MOLTEN SALT PHASE DIAGRAMS CALCULATION USING ARTIFICIAL NEURAL NETWORK OR PATTERN RECOGNITION-BOND PARAMETERS PART 3.ESTIMATION OF LIQUIDUS TEMPERATURE AND EXPERT SYSTEM

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Construction of the Inference Engine of Blast Furnace Expert System

The expert system for judging blast furnace condition is built to realize automatic judgment of blast furnace conditions and standardization of blast furnace operation. This paper discusses the design and implementation of the inference engine of blast furnace expert system. The satisfactory simulation results have been obtained.

EXPERT SYSTEM FOR CONTROLLING THE STATE OF SINTERING PROCESS

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Computer Aided Process Planning Expert System for Die Forging

ＣｏｍｐｕｔｅｒＡｉｄｅｄＰｒｏｃｅｓＰｌａｎｎｉｎｇＥｘｐｅｒｔＳｙｓｔｅｍｆｏｒＤｉｅＦｏｒｇｉｎｇＬＩＸｉａｏｌｅｉ（李晓蕾）ＷＡＮＧＺｈｅｎ（王真）ＬＵＹａｎ（吕炎）ＷＡＮＧＨａｏ（王昊）（Ｄｅｐｔ．ｏｆＭａｔｅｒｉａｌＥｎｇｉｎｅｅｒｉｎｇ...

An Approach of Developing Expert System in Support of Database Management System

A method of how to describe expert system using relative data model and the realization of inference using data search in support of database management system is introduced in this article.Thereby,the database system is promoted from data processing up to knowledge processing,and a practical method of how to develop expert system using the popular database developing tools is proposed.

The Implementation of Fault Diagnostic Expert System for Personal Computer

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.

FAULT DIAGNOSIS EXPERT SYSTEM FOR ROTATING MACHINERY BASED ON A FUZZY PROBABILITY LOGIC INFERENCE MODEL

A new theory- the fuzzy probability logic theory is presented , This theory incorpo- rates the genterally-used fuzzy logic and the traditionally-used probability logic theory in attempt to emulate the rational fault diagnosis under uncertainty. According to the theory , an inference model , named as FSL , is thus designed to be devoted to the building of a fault diagnosis expert system for rotating machinery (ROSLES) . The system is put into operation on a vibration simula- tor stand for 300 MW turbine generator set ( 1 : 1 0) and satisfactory results are gained.

Prediction System for Diagnosis and Detection of Coronavirus Disease-2019(COVID-19):A Fuzzy-Soft Expert System

In early December 2019,a new virus named“2019 novel coronavirus(2019-nCoV)”appeared in Wuhan,China.The disease quickly spread worldwide,resulting in the COVID-19 pandemic.In the currentwork,we will propose a novel fuzzy softmodal(i.e.,fuzzy-soft expert system)for early detection of COVID-19.Themain construction of the fuzzy-soft expert systemconsists of five portions.The exploratory study includes sixty patients(i.e.,fortymales and twenty females)with symptoms similar to COVID-19 in(Nanjing Chest Hospital,Department of Respiratory,China).The proposed fuzzy-soft expert systemdepended on five symptoms of COVID-19(i.e.,shortness of breath,sore throat,cough,fever,and age).We will use the algorithm proposed by Kong et al.to detect these patients who may suffer from COVID-19.In this way,the present system is beneficial to help the physician decide if there is any patient who has COVID-19 or not.Finally,we present the comparison between the present system and the fuzzy expert system.

Expert Experience and Data-Driven Based Hybrid Fault Diagnosis for High-SpeedWire Rod Finishing Mills

The reliable operation of high-speed wire rod finishing mills is crucial in the steel production enterprise.As complex system-level equipment,it is difficult for high-speed wire rod finishing mills to realize fault location and real-time monitoring.To solve the above problems,an expert experience and data-driven-based hybrid fault diagnosis method for high-speed wire rod finishing mills is proposed in this paper.First,based on its mechanical structure,time and frequency domain analysis are improved in fault feature extraction.The approach of combining virtual value,peak value with kurtosis value index,is adopted in time domain analysis.Speed adjustment and side frequency analysis are proposed in frequency domain analysis to obtain accurate component characteristic frequency and its corresponding sideband.Then,according to time and frequency domain characteristics,fault location based on expert experience is proposed to get an accurate fault result.Finally,the proposed method is implemented in the equipment intelligent diagnosis system.By taking an equipment fault on site,for example,the effectiveness of the proposed method is illustrated in the system.

