured and flat knowledge. The management of knowledge bases has been formally specified. Accordingly, LKO is well suited for the formal representation of knowledge and requirements of KBSs. Based on the framework, verification techniques are also explored to enhance the analysis of requirement specifications and the validation of KBSs. In addition, LKO pro-vides a methodology for the development of KBSs, applying the concepts of rapid prototyping and top-down design to deal with changing and incomplete requirements, and to provide multiple abstract models of the domain, where formal methods might be used at each abstract level.
基金the China High-Tech Ship Project of the Ministry of Industry and Information Technology(No.2021-51(MC-202032-Z08))。
文摘To increase efficiency in fierce competition,it is necessary and urgent to improve the standard of production planning for shipbuilding.The construction of curved blocks is the bottleneck to improve the efficiency of shipbuilding.Thus it is a key breakthrough for higher shipbuilding productivity to study the curved block production.By analyzing the scheduling problem in curved blocks production,we propose an intelligent curved block production scheduling method and its system based on a knowledge base,and show the main process of the system.The functions of the system include data management,assembly plan generation,plan adjustment,and plan evaluation.In order to deal with the actual situation and inherit the empirical knowledge,the system extracts some rules to control block selecting,algorithm selection,and evaluation thresholds to build a production decision-making knowledge base in the curved block scheduling system.The proposed knowledge base could be referred and modified by users,especially after a few interactions between the users and the knowledge base.The final assembly plan can be visualized and evaluated to facilitate the observation of plan implementation and effects of the decisions in the process.Finally,the system is verified by a large shipyard in Shanghai using real data and the results illustrate that the proposed method can perform the knowledge-based scheduling for curved blocks construction effectively.
基金This project is supported by National Hi-tech Research and Development Program of China(863 Program, No. 2001AA412020, No. 2001AA412210).
文摘In order to enhance the intelligent level of system and improve the interaetivity with other systems, a knowledge and XML based computer aided process planning （CAPP） system is implemented. It includes user management, bill of materials（BOM） management, knowledge based process planning, knowledge management and database maintaining sub-systems. This kind of nesting knowledge representation method the system provided can represent complicated arithmetic and logical relationship to deal with process planning tasks. With the representation and manipulation of XML based technological file, the system solves some important problems in web environment such as information interactive efficiency and refreshing of web page. The CAPP system is written in ASP VBScript, JavaScript, Visual C＋＋ languages and Oracle database. At present, the CAPP system is running in Shenyang Machine Tools. The functions of it meet the requirements of enterprise production.
文摘In this paper, the structure characteristics of open complex giant systems are concretely analysed in depth, thus the view and its significance to support the meta synthesis engineering with manifold knowledge models are clarified. Furthermore, the knowledge based multifaceted modeling methodology for open complex giant systems is emphatically studied. The major points are as follows: (1) nonlinear mechanism and general information partition law; (2) from the symmetry and similarity to the acquisition of construction knowledge; (3) structures for hierarchical and nonhierarchical organizations; (4) the integration of manifold knowledge models; (5) the methodology of knowledge based multifaceted modeling.
文摘A new structure of ESKD (expert system based on knowledge discovery system KD (D&K)) is first presented on the basis of KD (D&K)-a synthesized knowledge discovery system based on double-base (database and knowledge base) cooperating mechanism. With all new features, ESKD may form a new research direction and provide a great probability for solving the wealth of knowledge in the knowledge base. The general structural frame of ESKD and some sub-systems among ESKD have been described, and the dynamic knowledge base based on double-base cooperating mechanism has been emphased on. According to the result of demonstrative experi- ment, the structure of ESKD is effective and feasible.
文摘The aim, characteristics and requirements of stampability evaluation are identified. As sampability evaluation is highly skill intensive and requires a wide variety of design expertise and knowledge, a knowledge based system is proposed for implementing the stampability evaluation. The stampability evaluation knowledge representation, and processing phases are illustrated. A case study demonstrates the feasibility of the knowledge based approach to stampability evaluation.
