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.

Design and Development of Web-based Expert System for the Diagnosis of Disease and Pests of Fruits and Vegetables

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

Variable universe fuzzy expert system for aluminum electrolysis

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.

An Analysis of the Structure of Carbide-tool Utilization Expert System

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.

OBJECT-ORIENTED IMPLEMENTATION OF EXPERT SYSTEMS FOR ENGINE LUBRICATING OIL INSPECTION

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.

REALIZATION OF OBJECT-ORIENTED RULE-TYPE EXPERT SYSTEM TEMPLATE

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.

Expert System for the Design of Single Speed Gear Boxes

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.

A Blackboard-Based Multi-Agent Cooperative Expert System Tool

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.

Expert System for Statistical Prediction of Mineral Deposits on Middle and Large Scales

The expert system for statistical prediction of mineral deposits on middle and large scales takes the system of scientific exploration theories, criteria and methods proposed by Professor Zhao Pengda as the field expert knowledge. At present the developed system focuses on two aspects: synthetic exploration and quantitative exploration. Among the three basic theories for the prediction of deposits, it highlights the applications of seeking anomaly theory. This system is characteristic in the determination of geological background, the study of geological anomalies and the delineation of geological background, the study of geological anomalies and the delineation of mineralization anomalies. The system combines closely the knowledge base, method base and database .integrates the input and output information of multi - sources and mul-ti - variables , data , graphs and imagine processing system and inquiring system as a whole . So the system can meet in general all kinds of demands in statistical prediction of mineral deposits . Since the statistical prediction of mineral resources is a kind of systematic engineering pro ject , a further study should be carried out on the fields of theoretical exploration and ster eo - exploration on the basis of unceasingly perfecting the above-mentioned fields in order to establish a comprehensive intelligent system for scientific exploration , to provide new methods , new techniques and new ideas for fast prospecting appraisal of mineral resources .

STUDY OF REAL-TIME EXPERT SYSTEM TOOL FOR INDUSTRIAL FAULT MONITORING AND DIAGNOSIS

From the requirements of industrial production,an integrated fault monitoring,diagnosis and repairing system is suggested in this paper. This new scheme of fault monitoring and diagnosis system is realized by a master-slave real-time expert system,and a real-time expert system tool for this system is also developed accordingly. As an example of application of this tool ,a realtime expert system for fault monitoring and diagnosis on DC mine hoist is developed. Experiments show that this tool possesses better supporting environment, strong knowledge acquisition ability, and convenience for use. The system developed by this tool not only meets the real-time requirement of DC hoist,but also can give correct diagnosis results.

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.

A FAULT ISOLATION EXPERT SYSTEM FOR ENGINE INDICATION AND CREW ALERTING SYSTEM

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.

Mathematical models and expert system for grate-kiln process of iron ore oxide pellet production.Part Ⅱ:Rotary kiln process control

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.

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.

AN EXPERT SYSTEM ON ASSESSING ROCKBURST RISKS FOR SOUTH AFRICAN DEEP GOLD MINES

Expert systems are methods that can cope with rock engineer’s expertise effectively.An expert system on assessing rockburst risks for South African deep gold mines is described.Expertise was represented by rules, frames and mathematical models integratively. About 950 rules was built in the knowledge base, which can be learned by the suggested learning algorithm. A new uncertain reasoning algorithm was proposed. According to the features such as depth below surface, energy release rate (ERR), excess shear stress (ESS), geological structure, face angle with structure, distance from structure, extent of mining, mining type, width of bracket pillar, stope width, local support, regional support and gully support, rockburst risk is assessed either "Low", "Moderate", "High" or "Severe". A computer program system was developed by Turbo Prolog. The results of testing cases show its applicability of the system.

A New Fire Detection Method Using a Multi-Expert System Based on Color Dispersion, Similarity and Centroid Motion in Indoor Environment

In this paper, a video fire detection method is proposed, which demonstrated good performance in indoor environment. Three main novel ideas have been introduced. Firstly, a flame color model in RGB and HIS color space is used to extract pre-detected regions instead of traditional motion differential method, as it’s more suitable for fire detection in indoor environment. Secondly, according to the flicker characteristic of the flame, similarity and two main values of centroid motion are proposed. At the same time, a simple but effective method for tracking the same regions in consecutive frames is established. Thirdly,a multi-expert system consisting of color component dispersion,similarity and centroid motion is established to identify flames.The proposed method has been tested on a very large dataset of fire videos acquired both in real indoor environment tests and from the Internet. The experimental results show that the proposed approach achieved a balance between the false positive rate and the false negative rate, and demonstrated a better performance in terms of overall accuracy and F standard with respect to other similar fire detection methods in indoor environment.

Tuning PID Parameters Based on a Combination of the Expert System and the Improved Genetic Algorithms

a new strategy combining an expert system and improved genetic algorithms is presented for tuning proportional-integral-derivative （PID） parameters for petrochemical processes. This retains the advantages of genetic algorithms, namely rapid convergence and attainment of the global optimum. Utilization of an orthogonal experiment method solves the determination of the genetic factors. Combination with an expert system can make best use of the actual experience of the plant operators. Simulation results of typical process systems examples show a good control performance and robustness.