Expert consensus on irrigation and intracanal medication in root canal therapy

Chemical cleaning and disinfection are crucial steps for eliminating infection in root canal treatment. However, irrigant selection or irrigation procedures are far from clear. The vapor lock effect in the apical region has yet to be solved, impeding irrigation efficacy and resulting in residual infections and compromised treatment outcomes.

Fully Completed Spherical Fuzzy Approach-Based Z Numbers(PHIModel)for Enhanced Group Expert Consensus

This study aims to establish an expert consensus and enhance the efficacy of decision-making processes by integrating Spherical Fuzzy Sets(SFSs)and Z-Numbers(SFZs).A novel group expert consensus technique,the PHImodel,is developed to address the inherent limitations of both SFSs and the traditional Delphi technique,particularly in uncertain,complex scenarios.In such contexts,the accuracy of expert knowledge and the confidence in their judgments are pivotal considerations.This study provides the fundamental operational principles and aggregation operators associated with SFSs and Z-numbers,encompassing weighted geometric and arithmetic operators alongside fully developed operators tailored for SFZs numbers.Subsequently,a case study and comparative analysis are conducted to illustrate the practicality and effectiveness of the proposed operators and methodologies.Integrating the PHI model with SFZs numbers represents a significant advancement in decision-making frameworks reliant on expert input.Further,this combination serves as a comprehensive tool for decision-makers,enabling them to achieve heightened levels of consensus while concurrently assessing the reliability of expert contributions.The case study results demonstrate the PHI model’s utility in resolving complex decision-making scenarios,showcasing its ability to improve consensus-building processes and enhance decision outcomes.Additionally,the comparative analysis highlights the superiority of the integrated approach over traditional methodologies,underscoring its potential to revolutionize decision-making practices in uncertain environments.

UAV maneuvering decision-making algorithm based on deep reinforcement learning under the guidance of expert experience

Autonomous umanned aerial vehicle(UAV) manipulation is necessary for the defense department to execute tactical missions given by commanders in the future unmanned battlefield. A large amount of research has been devoted to improving the autonomous decision-making ability of UAV in an interactive environment, where finding the optimal maneuvering decisionmaking policy became one of the key issues for enabling the intelligence of UAV. In this paper, we propose a maneuvering decision-making algorithm for autonomous air-delivery based on deep reinforcement learning under the guidance of expert experience. Specifically, we refine the guidance towards area and guidance towards specific point tasks for the air-delivery process based on the traditional air-to-surface fire control methods.Moreover, we construct the UAV maneuvering decision-making model based on Markov decision processes(MDPs). Specifically, we present a reward shaping method for the guidance towards area and guidance towards specific point tasks using potential-based function and expert-guided advice. The proposed algorithm could accelerate the convergence of the maneuvering decision-making policy and increase the stability of the policy in terms of the output during the later stage of training process. The effectiveness of the proposed maneuvering decision-making policy is illustrated by the curves of training parameters and extensive experimental results for testing the trained policy.

Practice and Thinking of Agricultural Science and Technology Experts Serving the Grassroots to Promote Rural Revitalization

Provincial agricultural research institutes are local agricultural research institutions.They are familiar with local agricultural and ru-ral conditions,and have advantages in scientific and technological achievements,technical reserves and the construction of scientific and tech-nological talent support systems.In the process of promoting the implementation of the rural revitalization strategy,all the responsibilities and obligations of the agricultural research institute are to identify the focus of scientific and technological support and talent support in rural revital-ization,and break the bottleneck and constraints of rural revitalization.By sorting out the current situation of agricultural science and technolo-gy experts serving the grassroots in the problem of talent support for rural revitalization,this paper analyzed the existing problems and put for-ward countermeasures and recommendations.

