- My presentations
Auth with social network:
Download presentation
We think you have liked this presentation. If you wish to download it, please recommend it to your friends in any social system. Share buttons are a little bit lower. Thank you!
Presentation is loading. Please wait.
Expert System Lecture Module-16.
Published by Pauline Farmer Modified over 9 years ago
Similar presentations
Presentation on theme: "Expert System Lecture Module-16."— Presentation transcript:
Modelling with expert systems. Expert systems Modelling with expert systems Coaching modelling with expert systems Advantages and limitations of modelling.
ARCHITECTURES FOR ARTIFICIAL INTELLIGENCE SYSTEMS
STRONG METHOD PROBLEM SOLVING
Bayesian Network and Influence Diagram A Guide to Construction And Analysis.
CHAPTER 13 Inference Techniques. Reasoning in Artificial Intelligence n Knowledge must be processed (reasoned with) n Computer program accesses knowledge.
Truth Maintenance Systems. Outline What is a TMS? Basic TMS model Justification-based TMS.
The Logic of Intelligence Pei Wang Department of Computer and Information Sciences Temple University.
Rulebase Expert System and Uncertainty. Rule-based ES Rules as a knowledge representation technique Type of rules :- relation, recommendation, directive,
CS 484 – Artificial Intelligence1 Announcements Choose Research Topic by today Project 1 is due Thursday, October 11 Midterm is Thursday, October 18 Book.
Inferences The Reasoning Power of Expert Systems.
Intelligent systems Lecture 6 Rules, Semantic nets.
Rule Based Systems Michael J. Watts
Chapter 12: Expert Systems Design Examples
Rule Based Systems Alford Academy Business Education and Computing
Expert System Human expert level performance Limited application area Large component of task specific knowledge Knowledge based system Task specific knowledge.
1 5.0 Expert Systems Outline 5.1 Introduction 5.2 Rules for Knowledge Representation 5.3 Types of rules 5.4 Rule-based systems 5.5 Reasoning approaches.
Knowledge Acquisitioning. Definition The transfer and transformation of potential problem solving expertise from some knowledge source to a program.
CIS 430 ( Expert System ) Supervised By : Mr. Ashraf Yaseen Student name : Ziad N. Al-A’abed Student # : EXPERT SYSTEM.
1 Chapter 9 Rules and Expert Systems. 2 Chapter 9 Contents (1) l Rules for Knowledge Representation l Rule Based Production Systems l Forward Chaining.
Rules and Expert Systems
About project
© 2024 SlidePlayer.com Inc. All rights reserved.
Working together, we can reimagine medicine to improve and extend people’s lives.
Analytical Expert (ARD) (m/f/d)
About the role.
Major accountabilities:
- Designing, planning, supporting the execution as well as interpreting and reporting results of scientific experiments for the development and timely supply of drug substances (DS) and drug products (DP) intended for clinical use in late stage development and potential commercialization.
- Writing & reviewing analytical documents (e.g Analytical procedures, Specifications, Product characterization reports, Validation protocols/reports, Stability protocols/reports as well as Batch records compilation and line function material disposition for stability and release testing) and aligning the corresponding activities within a global project team.
- Managing interactions with internal and external stakeholders, including outsourced activities to CROs by providing scientific and technical guidance whenever necessary.
- Proactively identifying scientific, technological and GMP challenges, propose creative solutions and communicate key issues to the appropriate management level and respective technical project team.
- Working according to appropriate SOPs, GMP, Quality Directives, Health and Safety & internal Novartis guidelines.
Minimum Requirements:
- Minimum: Bachelor in analytical chemistry or equivalent with significant experience in analytical development of drugs. Desirable: Advanced degree in a relevant life science scientific area (e.g. Master, Ph.D. or equivalent in chemistry / pharmaceutical or analytical science).
- Preferably 5 years’ experience in the pharmaceutical industry with a track record in GMP activities for development or marketed products.
