Accurate prediction of rockburst intensity levels is crucial for ensuring the safety of deep hard rock engineering construction.This paper introduced an expert system for rockburst intensity level prediction that empl...Accurate prediction of rockburst intensity levels is crucial for ensuring the safety of deep hard rock engineering construction.This paper introduced an expert system for rockburst intensity level prediction that employs machine learning algorithms as the basis for its inference rules.The system comprises four modules:a database,a repository,an inference engine,and an interpreter.A database containing 1114 rockburst cases was used to construct 357 datasets that serve as the repository for the expert system.Additionally,19 types of machine learning algorithms were used to establish 6783 micro-models to construct cognitive rules within the inference engine.By integrating probability theory and marginal analysis,a fuzzy scoring method based on the SoftMax function was developed and applied to the interpreter for rockburst intensity level prediction,effectively restoring the continuity of rockburst characteristics.The research results indicate that ensemble algorithms based on decision trees are more effective in capturing the characteristics of rockburst.Key factors for accurate prediction of rockburst intensity include uniaxial compressive strength,elastic energy index,the maximum principal stress,tangential stress,and their composite indicators.The accuracy of the proposed rockburst intensity level prediction expert system was verified using 20 engineering rockburst cases,with predictions aligning closely with the actual rockburst intensity levels.展开更多
A literature review on AI applications in the field of railway safety shows that the implemented approaches mainly concern the operational,maintenance,and feedback phases following railway incidents or accidents.These...A literature review on AI applications in the field of railway safety shows that the implemented approaches mainly concern the operational,maintenance,and feedback phases following railway incidents or accidents.These approaches exploit railway safety data once the transport system has received authorization for commissioning.However,railway standards and regulations require the development of a safety management system(SMS)from the specification and design phases of the railway system.This article proposes a new AI approach for analyzing and assessing safety from the specification and design phases of the railway system with a view to improving the development of the SMS.Unlike some learning methods,the proposed approach,which is dedicated in particular to safety assessment bodies,is based on semi-supervised learning carried out in close collaboration with safety experts who contributed to the development of a database of potential accident scenarios(learning example database)relating to the risk of rail collision.The proposed decision support is based on the use of an expert system whose knowledge base is automatically generated by inductive learning in the form of an association rule(rule base)and whose main objective is to suggest to the safety expert possible hazards not considered during the development of the SMS to complete the initial hazard register.展开更多
This paper proposes a deep learning-based 3D LiDAR perception framework designed for applications such as autonomous robots and vehicles.To address the high dependency on large-scale annotated data—an inherent limita...This paper proposes a deep learning-based 3D LiDAR perception framework designed for applications such as autonomous robots and vehicles.To address the high dependency on large-scale annotated data—an inherent limitation of deep learning models—this study introduces a hybrid perception architecture that incorporates expertdriven LiDAR processing techniques into the deep neural network.Traditional 3DLiDAR processingmethods typically remove ground planes and apply distance-or density-based clustering for object detection.In this work,such expert knowledge is encoded as feature-level inputs and fused with the deep network,therebymitigating the data dependency issue of conventional learning-based approaches.Specifically,the proposedmethod combines two expert algorithms—Patchwork++for ground segmentation and DBSCAN for clustering—with a PointPillars-based LiDAR detection network.We design four hybrid versions of the network depending on the stage and method of integrating expert features into the feature map of the deep model.Among these,Version 4 incorporates a modified neck structure in PointPillars and introduces a new Cluster 2D Pseudo-Map Branch that utilizes cluster-level pseudo-images generated from Patchwork++and DBSCAN.This version achieved a+3.88%improvement mean Average Precision(mAP)compared to the baseline PointPillars.The results demonstrate that embedding expert-based perception logic into deep neural architectures can effectively enhance performance and reduce dependency on extensive training datasets,offering a promising direction for robust 3D LiDAR object detection in real-world scenarios.展开更多