British Law Expert:South China Sea Islands Are Chinese Territory

The History and Sovereignty of the South China Sea Islands clarifies the sovereignty over the South China Sea Islands with irrefutable facts.THE English edition of The History and Sovereignty of the South China Sea Islands was released by New Star Press under China International Communications Group at the 2024 Beijing International Book Fair on June 20.Prior to this,the Chinese version of the book,also published by New Star Press,had attracted wide attention from the international community.

A Health State Prediction Model Based on Belief Rule Base and LSTM for Complex Systems

In industrial production and engineering operations,the health state of complex systems is critical,and predicting it can ensure normal operation.Complex systems have many monitoring indicators,complex coupling structures,non-linear and time-varying characteristics,so it is a challenge to establish a reliable prediction model.The belief rule base(BRB)can fuse observed data and expert knowledge to establish a nonlinear relationship between input and output and has well modeling capabilities.Since each indicator of the complex system can reflect the health state to some extent,the BRB is built based on the causal relationship between system indicators and the health state to achieve the prediction.A health state prediction model based on BRB and long short term memory for complex systems is proposed in this paper.Firstly,the LSTMis introduced to predict the trend of the indicators in the system.Secondly,the Density Peak Clustering(DPC)algorithmis used todetermine referential values of indicators for BRB,which effectively offset the lack of expert knowledge.Then,the predicted values and expert knowledge are fused to construct BRB to predict the health state of the systems by inference.Finally,the effectiveness of the model is verified by a case study of a certain vehicle hydraulic pump.

Development of a Non-Pollution Orange Fruit Expert System Software Based on ASP.NET

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.

Research on the Algorithm of Avionic Device Fault Diagnosis Based on Fuzzy Expert System

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.

Study on Missile Intelligent Fault Diagnosis System Based on Fuzzy NN Expert System

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.

Application of Improved Genetic Algorithm in Network Fault Diagnosis Expert System

Knowledge acquisition is the “bottleneck” of building an expert system. Based on the optimization model, an improved genetic algorithm applied to knowledge acquisition of a network fault diagnostic expert system is proposed. The algorithm applies operators such as selection, crossover and mutation to evolve an initial population of diagnostic rules. Especially, a self adaptive method is put forward to regulate the crossover rate and mutation rate. In the end, a knowledge acquisition problem of a simple network fault diagnostic system is simulated, the results of simulation show that the improved approach can solve the problem of convergence better.

An Image-Based Diagnostic Expert System for Corn Diseases

The annual worldwide yield losses due to pests are estimated to be billions of dollars. Integrated pest management （IPM） is one of the most important components of crop production in most agricultural areas of the world, and the effectiveness of crop protection depends on accurate and timely diagnosis of phytosanitary problems. Accurately identifying and treatment depends on the method which used in disease and insect pests diagnosis. Identifying plant diseases is usually difficult and requires a plant pathologist or well-trained technician to accurately describe the case. Moreover, quite a few diseases have similar symptoms making it difficult for non-experts to distinguish disease correctly. Another method of diagnosis depends on comparison of the concerned case with similar ones through one image or more of the symptoms and helps enormously in overcoming difficulties of non-experts. The old adage ＇a picture is worth a thousand words＇ is crucially relevant. Considering the user＇s capability to deal and interact with the expert system easily and clearly, a webbased diagnostic expert-system shell based on production rules （i.e., IF 〈 effects 〉 THEN 〈 causes 〉） and frames with a color image database was developed and applied to corn disease diagnosis as a case study. The expert-system shell was made on a 32-bit multimedia desktop microcomputer. The knowledge base had frames, production rules and synonym words as the result of interview and arrangement. It was desired that 80% of total frames used visual color image data to explain the meaning of observations and conclusions. Visual color image displays with the phrases of questions and answers from the expert system, enables users to identify any disease, makes the right decision, and chooses the right treatment. This may increase their level of understanding of corn disease diagnosis. The expert system can be applied to diagnosis of other plant pests or diseases by easy changes to the knowledge base.