Components of Expert Systems within the Company

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Information systems are always developing and improving in a profitable way business and everyday applications. The word expert system, or commonly called an expert system, is one of the most successful trends today.

In fact, the main purpose of making information systems is to simplify and streamline human work.

Expert systems and their implementation will be discussed in detail on this occasion. As defined, this kind of system has some advantages and disadvantages which we will discuss in more detail below.

What are Expert System Components

First of all, we will talk about what an expert system is. The general definition of an "expert system" is a computer program or information system that uses the knowledge of one or more experts in a particular field.

What are Expert System Components

The targeted expert is someone who has unique expertise in their respective profession, for example doctors, psychologists, mechanics, and so on. The software was originally designed by researchers in artificial intelligence (AI) programs in the 1960s and 1970s and was only put into use in the 1980s.

Purpose of the Expert System Component

Expert systems have the capacity to propose a series of activities or user behavior to be able to operate a precise and accurate corrective system. In terms of drawing conclusions based on existing data and facts, this system utilizes the ability of reasoning processes.

The following are some of the main objectives of using an expert system:

Interpretation

An expert system attempts to produce an assessment or description of a collection of raw data (raw data). Decision making is based on observation results, starting from image analysis, speech recognition, signal interpretation, and so on.

predictions

Have the ability to predict the outcome of certain circumstances and events, such as demographic, economic, financial and other data,

Diagnosis

can find fault sources in complex scenarios based on observed symptoms with accurate diagnosis.

Design Design Expert System Components

able to find and develop configurations related to system components that are suitable for certain performance goals by meeting certain limits. Plans of buildings, fields, and so on are good examples.

Design Design Expert System Components

Planning

With the help of an expert system, a series of steps can be planned to achieve a certain goal at a certain time.

Monitoring

The implementation process is an example of a computer-assisted monitoring system, which involves anticipated state based observations (CAMS).

debugging

We can identify and analyze potential causes of system failures and malfunctions.

Instructions

recognize the degree to which you lack knowledge about the subject

Control

Have the knowledge to regulate complex environmental behavior patterns (environment). To illustrate, consider the concepts of interpretation control, improvement control, and prediction prediction (estimate).

Methods in the Expert System

There are various approaches used in using expert systems, including the following.

AHP (Analytical Hierarchy Process)

AHP is a technique that uses an expert system to compare many pairs of criteria and make judgments based on the results of these comparisons.

Variables are used to study programs hierarchically based on sequence for the program analysis approach. Then, it will be compared with existing metrics to draw conclusions about the value of each criterion and variable used.

Breadth First Search

Breadth-first search is an algorithm that functions to search extensively for data on an expert system. In this procedure, previously checked information is stored in the data queue process (queue).

In addition, a boolean table is also needed to store information in a node so that no information is viewed more than once.

BFS (Best First Search)

Combining DFS with a "breadth-first" approach is the best way to start the search, because the expert system can display the results of the variable analysis that has been carried out.

DFS (Depth First Search)

Expert systems are also used in the DFS approach. The algorithm relies on a tree or graph structure and data depth.

Forward Tracing (Forward Chaining)

It is a reasoning strategy that is incorporated into an expert system, which begins with a fact-finding procedure. Where the data is used to weigh the importance of a truth to the resulting hypothesis

Backward Chaining

Backward chaining is the opposite of forward chaining, where this approach monitors the decision system starting from the conclusion drawing stage at the point of reasoning. The next step is to come up with hypotheses and test them until you have enough information to draw a solid conclusion.

Backtracking Backward Chaining

The structure used in the Expert System Component

An expert system consists of various components and structures that work together to create a complete information system. The following are some of the components that make up this system architecture.

User Interface (User Interface)

Interface or interface is a technique used as a way to communicate and engage with people (users) (users). The interface gets information from the user and turns it into commands that the system can understand.

Knowledge Base

An understanding of problem solving formulations and techniques is included in the knowledge base. For a computer system to solve problems, knowledge must be acquired through accumulation, transformation, and transfer of capabilities.

The job of an engineer at this point is to collect all available information and store it in a central repository (insights).

Knowledge Acquisition

Acquisition of knowledge is the process of accumulation, transformation and transfer of any skills for solving problems from a source of knowledge into a computer system.