The 17 Sustainable Development Goals(SDGs)for 2030,adopted by all United Nations member states in 2015,are facing a range of challenges.Factors such as climate change,regional conflicts and economic recession are havi...The 17 Sustainable Development Goals(SDGs)for 2030,adopted by all United Nations member states in 2015,are facing a range of challenges.Factors such as climate change,regional conflicts and economic recession are having a significant impact,particularly on global poverty governance.As a platform for dialogue,exchange and technical cooperation,the 2025 International Seminar on Global Poverty Reduction Partnerships was held in Beijing on 10 December 2025.展开更多
According to the requirements of agricultural production and usem, taking diagnosis and decision-making of prevention for common diseases and pests in fruits and vegetables in southern China as the core, with communic...According to the requirements of agricultural production and usem, taking diagnosis and decision-making of prevention for common diseases and pests in fruits and vegetables in southern China as the core, with communication and sharing as principle, adopted diagnosis, inquiries and guiding prevention of diseases and pests in fruits and vegetables as purpose, expert examination system of plant disease and pests in fruits and vegetables based on Web highly integrates the knowledge and prevention techniques of common diseases and pests for main fruit and vegetable in south China. In this system, the users can browse and inquiry the information about the fruit and vegetable diseases and pests, as well as their diagnosis and control. The implementation of the system plays an active role in promo- ting plant protection knowledge and guiding farms to scientifically control diseases and pests in fruits and vegetables展开更多
In aluminum electrolytic process, the variables affect the current efficiency and the stability of electrolysis cells. AIF3 addition and aluminum tapping volume are two important factors that affect economic benefits ...In aluminum electrolytic process, the variables affect the current efficiency and the stability of electrolysis cells. AIF3 addition and aluminum tapping volume are two important factors that affect economic benefits of aluminum electrolytic production. Fuzzy logic provides a suitable mechanism to describe the relationship between the process variables and the current efficiency. Fuzzy expert system based on Mamdani fuzzy inference process for aluminum electrolysis was adopted to adjust A1F3 addition and aluminum tapping volume. A novel variable universe approach was applied in the system to solve the problem that different electrolysis cells have different universes of variables. The system was applied to 300 kA aluminum electrolysis cells in a aluminum plant. Experimental results showed that the electrolyte temperature was kept stably between 945 and 955℃, the current efficiency reached 93.5%, and the DC power consumption was 13 000 kW.h per ton aluminum.展开更多
The necessity and feasibility of an expert system for carbide-tool utilization are analyzed and a practical system named CUES(carbide-tool utilization expert system ) is developed and realized. The system concept, mod...The necessity and feasibility of an expert system for carbide-tool utilization are analyzed and a practical system named CUES(carbide-tool utilization expert system ) is developed and realized. The system concept, module structure, data management, inference strategy and the interface design of the system are discussed in.detail. The system would be useful not only for the preparation of tool bank of FMS or CIMS, but the for the proper application of cemented carbide tools in conventional machining Processes.展开更多
The inspection of engine lubricating oil can give an indication of the internal condition of an engine. By means of the Object-Oriented Programming (OOP), an expert system is developed in this paper to computerize the...The inspection of engine lubricating oil can give an indication of the internal condition of an engine. By means of the Object-Oriented Programming (OOP), an expert system is developed in this paper to computerize the inspection. The traditional components of an expert system, such us knowledge base, inference engine and user interface are reconstructed and integrated, based on the Microsoft Foundation Class (MFC) library. To testify the expert system, an inspection example is given at the end of this paper.展开更多
Expert systems (ESs) are being increasingly applied to the fault diagnosis of engines. Based on the idea of ES template (EST), an object-oriented rule-type EST is emphatically studied on such aspects as the object-ori...Expert systems (ESs) are being increasingly applied to the fault diagnosis of engines. Based on the idea of ES template (EST), an object-oriented rule-type EST is emphatically studied on such aspects as the object-oriented knowledge representation, the heuristic inference engine with an improved depth-first search (DFS) and the graphical user interface. A diagnositic ES instance for debris on magnetic chip detectors (MCDs) is then created with the EST. The spot running shows that the rule-type EST enhances the abilities of knowledge representation and heuristic inference, and breaks a new way for the rapid construction and implementation of ES.展开更多