基金funded by the Deanship of Scientific Research at Jouf University under Grant number DSR-2022-RG-0101。
文摘As legal cases grow in complexity and volume worldwide,integrating machine learning and artificial intelligence into judicial systems has become a pivotal research focus.This study introduces a comprehensive framework for verdict recommendation that synergizes rule-based methods with deep learning techniques specifically tailored to the legal domain.The proposed framework comprises three core modules:legal feature extraction,semantic similarity assessment,and verdict recommendation.For legal feature extraction,a rule-based approach leverages Black’s Law Dictionary and WordNet Synsets to construct feature vectors from judicial texts.Semantic similarity between cases is evaluated using a hybrid method that combines rule-based logic with an LSTM model,analyzing the feature vectors of query cases against a legal knowledge base.Verdicts are then recommended through a rule-based retrieval system,enhanced by predefined legal statutes and regulations.By merging rule-based methodologies with deep learning,this framework addresses the interpretability challenges often associated with contemporary AImodels,thereby enhancing both transparency and generalizability across diverse legal contexts.The system was rigorously tested using a legal corpus of 43,000 case laws across six categories:Criminal,Revenue,Service,Corporate,Constitutional,and Civil law,ensuring its adaptability across a wide range of judicial scenarios.Performance evaluation showed that the feature extraction module achieved an average accuracy of 91.6%with an F-Score of 95%.The semantic similarity module,tested using Manhattan,Euclidean,and Cosine distance metrics,achieved 88%accuracy and a 93%F-Score for short queries(Manhattan),89%accuracy and a 93.7%F-Score for medium-length queries(Euclidean),and 87%accuracy with a 92.5%F-Score for longer queries(Cosine).The verdict recommendation module outperformed existing methods,achieving 90%accuracy and a 93.75%F-Score.This study highlights the potential of hybrid AI frameworks to improve judicial decision-making and streamline legal processes,offering a robust,interpretable,and adaptable solution for the evolving demands of modern legal systems.
文摘In this paper, the knowledge based enterprise is considered as an organism, which possesses a set of capabilities. The organizational structure model of knowledge based enterprise organism is described in order to possess the essential capacity set. A dynamic capacity set is defined and analyzed based on the definition of the growth and development for knowledge based enterprise organism. The structure of the capacity base, a subset of the capacity set, is optimized for different periods of the organism ...
文摘Aim To analyse the influence of knowledge base on the performance of the fuzzy controller of the electrohydraulic position control system,and to determine their selection cri- teria. Methods Experiments based on different membership functions,scaling factors and con-trol rules were done separately.The experiment results and the influence of different know- ledge base on the control performance were analysed in theory so that criteria of selcting knowledge base can be summarized correctly.Results Knowledge base,including membershipfunctions, scaling factors and control rules,has a crucial effect on the fuzzy control system.Suitably selected knowledge base can lead to good control performance of fuzzy control sys-tem. Conclusion Being symmetric,having an intersection ratio of 1 and satisfying width con- dition are three necessities for selecting membership functions.Selecting scaling factors dependson both the system requirement and a comprehensive analysis in the overshoot,oscillation, rising time and stability. Integrity and continuity must be guaranteed when determining control rules.
基金Supported by the National Science Foundation China(61422303)National Key Technology R&D Program(2015BAF22B02)the Development Fund for Shanghai Talents
文摘Equipment selection for industrial process usually requires the extensive participation of industrial experts and technologists, which causes a serious waste of resources. This work presents an equipment selection knowledge base system for industrial styrene process(S-ESKBS) based on the ontology technology. This structure includes a low-level knowledge base and a top-level interactive application. As the core part of the S-ESKBS, the low-level knowledge base consists of the equipment selection ontology library, equipment selection rule set and Pellet inference engine. The top-level interactive application is implemented using S-ESKBS, including the parsing storage layer, inference query layer and client application layer. Case studies for the industrial styrene process equipment selection of an analytical column and an alkylation reactor are demonstrated to show the characteristics and implementability of the S-ESKBS.
文摘After analyzing the welding procedure knowledge in Chinese national standards for welding procedure qualification of steel pressure vessel from the point of establishing expert system, it can be divided into five types of knowledge, i. e. practice, definition, regularity, process and description knowledge. The knowledge expression methods are established according to the different type of welding procedure knowledge. The reasoning process based on rule is adopted. And the reasoning engine is embedded among objects integrated with the knowledge base.
文摘Setting up a knowledge base is a helpful way to optimize the operation of the polyethylene process by improving the performance and the ef ciency of reuse of information and knowledge two critical ele- ments in polyethylene smart manufacturing. In this paper, we propose an overall structure for a knowl- edge base based on practical customer demand and the mechanism of the polyethylene process. First, an ontology of the polyethylene process constructed using the seven-step method is introduced as a carrier for knowledge representation and sharing. Next, a prediction method is presented for the molecular weight distribution (MWD) based on a back propagation (BP) neural network model, by analyzing the relationships between the operating conditions and the parameters of the MWD. Based on this network, a differential evolution algorithm is introduced to optimize the operating conditions by tuning the MWD. Finally, utilizing a MySQL database and the Java programming language, a knowledge base system for the operation optimization of the polyethylene process based on a browser/server framework is realized.
基金The National Natural Science Foundation of China(No.61502095).