In this phase, the engineer's job is to absorb all the knowledge to be sent to the knowledge base (Insight).

Inference Engine (Inference Engine or Motor)

This component provides a method of thinking and mentality used by experts to be able to solve a problem well.

An inference engine is a piece of computer software that gives you methods to use at work and then analyzes the results to give you suggestions.

Workplace / Blackboard

Workspace is a working memory collection area that is used to record every event that occurs, including momentary decision making.

Facility Explanation

Annotation facilities are incorporated as an additional component to promote the use of expert systems and monitor the reactions and results of interactive explanations of behavior in expert systems.

Knowledge Improvement

Experts also have superior analytical skills to be able to improve their performance in such a way. This aptitude consists of proficiency in computerized learning. As a result, the algorithm is able to distinguish between past successes and failures based on data that will be useful in the future.

An example of an Expert System

The following are some examples of programs that implement expert systems, namely:

  1. Dendral is an application for determining the molecular composition of new chemical mixtures that have never been tested before.
  2. MYCIN is software designed to diagnose a wide variety of disorders.
  3. Prospector is an application adapted to the demands in the field of geology.
  4. XCON and XSEL are tools used to manage large computer systems.

Advantages of Expert Systems

The next thing that will be discussed is how to present information about the benefits of an expert system.

  1. Work more efficiently to get more done in less time.
  2. They have the ability to improve the quality of their advice by being more consistent.
  3. It has a high degree of dependability and capacity to operate in real time.

Disadvantages of Expert Systems

The weaknesses of the expert system are as follows:

  1. There is a barrier to gaining new experience or understanding by adopting different ways held by many experts.
  2. It costs a lot of money to train professionals, but the end result is worth it if the information they produce is of high quality.
  3. The level of expert system judgment does not always produce absolute truth. Still need frequent testing stages to be able to make the best decision.

Expert System advantages and disadvantages

FAQs

The following are questions and answers about expert system components that you should know about

What are some examples of expert systems?

Below are some examples of implementing expert systems, along with some background on the many ideas that inform them.

  1. Sophie: is the study of electric circuits, conducted by Sophie.
  2. Folio: assists managers in the selection of investments and brokerage stocks.
  3. Prospector: In geology, the word "prospector" refers to a tool used to assist in the search for mineral resources. This expert system was built by the Sheffield Research Institute in the late 70's.
  4. Dendral: Discover new organic structures using mass spectrometry and chemistry, as described in Dendral.
  5. Dipmeter Advisor: used by Schlumberger to check data in oil drilling. By using Mycin, disease-causing bacteria can be identified, and antibiotics can be prescribed based on the patient's weight. This system was invented by Edward Feigenbaum of Stanford University in the 70's.
  6. Delta: maintenance of diesel electric locomotives. The General Electric Company is responsible for conceptualizing and implementing this system.
  7. AT&T Bell Lab's ACE: Troubleshooting SP problems for early 1980s telephone wiring systems.
  8. XCON & XSEL: expert systems whose role is to help set up large computer systems. This system was created by Digital Equipment Corporation (DEC) and Carnegie Mellon University (CMU).
  9. MVS (multiple virtual storage) is an operating system developed by IBM in the early 1980s and controlled by YESMVS computers.

Since when did expert systems begin to be developed?

Expert systems were developed by the AI community in the mid-1960s. This period of artificial intelligence research was dominated by the belief that reason combined with sophisticated computers would produce expert or skilled human performance.

Who Calls an Expert?

An expert or expert is someone who is widely regarded as a trusted source of certain techniques or expertise, his talent lies in judging and deciding something correctly, according to the rules and status of other people or the public in a particular field of specialization.

Conclusion

An expert system is a computer program or information system that uses knowledge from one or more experts in a particular field. The software was originally designed by researchers in artificial intelligence (AI) programs in the 1960s and 1970s and was only put into use in the 1980s.

There are various techniques for using expert systems, including Breadth-First Search and Analytical Hierarchy Process. The implementation process is an example of a computer-assisted monitoring system (CAMS), thus the discussion in our article above, I hope this information is useful, that's all and thank you.

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