This paper describes the development of an expert system(ES) on earth retaining structures for the selection and design.The ES retaining is an interactive menudriven system and consists of two main parts—the selectio...This paper describes the development of an expert system(ES) on earth retaining structures for the selection and design.The ES retaining is an interactive menudriven system and consists of two main parts—the selection part,selectwall and the design part.Selectwall is developed using the knowledge base and it makes a choice of the most appropriate retaining structure.The design part is developed by three independent subprograms which perform detailed design including strength,deformation,stability of the retaining structure.The calculation results are illustrated by plotting the diagram.Using this program,the design procedure of the retaining structure can be performed automatically.展开更多
Based on the characteristic peculiarities of mechanical design expert systems (MDES), the design process pf gear box and its components is introduced and the gear box design expert systems (GBES)is established. GBES e...Based on the characteristic peculiarities of mechanical design expert systems (MDES), the design process pf gear box and its components is introduced and the gear box design expert systems (GBES)is established. GBES employs the methods of knowledge representation to indicate the knowledge-unit-rule-process, table-vector-process. By taking the advantage of knowledge unit's indicator, it can make the units of knowledge base to to combine to form a whole in the feature of trees and nets so that it can give deduction conveniently. The knowledge base of GBES is organized in hierarchy, which provides the efficient managerial systems of knowledge base. It makes the knowledge base convenient greatly for establishing and using. The assistant modules of GBES are written in FORTRAN and the part of expert systems is written in LISP. It explains the I/O among each module and the forms of independent application. The GBES systems have been put into preliminary, use in practice.展开更多
With the acknowledgement of species, symptoms and control measures for diseases, pests and weeds in tumorous stem mustard, the expert prevention system has been studied and developed based on internct, and the system ...With the acknowledgement of species, symptoms and control measures for diseases, pests and weeds in tumorous stem mustard, the expert prevention system has been studied and developed based on internct, and the system mainly includes knowledge database, inference engine, browser web and so on. The knowledge database has been established by Micrsoft Access 2003 software; the procedure of inference engine has been compiled by JavaScript; the pages of browser web have been made by Dreamweaver MX software. The expert system is fuR-featured and user-friendly, which can provide control knowledge against the diseases, pests and weeds of tumorous stem mustard for the majority of farmers, scientific technological person and grass-roots level managers quickly and conveniently,展开更多
Aim To design and implement a multi-agent cooperative problem solving expert system tool. Methods A blackboard system was adopted in the system as a data sharing and information exchanging center, to coordinate the co...Aim To design and implement a multi-agent cooperative problem solving expert system tool. Methods A blackboard system was adopted in the system as a data sharing and information exchanging center, to coordinate the complex cooperative problem solving. The system was developed in UNIX and MSWindows 95 mixed TCP/IP network environment. Results and Conclusion A prototype system of a multi-agent cooperative expert systems tool is implemented.The experiment demonstrates that the fundamental functions of a cooperative expert systems is realized.展开更多
In this paper a PC fault diagnostic expert system (PCDGES) is introduced, which can be run under CCDOS and encoded by English Prolog and C. In the system, a method of combining logic with production rules is applied ...In this paper a PC fault diagnostic expert system (PCDGES) is introduced, which can be run under CCDOS and encoded by English Prolog and C. In the system, a method of combining logic with production rules is applied to represent knowledge. The expert system program is separated from knowledge base. Inference computation is mainly carried backward, and the forward is regarded as an auxiliary inference. The knowledge base can be easily updated, deleted and added in operation time. It has a supporting machanism for the acquisition of knowledge and by means of “telling method”, knowledge can be acquisited. The system also has “why” explanation function and an interface with DOS, full screen editor, and hardware dignostic program. For Chinese users, all the prompt information and selection menus are displayed in color Chinese.展开更多
Based on ASP.NET,a orange fruit tree fertilizer expert system software was developed.The system could simulate and decide an annual fertilization plan for young and mature trees in terms of geographical position and c...Based on ASP.NET,a orange fruit tree fertilizer expert system software was developed.The system could simulate and decide an annual fertilization plan for young and mature trees in terms of geographical position and climate.This paper introduced the design conditions,framework,production,and deployment of the system.It exhibited characters of orange specialty and was a typical online agriculture expert system.The use of the system for orange fruit management could decrease production cost,guarantee orange quality and improve economical benefit at the same time.Farmer using the system saved N input by 41-238 g/plant,P2O5 input 3-24 g/plant,and K2O input 1-36 g/plant,and got higher yield by 6-17 kg/plant.展开更多
