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Application of fuzzy logic and neural network technologies ...

A brief summary of Fuzzy Logic and Neural Network principles is presented to provide a basis for the introduction of two applications, one in Fuzzy Logic and the other utilising a Fuzzy Neural Network. The applications are part of a major project aiming to develop a new generation of fully automated control systems for Autocone cone crushers.

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Amanda Conner is an American comics artist and commercial art illustrator.She began her career in the late 1980s for Archie Comics and Marvel Comics, before moving on to contribute work for Claypool Comics' Soulsearchers and Company and Harris Comics' .

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Fuzzy Logic Book - University of Southern California. Introductory textbook on rule-based fuzzy logic systems, type-1 and type-2, that for the first time explains how fuzzy logic can MODEL a wide range of uncertainties and be designed to minimize their effects. This is an expanded and richer fuzzy logic.

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CONSTRAINT CONTROL OF A SIMULATED ORE CRUSHING .

desirable in some circumstances. The Fuzzy Logic Control strategy required more effort to configure and tune compared to the PID strategy. It was found that the configuration of the Fuzzy Logic Controller could affect performance and so the controller design as .

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Development of Fuzzy Logic Controller for Cement Mill

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Application of fuzzy logic and neural network technologies ...

All fights reserved 0892-6875/95 $9.50+0.00 APPLICATION OF FUZZY LOGIC AND NEURAL NETWORK TECHNOLOGIES IN CONE CRUSHER CONTROL M. MOSHGBAR R. PARKINt" and R.A BEARMAN$ De Montfort University, UK Dept. of Mechanical Engineering, Loughborough University of Technology, Loughborough, Leics.

mabe fuzzy logic 100 - rossjohnson

Fuzzy Logic Book - University of Southern California. Introductory textbook on rule-based fuzzy logic systems, type-1 and type-2, that for the first time explains how fuzzy logic can MODEL a wide range of uncertainties and be designed to minimize their effects. This is an expanded and richer fuzzy logic.

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The Evolution of Intelligent Systems in the Mining Industry2

Figure 1 – Secondary Crusher Fuzzy Logic Control System [Harris and Meech, 1987]. 5 of PI control provided gains that matched those from Fuzzy Control, and the potential to fine-tune the system to achieve even higher performance was considered a real .

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