Inference Engine An Inference Engine is a tool from Artificial Intelligence. The first inference engines were components of expert systems. The typical expert system consisted of a knowledge base and an inference engine. The knowledge base stored facts about the world. The inference engine applied logical rules to the knowledge base and deduced new knowledge. Architecture[edit] The logic that an inference engine uses is typically represented as IF-THEN rules. A simple example of Modus Ponens often used in introductory logic books is "If you are human then you are mortal". Rule1: Human(x) => Mortal(x) A trivial example of how this rule would be used in an inference engine is as follows. This innovation of integrating the inference engine with a user interface led to the second early advancement of expert systems: explanation capabilities. An inference engine cycles through three sequential steps: match rules, select rules, and execute rules. Implementations[edit] See also[edit] References[edit]
List of types of systems engineering From Wikipedia, the free encyclopedia Jump to navigationJump to search This list of types of systems engineering gives an overview of the types of systems engineering. B[edit] Biological systems engineering[1] C[edit] Communications system engineering, see telecommunicationComputer systems engineering, see also computer engineering[2]Computer science and systems engineering, see also computer science[3]Control systems engineering[4] E[edit] I[edit] M[edit] Manufacturing systems engineering, see also industrial engineering[8]Marine systems engineering, see also naval architecture[9]Mechanical and systems engineering, see also mechanical engineering[10] P[edit] Petroleum systems engineering, see also petroleum engineering[11]Power systems engineering, see also power engineering[12]Process systems engineering, see also industrial engineering[13] S[edit] See also[edit] References[edit]
Telecommunications engineering Engineering science that deals with the recording, transmission, processing and storage of messages Telecommunications engineering is a subfield of electronics engineering which seeks to design and devise systems of communication at a distance.[1][2] The work ranges from basic circuit design to strategic mass developments. A telecommunication engineer is responsible for designing and overseeing the installation of telecommunications equipment and facilities, such as complex electronic switching systems, and other plain old telephone service facilities, optical fiber cabling, IP networks, and microwave transmission systems. Telecommunication is a diverse field of engineering connected to electronic, civil and systems engineering.[1] Ultimately, telecom engineers are responsible for providing high-speed data transmission services. History[edit] Telegraph and telephone[edit] Radio and television[edit] Satellite[edit] Computer networks and the Internet[edit] Optical fiber[edit] Concepts[edit]
Knowledge Base A knowledge base (KB) is a technology used to store complex structured and unstructured information used by a computer system. The initial use of the term was in connection with expert systems which were the first knowledge-based systems. The original use of the term knowledge-base was to describe one of the two sub-systems of a knowledge-based system. A knowledge-based system consists of a knowledge-base that represents facts about the world and an inference engine that can reason about those facts and use rules and other forms of logic to deduce new facts or highlight inconsistencies.[1] The term 'knowledge-base' was to distinguish from the more common widely used term database. Flat data. Early expert systems also had little need for multiple users or the complexity that comes with requiring transactional properties on data. The volume requirements were also different for a knowledge-base compared to a conventional database. See also[edit] Notes[edit]
Advanced Innovation Design Approach Advanced Innovation Design Approach (AIDA) is a holistic approach for enhancing innovative and competitive capability of industrial companies. The name Advanced Innovation Design Approach (AIDA) was proposed in the research project "Innovation Process 4.0" run at the University of Applied Sciences Offenburg, Germany in co-operation with 10 German industrial companies in 2015–2019.[1] AIDA can be considered as a pioneering mindset, an individually adaptable range of strongest innovation techniques such as comprehensive front-end innovation process, advanced innovation methods, best tools and methods of the theory of inventive problem solving TRIZ,[2] organisational measures for accelerating innovation, IT-solutions for Computer-Aided Innovation, and other tools for new product development, elaborated in the recent decade in the industry and academia. Principle of completeness[edit] Initial complex problem must be segmented into the partial problems. Voice-of-the-Customer Methods,[5] e.g.
Transportation engineering Academic discipline and occupational field The engineering of this roundabout in Bristol, England, attempts to make traffic flow free-moving Transportation engineering or transport engineering is the application of technology and scientific principles to the planning, functional design, operation and management of facilities for any mode of transportation in order to provide for the safe, efficient, rapid, comfortable, convenient, economical, and environmentally compatible movement of people and goods transport. The planning aspects of transportation engineering relate to elements of urban planning, and involve technical forecasting decisions and political factors. Before any planning occurs an engineer must take what is known as an inventory of the area or, if it is appropriate, the previous system in place. Highway engineering[edit] Engineers in this specialization: Railroad engineering[edit] Typical tasks include: Port and harbor engineering[edit] Airport engineering[edit] See also[edit]
Knowledge-Based Systems Knowledge-Based systems were first developed by Artificial Intelligence researchers. These early knowledge-based systems were primarily expert systems. In fact the term is often used synonymously with expert systems. The difference is in the view taken to describe the system. The first knowledge-based systems were rule based expert systems. Acquisition & Maintenance. As knowledge-based systems became more complex the techniques used to represent the knowledge base became more sophisticated. Another advancement was the development of special purpose automated reasoning systems called classifiers. The most recent advancement of knowledge-based systems has been to adopt the technologies for the development of systems that use the Internet. See also[edit] References[edit] External links[edit] Akerkar RA and Sajja Priti Srinivas (2009).
Alan Turing Institute Research institute in Britain The Alan Turing Institute is the United Kingdom's national institute for data science and artificial intelligence, founded in 2015 and largely funded by the UK government. It is named after Alan Turing,[1] the British mathematician and computing pioneer. Governance[edit] The Alan Turing Institute is an independent private-sector legal entity, operating not-for-profit and as a charity.[2] It is a joint venture among the University of Cambridge, the University of Edinburgh, the University of Oxford, University College London (UCL) and the University of Warwick, selected on the basis of international peer review.[3] In 2018, the institute was joined by eight additional university partners: Queen Mary University of London, University of Leeds, University of Manchester, University of Newcastle, University of Southampton, University of Birmingham, University of Exeter and University of Bristol.[4] Funding[edit] Location[edit] Background[edit] Notable people[edit]