- Broad scientific knowledge in chemistry, pharmaceutical or analytical sciences, ability to perform in a global and highly dynamic environment.
- Advanced knowledge of analytical techniques and associated processes (e.g. HPLC and corresponding Chromatographic Data System, Dissolution rate, Quality management systems, statistical evaluation tools ...).
- Good presentation skills and scientific/technical writing skills and associated IT Tools.
- Fluent in English (oral and writing), German is advantageous.
Why Novartis? Our purpose is to reimagine medicine to improve and extend people’s lives and our vision is to become the most valued and trusted medicines company in the world. How can we achieve this? With our people. It is our associates that drive us each day to reach our ambitions. Be a part of this mission and join us! Learn more here: https://www.novartis.com/about/strategy/people-and-culture You’ll receive: You can find everything you need to know about our benefits and rewards in the Novartis Life Handbook. https://www.novartis.com/careers/benefits-rewards Commitment to Diversity and Inclusion: Novartis is committed to building an outstanding, inclusive work environment and diverse teams' representative of the patients and communities we serve. Accessibility and accommodation Novartis is committed to working with and providing reasonable accommodation to all individuals. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the recruitment process, or in order to receive more detailed information about the essential functions of a position, please send an e-mail to inclusion.switzerland@novartis.com and let us know the nature of your request and your contact information. Please include the job requisition number in your message. Join our Novartis Network: If this role is not suitable to your experience or career goals but you wish to stay connected to hear more about Novartis and our career opportunities, join the Novartis Network here: https://talentnetwork.novartis.com/network
Why Novartis: Helping people with disease and their families takes more than innovative science. It takes a community of smart, passionate people like you. Collaborating, supporting and inspiring each other. Combining to achieve breakthroughs that change patients’ lives. Ready to create a brighter future together? https://www.novartis.com/about/strategy/people-and-culture
Join our Novartis Network: Not the right Novartis role for you? Sign up to our talent community to stay connected and learn about suitable career opportunities as soon as they come up: https://talentnetwork.novartis.com/network
Benefits and Rewards: Read our handbook to learn about all the ways we’ll help you thrive personally and professionally: https://www.novartis.com/careers/benefits-rewards
Novartis is committed to building an outstanding, inclusive work environment and diverse teams' representative of the patients and communities we serve.
Expert Systems
Jul 30, 2014
240 likes | 575 Views
Expert Systems. Learning Objectives:. By the end of this topic you should be able to: explain what is meant by an expert system describe the components of an expert system describe the applications of an expert system. Expert Systems. In everyday life:. Expert Systems.
Share Presentation
- credit scoring
- decision making
- expert system
- previous responses
- computer program
Presentation Transcript
Learning Objectives: By the end of this topic you should be able to: • explain what is meant by an expert system • describe the components of an expert system • describe the applications of an expert system
Expert Systems In everyday life:
Expert Systems In everyday life: • humans interpret information to gain knowledge
Expert Systems In everyday life: • humans interpret information to gain knowledge • this knowledge is used as the basis for making decisions
Expert Systems In everyday life: • humans interpret information to gain knowledge • this knowledge is used as the basis for making decisions An expert system is:
Expert Systems In everyday life: • humans interpret information to gain knowledge • this knowledge is used as the basis for making decisions An expert system is: • a computer program, used to help with a decision making process
Expert Systems In everyday life: • humans interpret information to gain knowledge • this knowledge is used as the basis for making decisions An expert system is: • a computer program, used to help with a decision making process • aka rules-based system, knowledge system
An Expert System is:
An Expert System: • is a computer program • is made up of a set of rules • analyses information about a specific type of problem. • trys to solve a problem in the same way as a human expert • has a narrow range of expertise • gives answers to questions • asks questions based on previous responses • can show how it reached conclusions • can learn from experience (heuristic) • is based on probabilities, not certainties • based on research into Artificial Intelligence (AI)
Expert System - Definition • has three components:
Expert System - 3 components • knowledge base • set of rules • consists of If...Then… rules • e.g. IF it is raining THEN I need to take an umbrella with me
Expert System - 3 components • knowledge base • set of rules • consists of If...Then… rules • e.g. IF it is raining THEN I need to take an umbrella with me • inference engine • evaluates data against the knowledge base • to provide a conclusion
Expert System - 3 components • knowledge base • set of rules • consists of If...Then… rules • e.g. IF it is raining THEN I need to take an umbrella with me • inference engine • evaluates data against the knowledge base • to provide a conclusion • user interface • displays questions to be completed by the operator • displays conclusions as output
Examples of Expert Systems
Examples of Expert Systems • weather forecasting
Examples of Expert Systems • weather forecasting • fault diagnosis • electrical goods, cars
Examples of Expert Systems • weather forecasting • fault diagnosis • electrical goods, cars • medical diagnosis • diagnose blood infections, identify tumours
Examples of Expert Systems • weather forecasting • fault diagnosis • electrical goods, cars • medical diagnosis • diagnose blood infections, identify tumours • facial recognition
Examples of Expert Systems • weather forecasting • fault diagnosis • electrical goods, cars • medical diagnosis • diagnose blood infections, identify tumours • facial recognition • careers advice
Examples of Expert Systems • weather forecasting • fault diagnosis • electrical goods, cars • medical diagnosis • diagnose blood infections, identify tumours • facial recognition • careers advice • credit scoring • identifying whether or not an individual should be granted credit
Examples of Expert Systems • weather forecasting • fault diagnosis • electrical goods, cars • medical diagnosis • diagnose blood infections, identify tumours • facial recognition • careers advice • credit scoring • identifying whether or not an individual should be granted credit • financial planning • what if we …..?”
- More by User
Expert Systems. Sepandar Sepehr McMaster University November 2008. Outline. Definition Examples Components and Human Interfaces Major Components Major Roles of Individuals Notes on Components Expert System Features Goal-Driven Reasoning Uncertainty Data Driven Reasoning
1.53k views • 33 slides
Expert Systems. Presented by Mohammad Saniee December 2, 2003. Department of Computer Engineering Sharif University of Technology. Expert Systems. A branch of Artificial Intelligence that makes an extensive use of specialized knowledge to solve problems at the level of an human expert.
913 views • 28 slides
Expert Systems. Bahar KARAOĞLAN International Computer Institute (2008 Fall ). Goal. The goal of this course is to clarify Basic concepts behind expert systems knowledge representation , inference mechanisms, problem solving .
1.22k views • 66 slides
Expert Systems. Expert systems are AI programs that solve a highly technical problem in some domain Normally a human expert is used for solving such problems. An expert system encodes a human expert’s knowledge. Common areas: medicine science: chemistry, biology engineering agriculture
1.32k views • 21 slides
EXPERT SYSTEMS
EXPERT SYSTEMS. Review – Classical Expert Systems. Can incorporate Neural, Genetic and Fuzzy Components. Expert Systems can perform many functions. Rules can be fuzzy, quantum, modal, neural, Bayesian, etc. Special inference methods may be used. Concepts of Knowledge Representation:
704 views • 47 slides
Expert Systems. 3.3.4. The aim of this presentation. You will be able to: Explain what is meant by an expert system and describe its components and applications. Introduction. Society is becoming more complex. More and more information is becoming available.
447 views • 20 slides
ICT IGCSE. Expert Systems. Objectives. Understand the use of expert systems in Mineral prospecting Car engine fault diagnosis Medical d iagnosis Oil/mineral prospecting Plant/animal identification Strategy games eg Chess. What is an Expert System?.
