By Spyros Tzafestas, Henk Verbruggen (auth.), Professor Spyros G. Tzafestas, Henk B. Verbruggen (eds.)
This ebook is worried with man made Intelligence (AI) innovations and methods as utilized to business determination making, keep watch over and automation difficulties. the sphere of AI has been extended tremendously over the past years as a result of that reliable theoretical and alertness effects have amassed. in the course of the first degree of AI improvement so much staff within the box have been content material with illustrations displaying principles at paintings on uncomplicated difficulties. Later, because the box matured, emphasis used to be became to demonstrations that confirmed the potential of AI strategies to address difficulties of functional price. Now, we arrived on the degree the place researchers and practitioners are literally construction AI platforms that face real-world and commercial difficulties. This quantity presents a suite of twenty 4 well-selected contributions that care for the applying of AI to such real-life and commercial difficulties. those contributions are grouped and provided in 5 components as follows: half 1: normal matters half 2: clever structures half three: Neural Networks in Modelling, keep watch over and Scheduling half four: process Diagnostics half five: commercial robot, production and Organizational structures half 1 includes 4 chapters delivering historical past fabric and working with common concerns comparable to the conceptual integration of qualitative and quantitative versions, the therapy of timing difficulties at procedure integration, and the research of right reasoning in interactive man-robot systems.
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Extra info for Artificial Intelligence in Industrial Decision Making, Control and Automation
A filtering process is needed for separating the correct predictions from the erroneous ones. This filtering process is usually designed using quantitative information about the system at hand. Our purpose here is to discuss the application of qualitative reasoning for control purposes. The control problem via this approach was studied by Kuipers and applied to a liquid control problem. Another interesting piece of work in this direction has been completed by Francis and Leitch [27,28]. They produced a Prolog-based expert system shell (called ARTIFACI') for the automation of the decision and control process.
E. 6). 2)} Thus, IF "X small" AND "X nearly equal to )I', THEN fly nearly small". Shafer - Dempster approach: The Shafer Dempster theory provides a more rigorous basis for the use of certainty factors and other indicators (measures) of uncertainty [20 -22]. This theory uses the numbers of the interval [0,1] to represent the support of some hypothesis from a piece of evidence. Let X denote the frame of discerment (reference superset). , V, -). The function m is called the basic probability assignment and it is a generalization of the classical concept of probability density function which distributes the unit probability among the elements of X (while m distributes 1 among the elements of 5).
7. Typical multilayered network weights using some error function of any kind of criterion. In a strict forward network, information flows from the input layer, through a number of hidden layers, to the output layer. In the case of feedback connections, information reverberates around the network under control of an algorithm, taking into account a convergence algorithm. In that case the network can be described by a nonlinear dynamical system. The application of a neural network can be divided into two main phases: 1.
Artificial Intelligence in Industrial Decision Making, Control and Automation by Spyros Tzafestas, Henk Verbruggen (auth.), Professor Spyros G. Tzafestas, Henk B. Verbruggen (eds.)