Pattern Matching Synthesis as an Automated Approach to Mechanism Design

1990 ◽  
Vol 112 (2) ◽  
pp. 190-199 ◽  
Author(s):  
D. A. Hoeltzel ◽  
Wei-Hua Chieng

A new knowledge-based approach for the synthesis of mechanisms, referred to as Pattern Matching Synthesis, has been developed based on a combination of committee machine and Hopfield neutral network models of pattern classification and matching applied to coupler curves. Computational tests performed on a dimensionally-parameterized four bar mechanism have yielded 15 distinct coupler curve groups (patterns) from a total of 356 generated coupler curves. This innovative approach represents a first step toward the automation of mapping structure-to-function in mechanism design based on the application of artificial intelligence programing techniques. Demonstrative examples of its application to “real-world” mechanism synthesis problems, including the design and evaluation of a two-stroke pump mechanism and the redesign of a variable-stroke engine mechanism have been included, establishing its viability for creative mechanism synthesis.

Author(s):  
D. A. Hoeltzel ◽  
W.-H. Chieng

Abstract A new knowledge-based approach for the synthesis of mechanisms, referred to as Pattern Matching Synthesis, has been developed based on committee machine and Hopfield neural network models of pattern matching applied to coupler curves. Computational tests performed on a dimensionally parameterized four bar mechanism have yielded 15 distinct coupler curve groups (patterns) from a total of 356 generated coupler curves. This innovative approach represents a first step toward the automation of mapping structure-to-function in mechanism design based on the application of artificial intelligence programming techniques.


Author(s):  
A. H. Soni ◽  
Y. Weng

Abstract EQ-1, an algebraic equation derivation system for a variety of mechanism synthesis motion programs, is presented in the paper. This project is considered as part of the automated mechanism design procedure. The applied Artificial Intelligence techniques are introduced to the mechanism design area. The blackboard model for problem solving is adopted in the system for organizing reasoning steps and domain knowledge to construct a solution to a specified mechanism configuration. A frame-like data structure is demonstrated in the system. The domain knowledge is kept in several independent knowledge sources. Meanwhile, the path propagation method is addressed to control the knowledge application.


2020 ◽  
Vol 961 (7) ◽  
pp. 27-36
Author(s):  
A.K. Cherkashin

The purpose of the study is to show how the features of geocartographic way of thinking are manifested in the meta-theory of knowledge based on mathematical formalisms. General cartographic concepts and regularities are considered in the view of metatheoretic analysis using cognitive procedures of fiber bundle from differential geometry. On levels of metainformation generalization, the geocartographic metatheoretic approach to the study of reality is higher than the system-theoretical one. It regulates the type of equations, models, and methods of each intertheory expressed in its own system terms. There is a balance between the state of any system and its geographical environment; therefore the observed phenomena are only explained theoretically in a metatheoretic projection on the corresponding system-thematic layer of the knowledge map. Metatheoretic research enables passing from the systematization of already known patterns to the formation of new knowledge through the scientific stratification of reality. General methods of metatheoretic analysis are mathematically distinguished


1989 ◽  
Vol 17 (3) ◽  
pp. 189-203 ◽  
Author(s):  
Philip Duchastel

Games have a fascination for people which make them ideal vehicles for instruction of an informal nature. Described here is an instructional game (GEO) in which the user learns elements of Canadian geography as she chases a spy around the country. The game utilizes artificial intelligence approaches to represent and put to use various types of knowledge (knowledge of geography, of tutoring, and of the student). Our experience in designing and refining the game is discussed, as well as prospects for extending this approach to other learning situations.


2017 ◽  
Vol 26 (3) ◽  
pp. 433-437
Author(s):  
Mark Dougherty

AbstractForgetting is an oft-forgotten art. Many artificial intelligence (AI) systems deliver good performance when first implemented; however, as the contextual environment changes, they become out of date and their performance degrades. Learning new knowledge is part of the solution, but forgetting outdated facts and information is a vital part of the process of renewal. However, forgetting proves to be a surprisingly difficult concept to either understand or implement. Much of AI is based on analogies with natural systems, and although all of us have plenty of experiences with having forgotten something, as yet we have only an incomplete picture of how this process occurs in the brain. A recent judgment by the European Court concerns the “right to be forgotten” by web index services such as Google. This has made debate and research into the concept of forgetting very urgent. Given the rapid growth in requests for pages to be forgotten, it is clear that the process will have to be automated and that intelligent systems of forgetting are required in order to meet this challenge.


2022 ◽  
Vol 12 ◽  
Author(s):  
Xueyun Zeng ◽  
Xuening Xu ◽  
Yenchun Jim Wu

Application of artificial intelligence is accelerating the digital transformation of enterprises, and digital content optimization is crucial to take the users' attention in social media usage. The purpose of this work is to demonstrate how social media content reaches and impresses more users. Using a sample of 345 articles released by Chinese small and medium-sized enterprises (SMEs) on their official WeChat accounts, we employ the self-determination theory to analyze the effects of content optimization strategies on social media visibility. It is found that articles with enterprise-related information optimized for content related to users' psychological needs (heart-based content optimization, mind-based content optimization, and knowledge-based content optimization) achieved higher visibility than that of sheer enterprise-related information, whereas the enterprise-related information embedded with material incentive (benefits-based content optimization) brings lower visibility. The results confirm the positive effect of psychological needs on the diffusion of enterprise-related information, and provide guidance for SMEs to apply artificial intelligence technology to social media practice.


Author(s):  
K. P. V. Sai Aakarsh ◽  
Adwin Manhar

Over many centuries, tools of increasing sophistication have been developed to serve the human race Digital computers are, in many respects, just another tool. They can perform the same sort of numerical and symbolic manipulations that an ordinary person can, but faster and more reliably. This paper represents review of artificial intelligence algorithms applying in computer application and software. Include knowledge-based systems; computational intelligence, which leads to Artificial intelligence, is the science of mimicking human mental faculties in a computer. That assists Physician to make dissection in medical diagnosis.


2021 ◽  
Vol 5 (9) ◽  
pp. RV1-RV5
Author(s):  
Sahrish Tariq ◽  
Nidhi Gupta ◽  
Preety Gupta ◽  
Aditi Sharma

The educational needs must drive the development of the appropriate technology”. They should not be viewed as toys for enthusiasts. Nevertheless, the human element must never be dismissed. Scientific research will continue to offer exciting technologies and effective treatments. For the profession and the patients, it serves to benefit fully from modern science, new knowledge and technologies must be incorporated into the mainstream of dental education. The technologies of modern science have astonished and intrigued our imagination. Correct diagnosis is the key to a successful clinical practice. In this regard, adequately trained neural networks can be a boon to diagnosticians, especially in conditions having multifactorial etiology.


10.14311/1121 ◽  
2009 ◽  
Vol 49 (2) ◽  
Author(s):  
M. Chvalina

This article analyses the existing possibilities for using Standard Statistical Methods and Artificial Intelligence Methods for a short-term forecast and simulation of demand in the field of telecommunications. The most widespread methods are based on Time Series Analysis. Nowadays, approaches based on Artificial Intelligence Methods, including Neural Networks, are booming. Separate approaches will be used in the study of Demand Modelling in Telecommunications, and the results of these models will be compared with actual guaranteed values. Then we will examine the quality of Neural Network models. 


2021 ◽  
Vol 15 (5) ◽  
pp. 583
Author(s):  
Fadwa Oukhay ◽  
Ahmed Badreddine ◽  
Taieb Ben Romdhane

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