Based on the fuzzy expert system fault diagnosis theory, the knowledge base architecture and inference engine algorithm are put forward for avionic device fault diagnosis. The knowledge base is constructed by fault qu...Based on the fuzzy expert system fault diagnosis theory, the knowledge base architecture and inference engine algorithm are put forward for avionic device fault diagnosis. The knowledge base is constructed by fault query network, of which the basic ele- ment is the test-diagnosis fault unit. Every underlying fault cause＇s membership degree is calculated using fuzzy product inference algorithm, and the fault answer best selection algorithm is developed, to which the deep knowledge is applied. Using some examples the proposed algorithm is analyzed for its capability of synthesis diagnosis and its improvement compared to greater membership degree first principle.展开更多
In order to study intelligent fault diagnosis methods based on fuzzy neural network (NN) expert system and build up intelligent fault diagnosis for a type of missile weapon system, the concrete implementation of a fuz...In order to study intelligent fault diagnosis methods based on fuzzy neural network (NN) expert system and build up intelligent fault diagnosis for a type of missile weapon system, the concrete implementation of a fuzzy NN fault diagnosis expert system is given in this paper. Based on thorough research of knowledge presentation, the intelligent fault diagnosis system is implemented with artificial intelligence for a large-scale missile weapon equipment. The method is an effective way to perform fuzzy fault diagnosis. Moreover, it provides a new way of the fault diagnosis for large-scale missile weapon equipment.展开更多
This paper is devoted to develop an expert system to manage the fault isolation and maintenance knowledge of the engine indication and crew alerting system (EICAS). The object oriented programming (OOP) technique and...This paper is devoted to develop an expert system to manage the fault isolation and maintenance knowledge of the engine indication and crew alerting system (EICAS). The object oriented programming (OOP) technique and the microsoft foundation class (MFC) are applied to set up a frame decision tree (FDT) which incorporates the expert system′s knowledge base, inference engine and user interface. Once a fault symptom indicated by the EICAS is input, by inferring step by step, the expert system can locate it in the engine and provide some homologous constructive maintenance advice.展开更多
Rotary kiln process for iron ore oxide pellet production is hard to detect and control.Construction of one-dimensional model of temperature field in rotary kiln was described.And the results lay a solid foundation for...Rotary kiln process for iron ore oxide pellet production is hard to detect and control.Construction of one-dimensional model of temperature field in rotary kiln was described.And the results lay a solid foundation for online control.Establishment of kiln process control expert system was presented,with maximum temperature of pellet and gas temperature at the feed end as control cores,and interval estimate as control strategy.Software was developed and put into application in a pellet plant.The results show that control guidance of this system is accurate and effective.After production application for nearly one year,the compressive strength and first grade rate of pellet are increased by 86 N and 2.54%,respectively,while FeO content is 0.05% lowered.This system can reveal detailed information of real time kiln process,and provide a powerful tool for online control of pellet production.展开更多
基金Project(42077244)supported by the National Natural Science Foundation of ChinaProject(2020-05)supported by the Open Research Fund of Guangdong Provincial Key Laboratory of Deep Earth Sciences and Geothermal Energy Exploitation and Utilization,China。
文摘Accurate prediction of rockburst intensity levels is crucial for ensuring the safety of deep hard rock engineering construction.This paper introduced an expert system for rockburst intensity level prediction that employs machine learning algorithms as the basis for its inference rules.The system comprises four modules:a database,a repository,an inference engine,and an interpreter.A database containing 1114 rockburst cases was used to construct 357 datasets that serve as the repository for the expert system.Additionally,19 types of machine learning algorithms were used to establish 6783 micro-models to construct cognitive rules within the inference engine.By integrating probability theory and marginal analysis,a fuzzy scoring method based on the SoftMax function was developed and applied to the interpreter for rockburst intensity level prediction,effectively restoring the continuity of rockburst characteristics.The research results indicate that ensemble algorithms based on decision trees are more effective in capturing the characteristics of rockburst.Key factors for accurate prediction of rockburst intensity include uniaxial compressive strength,elastic energy index,the maximum principal stress,tangential stress,and their composite indicators.The accuracy of the proposed rockburst intensity level prediction expert system was verified using 20 engineering rockburst cases,with predictions aligning closely with the actual rockburst intensity levels.