5.56k views • 23 slides
Expert Systems. Constructive Problem Solving. S. H. Davarpanah [email protected]. Computer Group Engineering Department University of Science and Culture. Expert Systems . Constructive Problem Solving I cf. Jackson, Chapter 14 Constructive Problem Solving II
382 views • 15 slides
Expert Systems:
Expert Systems:. Engineering knowledge. Motivations. You saw expert system architecture in the last lecture. Today the focus is on knowledge engineering. There are different types of knowledge. The right approach and technique should be used for the knowledge required. Objectives.
654 views • 31 slides
Expert Systems. User interface. Reasoning. Control. Inference engine. user. Knowledge base. Components of an rule based Expert System. Learning Objectives. What you need to know about expert systems What expert systems are The purpose of expert systems The components of expert systems
902 views • 18 slides
Expert Systems. Dr. Samy Abu Nasser. Introduction Knowledge Representation Semantic Nets, Frames, Logic Reasoning and Inference Predicate Logic, Inference Methods, Resolution Reasoning with Uncertainty Probability, Bayesian Decision Making Expert System Design ES Life Cycle.
602 views • 44 slides
Expert Systems. Chapter 7 Introduction to CLIPS. 7.5. Entering and Exiting CLIPS. A> CLIPS CLIPS (V6.5 09/01/97) CLIPS> exit exit CLIPS> (+ 3 4) 7 CLIPS> (exit) A>. 7.6. Facts. A “chunk” of information in CLIPS is called a fact .
752 views • 50 slides
Expert Systems. Content. What is an Expert System? Characteristics of an Expert System. Classification of Expert Systems. Components of an Expert System. Advantages & Disadvantages of Expert Systems. Creating an Expert System. Content. What is an Expert System?
1.08k views • 46 slides
Expert Systems. Dr. Samy Abu Nasser. Introduction CLIPS Overview Concepts, Notation, Usage Knowledge Representation Semantic Nets, Frames, Logic Reasoning and Inference Predicate Logic, Inference Methods, Resolution Reasoning with Uncertainty Probability, Bayesian Decision Making.
450 views • 33 slides
Expert Systems. Robots Unlimited , p. 234 – 243. Expert Systems. Expert knowledge in many domains can be captured as rules. Dendral (1965 – 1975) If: The spectrum for the molecule has two peaks at masses x 1 and x 2 such that: x 1 + x 2 = molecular weight + 28,
346 views • 12 slides
831 views • 25 slides
Expert Systems. Linguistic variables: a quintuple (x,T(x),U,G, ) X is the name of the variable;
615 views • 53 slides
Chapter 8. Expert Systems. Expert System. p. 547 MYCIN (1976) see section 8.2 backward chaining + certainty factor and rule-based systems p.233 Bayesian network p. 239 Fuzzy logic p. 246 Probability and Bayes ’ theorem p. 231 PROSPECTOR (1976), DENDRAL (1978)
573 views • 30 slides
Expert Systems. Processor of a computer is known as the ‘brains’ of a computer. However, a processor cannot think or act for itself. Computers do have some form of intelligence this is know as Artificial Intelligence. An Expert System is a type of Artificial Intelligence Program.
261 views • 7 slides
842 views • 50 slides
646 views • 46 slides
Expert Systems. An expert system is a computer program that is designed to hold the accumulated knowledge of one or more domain experts. What is an ES?. Expert System (ES) is a branch of Artificial Intelligence that attempt to mimic human experts.
2.53k views • 10 slides
IMAGES
VIDEO
COMMENTS
Expert Systems: Principles and Programming, Fourth Edition. Download ppt "Chapter 1: Introduction to Expert Systems". Objectives Learn the meaning of an expert system Understand the problem domain and knowledge domain Learn the advantages of an expert system Understand the stages in the development of an expert system Examine the general ...
Presentation Transcript. Chapter 7:Introduction to Expert Systems Expert Systems: Principles. Objectives • Learn the meaning of an expert system • Understand the problem domain and knowledge domain • Learn the advantages of an expert system • Understand the stages in the development of an expert system • Examine the general ...
