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Artificial intelligence and expert systems for engineers by C.S. Krishnamoorthy

By C.S. Krishnamoorthy

This e-book offers a accomplished presentation of man-made intelligence (AI) methodologies and instruments helpful for fixing a large spectrum of engineering difficulties. what is extra, it bargains those AI instruments on an accompanying disk with easy-to-use software program. man made Intelligence and specialist structures for Engineers info the AI-based methodologies often called: Knowledge-Based professional platforms (KBES); layout Synthesis; layout Critiquing; and Case-Based Reasoning. KBES are the preferred AI-based instruments and feature been effectively utilized to making plans, prognosis, category, tracking, and layout difficulties. Case stories are supplied with difficulties in engineering layout for greater knowing of the problem-solving versions utilizing the 4 methodologies in an built-in software program environment.Throughout the publication, examples are given in order that scholars and engineers can gather abilities within the use of AI-based methodologies for program to functional difficulties starting from analysis to making plans, layout, and development and production in quite a few disciplines of engineering.Artificial Intelligence and specialist platforms for Engineers is a must-have reference for college students, lecturers, learn students, and execs operating within the quarter of civil engineering layout specifically and engineering layout more often than not.

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A user of the expert system has to interact with it for giving data, defining facts and monitoring the status of problem solving. Conveying of information, be it textual or graphical, to the user should also be done in a very effective manner. Thus, a user-interface module with the capability to handle textual and graphical information forms another component of the expert system. 1 shows the architecture of a KBES with its components and the way the components interact with each other. 1 Architecture of a KBES As seen so far, the knowledge base and the inference engine are the most important components in a KBES.

Due to the above-mentioned limitations, it becomes difficult to apply predicate logic-based knowledge representation in expert systems. A good knowledge representation scheme should have the capability to represent real-life situations (objects and relationships among them), which can be exploited by efficient guided search strategies and which better reflect the way humans perceive and think. Previous Table of Contents Next Products | Contact Us | About Us | Privacy | Ad Info | Home Use of this site is subject to certain Terms & Conditions, Copyright © 1996-2000 EarthWeb Inc.

Let the user response to the query for this variable be 15. This response establishes the first fact and it is stored in the context. This results in the condition ‘no of stories <= 5’ to be FALSE and rule 1 cannot be fired and is discarded. This is done by popping the rule stack. The inference process takes the next rule with the same consequent (which is rule 2) and pushes it into the rule stack and starts evaluating the first condition in the antecedent. As that also evaluates to FALSE, rule stack is popped and the next rule with the current goal variable (‘load bearing’) in consequent (rule 3) is pushed to the stack.

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