文摘A literature review on AI applications in the field of railway safety shows that the implemented approaches mainly concern the operational,maintenance,and feedback phases following railway incidents or accidents.These approaches exploit railway safety data once the transport system has received authorization for commissioning.However,railway standards and regulations require the development of a safety management system(SMS)from the specification and design phases of the railway system.This article proposes a new AI approach for analyzing and assessing safety from the specification and design phases of the railway system with a view to improving the development of the SMS.Unlike some learning methods,the proposed approach,which is dedicated in particular to safety assessment bodies,is based on semi-supervised learning carried out in close collaboration with safety experts who contributed to the development of a database of potential accident scenarios(learning example database)relating to the risk of rail collision.The proposed decision support is based on the use of an expert system whose knowledge base is automatically generated by inductive learning in the form of an association rule(rule base)and whose main objective is to suggest to the safety expert possible hazards not considered during the development of the SMS to complete the initial hazard register.
基金supported by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(RS-2023-00245084)by Korea Institute for Advancement of Technology(KIAT)grant funded by the Korea Government(MOTIE)(RS-2024-00415938,HRD Program for Industrial Innovation)and Soonchunhyang University.
文摘This paper proposes a deep learning-based 3D LiDAR perception framework designed for applications such as autonomous robots and vehicles.To address the high dependency on large-scale annotated data—an inherent limitation of deep learning models—this study introduces a hybrid perception architecture that incorporates expertdriven LiDAR processing techniques into the deep neural network.Traditional 3DLiDAR processingmethods typically remove ground planes and apply distance-or density-based clustering for object detection.In this work,such expert knowledge is encoded as feature-level inputs and fused with the deep network,therebymitigating the data dependency issue of conventional learning-based approaches.Specifically,the proposedmethod combines two expert algorithms—Patchwork++for ground segmentation and DBSCAN for clustering—with a PointPillars-based LiDAR detection network.We design four hybrid versions of the network depending on the stage and method of integrating expert features into the feature map of the deep model.Among these,Version 4 incorporates a modified neck structure in PointPillars and introduces a new Cluster 2D Pseudo-Map Branch that utilizes cluster-level pseudo-images generated from Patchwork++and DBSCAN.This version achieved a+3.88%improvement mean Average Precision(mAP)compared to the baseline PointPillars.The results demonstrate that embedding expert-based perception logic into deep neural architectures can effectively enhance performance and reduce dependency on extensive training datasets,offering a promising direction for robust 3D LiDAR object detection in real-world scenarios.
文摘The 17 Sustainable Development Goals(SDGs)for 2030,adopted by all United Nations member states in 2015,are facing a range of challenges.Factors such as climate change,regional conflicts and economic recession are having a significant impact,particularly on global poverty governance.As a platform for dialogue,exchange and technical cooperation,the 2025 International Seminar on Global Poverty Reduction Partnerships was held in Beijing on 10 December 2025.
基金Supported by Science and Technology Project of Guangdong Province(2007A020300002-12)~~
文摘According to the requirements of agricultural production and usem, taking diagnosis and decision-making of prevention for common diseases and pests in fruits and vegetables in southern China as the core, with communication and sharing as principle, adopted diagnosis, inquiries and guiding prevention of diseases and pests in fruits and vegetables as purpose, expert examination system of plant disease and pests in fruits and vegetables based on Web highly integrates the knowledge and prevention techniques of common diseases and pests for main fruit and vegetable in south China. In this system, the users can browse and inquiry the information about the fruit and vegetable diseases and pests, as well as their diagnosis and control. The implementation of the system plays an active role in promo- ting plant protection knowledge and guiding farms to scientifically control diseases and pests in fruits and vegetables
基金Project (2009BAE85B00) supported by the National Key Technology R&D Program of ChinaProject (PHR20100509) supported by Funding Project for Academic Human Resources Development in Institutions of Higher Learning under the Jurisdiction of Beijing Municipality, China
文摘In aluminum electrolytic process, the variables affect the current efficiency and the stability of electrolysis cells. AIF3 addition and aluminum tapping volume are two important factors that affect economic benefits of aluminum electrolytic production. Fuzzy logic provides a suitable mechanism to describe the relationship between the process variables and the current efficiency. Fuzzy expert system based on Mamdani fuzzy inference process for aluminum electrolysis was adopted to adjust A1F3 addition and aluminum tapping volume. A novel variable universe approach was applied in the system to solve the problem that different electrolysis cells have different universes of variables. The system was applied to 300 kA aluminum electrolysis cells in a aluminum plant. Experimental results showed that the electrolyte temperature was kept stably between 945 and 955℃, the current efficiency reached 93.5%, and the DC power consumption was 13 000 kW.h per ton aluminum.