文摘Aiming at the relation linking task for question answering over knowledge base,especially the multi relation linking task for complex questions,a relation linking approach based on the multi-attention recurrent neural network(RNN)model is proposed,which works for both simple and complex questions.First,the vector representations of questions are learned by the bidirectional long short-term memory(Bi-LSTM)model at the word and character levels,and named entities in questions are labeled by the conditional random field(CRF)model.Candidate entities are generated based on a dictionary,the disambiguation of candidate entities is realized based on predefined rules,and named entities mentioned in questions are linked to entities in knowledge base.Next,questions are classified into simple or complex questions by the machine learning method.Starting from the identified entities,for simple questions,one-hop relations are collected in the knowledge base as candidate relations;for complex questions,two-hop relations are collected as candidates.Finally,the multi-attention Bi-LSTM model is used to encode questions and candidate relations,compare their similarity,and return the candidate relation with the highest similarity as the result of relation linking.It is worth noting that the Bi-LSTM model with one attentions is adopted for simple questions,and the Bi-LSTM model with two attentions is adopted for complex questions.The experimental results show that,based on the effective entity linking method,the Bi-LSTM model with the attention mechanism improves the relation linking effectiveness of both simple and complex questions,which outperforms the existing relation linking methods based on graph algorithm or linguistics understanding.
基金supported by the"Suqian Talent"Xiongying Program for Educational Innovation Talents Project(Grant No.SQXY202431)the National Key Research and Development Program of China(Grant No.2017YFD0700100).
文摘Currently,knowledge-based systems are generally updated manually,resulting in long cycles,low efficiency,and difficulty in ensuring comprehensive and systematic supplementary content.To address this issue,a knowledge-based system automatic updating method based on webpage information and user files is proposed for combine harvesters.The knowledge storage structure in an electronic warehouse is analyzed,and knowledge and data types are determined.A crawler designed to locate the combine harvester-related information in the target webpage realizes the acquisition and sorting of webpage knowledge and data.The type of file uploaded by the user is set based on the knowledge base and data type;the content of the user file is extracted and filtered,and the knowledge and data of the knowledge-based system are user-defined.The organized knowledge and data are stored or updated in the knowledge base to achieve automatic updating of the knowledge-based system based on webpage information and user files.The test results show that based on user file updates,the knowledge and data of the knowledge-based system can be customized according to user needs.This meets user requirements and allows for effective automatic updates based on webpages after automatic updating of the knowledge base based on webpages.After the automatic updating of the knowledge base based on webpage information is triggered,the knowledge and data from the three webpages that were initially crawled and read are automatically updated to the knowledge base in 5.265 s.Realizing the automatic updating of knowledge and data can shorten the updating period,maintain the effectiveness and practicability of the knowledge-based system,ensure the scientific and advanced nature of the intelligent design process,and provide technical models and methods for the knowledge collection of similar knowledge-based systems.
基金Supported by National Natural Science Foundation of China(No.70271002)
文摘Based on the knowledge representation and knowledge reasoning, this paper addresses the creation of the multi-attribute knowledge base on the basis of hybrid knowledge representation, with the help of object-oriented programming language and relational database. Compared with general knowledge base, multi-attribute knowledge base can enhance the ability of knowledge processing and application; integrate the heterogeneous knowledge, such as model, symbol, case-based sample knowledge; and support the whole decision process by integrated reasoning.
文摘The present work deals with the development of an Ontology-Based Knowledge Network of soil/water physicochemical & biological properties (soil/water concepts), derived from ASTM Standard Methods (ASTMi,n) and relevant scientific/applicable references (published papers—PPi,n) to fill up/bridge the gap of the information science between cited Standards and infiltration discipline conceptual vocabulary providing accordingly a dedicated/internal Knowledge Base (KB). This attempt constitutes an innovative approach, since it is based on externalizing domain knowledge in the form of Ontology-Based Knowledge Networks, incorporating standardized methodology in soil engineering. The ontology soil/water concepts (semantics) of the developed network correspond to soil/water physicochemical & biological properties, classified in seven different generations that are distinguished/located in infiltration/percolation process of contaminated water through soil porous media. The interconnections with arcs between corresponding concepts/properties among the consecutive generations are defined by the relationship of dependent and independent variables. All these interconnections are documented according to the below three ways: 1) dependent and independent variables interconnected by using the logical operator “<em>depends on</em>” quoting existent explicit functions and equations;2) dependent and independent variables interconnected by using the logical operator “<em>depends on</em>” quoting produced implicit functions, according to Rayleigh’s method of indices;3) dependent and independent variables interconnected by using the logical operator “<em>related to</em>” based on a logical dependence among the examined nodes-concepts-variables. The aforementioned approach provides significant advantages to semantic web developers and web users by means of prompt knowledge navigation, tracking, retrieval and usage.