M SOLVER (GPS) by A. Newell and H. Simon.1969 DENDRAL (Feigenbaum, Buchanan, Lederberg) was the first system that showed the importance o. n-specific knowledge (expertise).1970sMYCIN (Buchanan & Shortliffe) medical diagnosis syste. introduced the use of certainty factors.1982 R1 (aka XCON) by McDermott was the first commercial ES (by.
Representation. mechanisms that permit efficient compilation and structuring of knowledge reduce run-time requirements of both time and memory. As an example, an object-oriented language allows some information to be stated once, in an abstract class, and accessed (by inheritance) in a large number of subclasses.
This presentation gives a concise explanation of expert systems, how they work and the various components of expert systems. It also explain the various type...
IDDS: Rules-based Expert Systems Based on a presentation by Mark Ponsen in 02/21/05 What is an Expert System Web definition: A computer program that contains expert knowledge about a particular problem, often in the form of a set of if-then rules, that is able to solve problems at a level equivalent or greater than human experts Building Expert ...
Presentation on theme: "Introduction to Expert Systems"— Presentation transcript: 1 Introduction to Expert Systems. 2 What is an expert system? "An expert system is a computer system that emulates, or acts in all respects, with the decision-making capabilities of a human expert." ...
Expert System • An expert system is a system that employs human knowledge captured in a computer to solve problems that ordinarily require human expertise. (Turban) • A computer program that emulates the behaviour of human experts who are solving real-world problems associated with a particular domain of knowledge.
Expert system. A Symbolics 3640 Lisp machine: an early (1984) platform for expert systems. In artificial intelligence (AI), an expert system is a computer system emulating the decision-making ability of a human expert. [1] Expert systems are designed to solve complex problems by reasoning through bodies of knowledge, represented mainly as if ...
Dependency-directed backtracking is a powerful technique based on the representations of the truth maintenance system. Download ppt "Expert System Lecture Module-16." Expert Systems (ES) Expert systems are knowledge based programs which provide expert quality solutions to the problems in specific domain of applications.
Expert System Presentation - Free download as PDF File (.pdf), Text File (.txt) or view presentation slides online. Expert systems are computer programs that mimic human experts to solve complex problems. The document discusses the components, architectures, benefits and challenges of expert systems. It provides examples of expert systems such as medical diagnosis systems, chess games and loan ...
Expert system Development and pitfalls.ppt - Free download as Powerpoint Presentation (.ppt), PDF File (.pdf), Text File (.txt) or view presentation slides online. The document discusses various considerations for building an expert system, including necessary requirements, justification, appropriate tasks, tool selection, knowledge acquisition, and common pitfalls.
expert system.pptx - Free download as Powerpoint Presentation (.ppt / .pptx), PDF File (.pdf), Text File (.txt) or view presentation slides online. Expert systems are computer applications that solve complex problems requiring human expertise. They contain a substantial knowledge base in a particular domain and use reasoning mechanisms to apply their knowledge to problems.
Expert Systems. An expert system is a computer program that is designed to hold the accumulated knowledge of one or more domain experts. What is an ES?. Expert System (ES) is a branch of Artificial Intelligence that attempt to mimic human experts. Slideshow 9417771 by candaceg.
Presentation Transcript. Expert System Lecture Module-16. Expert Systems (ES) • Expert systems are knowledge based programs which provide expert quality solutions to the problems in specific domain of applications. • The core components of expert system are • knowledge base and • navigational capability (inference engine) • Generally ...
Major accountabilities:Designing, planning, supporting the execution as well as interpreting and reporting results of scientific experiments for the development and timely supply of drug substances (DS) and drug products (DP) intended for clinical use in late stage development and potential commercialization.Writing & reviewing analytical documents (e.g Analytical procedures, Specifications ...
Presentation Transcript. Expert Systems. Learning Objectives: By the end of this topic you should be able to: • explain what is meant by an expert system • describe the components of an expert system • describe the applications of an expert system. Expert Systems In everyday life: Expert Systems In everyday life: • humans interpret ...