文摘The necessity and feasibility of an expert system for carbide-tool utilization are analyzed and a practical system named CUES(carbide-tool utilization expert system ) is developed and realized. The system concept, module structure, data management, inference strategy and the interface design of the system are discussed in.detail. The system would be useful not only for the preparation of tool bank of FMS or CIMS, but the for the proper application of cemented carbide tools in conventional machining Processes.
文摘The inspection of engine lubricating oil can give an indication of the internal condition of an engine. By means of the Object-Oriented Programming (OOP), an expert system is developed in this paper to computerize the inspection. The traditional components of an expert system, such us knowledge base, inference engine and user interface are reconstructed and integrated, based on the Microsoft Foundation Class (MFC) library. To testify the expert system, an inspection example is given at the end of this paper.
文摘Expert systems (ESs) are being increasingly applied to the fault diagnosis of engines. Based on the idea of ES template (EST), an object-oriented rule-type EST is emphatically studied on such aspects as the object-oriented knowledge representation, the heuristic inference engine with an improved depth-first search (DFS) and the graphical user interface. A diagnositic ES instance for debris on magnetic chip detectors (MCDs) is then created with the EST. The spot running shows that the rule-type EST enhances the abilities of knowledge representation and heuristic inference, and breaks a new way for the rapid construction and implementation of ES.
文摘This paper describes the development of an expert system(ES) on earth retaining structures for the selection and design.The ES retaining is an interactive menudriven system and consists of two main parts—the selection part,selectwall and the design part.Selectwall is developed using the knowledge base and it makes a choice of the most appropriate retaining structure.The design part is developed by three independent subprograms which perform detailed design including strength,deformation,stability of the retaining structure.The calculation results are illustrated by plotting the diagram.Using this program,the design procedure of the retaining structure can be performed automatically.
文摘Based on the characteristic peculiarities of mechanical design expert systems (MDES), the design process pf gear box and its components is introduced and the gear box design expert systems (GBES)is established. GBES employs the methods of knowledge representation to indicate the knowledge-unit-rule-process, table-vector-process. By taking the advantage of knowledge unit's indicator, it can make the units of knowledge base to to combine to form a whole in the feature of trees and nets so that it can give deduction conveniently. The knowledge base of GBES is organized in hierarchy, which provides the efficient managerial systems of knowledge base. It makes the knowledge base convenient greatly for establishing and using. The assistant modules of GBES are written in FORTRAN and the part of expert systems is written in LISP. It explains the I/O among each module and the forms of independent application. The GBES systems have been put into preliminary, use in practice.
基金Supported by Yangtze Normal University Research Projects of Young Teachers(09JKY071)~~
文摘With the acknowledgement of species, symptoms and control measures for diseases, pests and weeds in tumorous stem mustard, the expert prevention system has been studied and developed based on internct, and the system mainly includes knowledge database, inference engine, browser web and so on. The knowledge database has been established by Micrsoft Access 2003 software; the procedure of inference engine has been compiled by JavaScript; the pages of browser web have been made by Dreamweaver MX software. The expert system is fuR-featured and user-friendly, which can provide control knowledge against the diseases, pests and weeds of tumorous stem mustard for the majority of farmers, scientific technological person and grass-roots level managers quickly and conveniently,
文摘Aim To design and implement a multi-agent cooperative problem solving expert system tool. Methods A blackboard system was adopted in the system as a data sharing and information exchanging center, to coordinate the complex cooperative problem solving. The system was developed in UNIX and MSWindows 95 mixed TCP/IP network environment. Results and Conclusion A prototype system of a multi-agent cooperative expert systems tool is implemented.The experiment demonstrates that the fundamental functions of a cooperative expert systems is realized.
文摘In this paper a PC fault diagnostic expert system (PCDGES) is introduced, which can be run under CCDOS and encoded by English Prolog and C. In the system, a method of combining logic with production rules is applied to represent knowledge. The expert system program is separated from knowledge base. Inference computation is mainly carried backward, and the forward is regarded as an auxiliary inference. The knowledge base can be easily updated, deleted and added in operation time. It has a supporting machanism for the acquisition of knowledge and by means of “telling method”, knowledge can be acquisited. The system also has “why” explanation function and an interface with DOS, full screen editor, and hardware dignostic program. For Chinese users, all the prompt information and selection menus are displayed in color Chinese.
基金fund by the Major Science and Technology Program (2009ZX07102-004),Chinathe IPNI (International Plant Nutrition Institute) Program,Canada (2009ZX07102-004)
文摘Based on ASP.NET,a orange fruit tree fertilizer expert system software was developed.The system could simulate and decide an annual fertilization plan for young and mature trees in terms of geographical position and climate.This paper introduced the design conditions,framework,production,and deployment of the system.It exhibited characters of orange specialty and was a typical online agriculture expert system.The use of the system for orange fruit management could decrease production cost,guarantee orange quality and improve economical benefit at the same time.Farmer using the system saved N input by 41-238 g/plant,P2O5 input 3-24 g/plant,and K2O input 1-36 g/plant,and got higher yield by 6-17 kg/plant.
基金The 11th Five-year National Defense Preliminary Research Projects (B0520060455)
文摘Based on the fuzzy expert system fault diagnosis theory, the knowledge base architecture and inference engine algorithm are put forward for avionic device fault diagnosis. The knowledge base is constructed by fault query network, of which the basic ele- ment is the test-diagnosis fault unit. Every underlying fault cause＇s membership degree is calculated using fuzzy product inference algorithm, and the fault answer best selection algorithm is developed, to which the deep knowledge is applied. Using some examples the proposed algorithm is analyzed for its capability of synthesis diagnosis and its improvement compared to greater membership degree first principle.
文摘In order to study intelligent fault diagnosis methods based on fuzzy neural network (NN) expert system and build up intelligent fault diagnosis for a type of missile weapon system, the concrete implementation of a fuzzy NN fault diagnosis expert system is given in this paper. Based on thorough research of knowledge presentation, the intelligent fault diagnosis system is implemented with artificial intelligence for a large-scale missile weapon equipment. The method is an effective way to perform fuzzy fault diagnosis. Moreover, it provides a new way of the fault diagnosis for large-scale missile weapon equipment.
文摘This paper is devoted to develop an expert system to manage the fault isolation and maintenance knowledge of the engine indication and crew alerting system (EICAS). The object oriented programming (OOP) technique and the microsoft foundation class (MFC) are applied to set up a frame decision tree (FDT) which incorporates the expert system′s knowledge base, inference engine and user interface. Once a fault symptom indicated by the EICAS is input, by inferring step by step, the expert system can locate it in the engine and provide some homologous constructive maintenance advice.
基金Project(NCET-05-0630) supported by Program for New Century Excellent Talents in University of China
文摘Rotary kiln process for iron ore oxide pellet production is hard to detect and control.Construction of one-dimensional model of temperature field in rotary kiln was described.And the results lay a solid foundation for online control.Establishment of kiln process control expert system was presented,with maximum temperature of pellet and gas temperature at the feed end as control cores,and interval estimate as control strategy.Software was developed and put into application in a pellet plant.The results show that control guidance of this system is accurate and effective.After production application for nearly one year,the compressive strength and first grade rate of pellet are increased by 86 N and 2.54%,respectively,while FeO content is 0.05% lowered.This system can reveal detailed information of real time kiln process,and provide a powerful tool for online control of pellet production.
