Sistemi per la Gestione Aziendale.

Slides:



Advertisements
Similar presentations
Università degli Studi di Perugia - Dipartimento di Ingegneria Industriale Prof. Francesco Castellani -
Advertisements

UNIVERSITÀ DEGLI STUDI DI PERUGIA Dipartimento di Ingegneria Industriale Prof. Francesco Castellani Corso di Meccanica Applicata A.
UNIVERSITÀ DEGLI STUDI DI PERUGIA Dipartimento di Ingegneria Industriale Prof. Francesco Castellani Corso di Meccanica Applicata A.
Università degli Studi di Perugia - Dipartimento di Ingegneria Industriale Prof. Francesco Castellani - MISURE.
Double Degree Agreement Pisa - Cranfield
Università di Napoli Federico II Dipartimento di Ingegneria Elettrica SAS Project Electromagnetic analysis of protection systems for airport structures.
WG1 Presentation. WG1: Economic Geography modeling Leader: Pasquale Commendatore (Università di Napoli ‘Federico II’, Italy) Co-leader: SaimeSuna KAYAM.
$100 $200 $300 $400 $500 $100 $200 $300 $400 $500 $100 $200 $300 $400 $500 $100 $200 $300 $400 $500 $100 $200 $300 $400 $500 $100 $200 $300.
FUZZY SYSTEMS. Fuzzy Systems Fuzzy Sets – To quantify and reason about fuzzy or vague terms of natural language – Example: hot, cold temperature small,
This is where they start. This is where the jet catches up and overtakes the plane. This distance is d Distance=RatexTime airplane jet 192 km/h 960 km/h.
Fuzzy Logic What is that? Prof. Dr. T. Nouri
Fuzzy Expert System.
1 Facoltà di Economia Corso di Laurea in Economia e Gestione Aziendale Corso di Laurea in Economia e Finanza Lingua Inglese Luisanna Fodde Olga Denti.
LAUREA IN INGEGNERIA BIOMEDICA Modulo di PRINCIPI DI BIOINGEGNERIA I University of Naples “Federico II” - Dept. of Electronic Engineering and Telecommunications.
1 Facoltà di Economia Corso di Laurea in Economia e Gestione Aziendale Corso di Laurea in Economia e Finanza Pre-Corso Lingua Inglese Business English.
N° 23 page 70page N° 24 page 70page N° 25 page 70page N° 26 page 70page N° 45 page 71page.
1Both Mr Rabbit and Mr Tortoise took the same round trip, but Mr Rabbit slept & returned later.
$100 $200 $300 $400 $500 $100 $200 $300 $400 $500 $100 $200 $300 $400 $500 $100 $200 $300 $400 $500 $100 $200 $300 $400 $500 $100 $200 $300.
 Definition Definition  Bit of History Bit of History  Why Fuzzy Logic? Why Fuzzy Logic?  Applications Applications  Fuzzy Logic Operators Fuzzy.
Motion Review Physics TCHS.
Национальная процедура одобрения и регистрации проектов (программ) международной технической помощи (исключая представление информации об организации и.
Napoli, – USEReST 2008 VOLCANO MONITORING VIA FRACTAL MODELING OF LAVA FLOWS Gerardo DI MARTINO Antonio IODICE Daniele RICCIO Giuseppe RUELLO.
“Principles of Soft Computing, 2 nd Edition” by S.N. Sivanandam & SN Deepa Copyright  2011 Wiley India Pvt. Ltd. All rights reserved. CHAPTER 12 FUZZY.
Chap 3: Fuzzy Rules and Fuzzy Reasoning J.-S. Roger Jang ( 張智星 ) CS Dept., Tsing Hua Univ., Taiwan Fuzzy.
Homework 5 Min Max “Temperature is low” AND “Temperature is middle”
 What is speed? › How fast you are going  What does it depend on? › How much distance you cover over a period of time. Ex. You drive at an average of.
Fuzzy Expert System n Introduction n Fuzzy sets n Linguistic variables and hedges n Operations of fuzzy sets n Fuzzy rules n Summary.
Physics of the Yellow Change Interval ITE International Convention, 8/3/
v- tx-tKinematics Reaction Time Chase.
Motion and Force 8SCIENCE.
University “Federico II” of Naples - Dept. of Electronic Engineering and Telecommunications Biomedical Engineering Unit - Via Claudio, Napoli.
 How fast or slow something moves.  Ex: Ms. McKinley’s Dodge Neon drives 70 mph down the 110 Fwy.  UNIT: distance unit divided by a time unit (ex:
基 督 再 來 (一). 經文: 1 你們心裡不要憂愁;你們信神,也當信我。 2 在我父的家裡有許多住處;若是沒有,我就早 已告訴你們了。我去原是為你們預備地去 。 3 我 若去為你們預備了地方,就必再來接你們到我那 裡去,我在 那裡,叫你們也在那裡, ] ( 約 14 : 1-3)
Dottorato di ricerca in Scienze e tecnologie delle produzioni agro-alimentari Università degli studi di Napoli Federico II Facoltà di Agraria XXIV ciclo.
Speed Speed describes how fast an object is moving Speed describes how fast an object is moving If an object is not moving it has no speed If an object.
Discussion: What is this residual plot telling us about the relationship between speed and braking distance? Let’s now end by discussing how to interpret.
Sistemi per la Gestione Aziendale.
tSmax = instant when the starch productivity reach the maximum.
Acceleration.
Facoltà di Scienze Economiche, Giuridiche e Politiche
Fuzzy Logic 11/6/2001.
Homework 8 Min Max “Temperature is low” AND “Temperature is middle”
Introduction to Fuzzy Logic
£"'>£"'>.I.I ' ·.· · ·..I.
Dr. Unnikrishnan P.C. Professor, EEE
INTELLIGENT CRUISE CONTROL WITH FUZZY LOGIC
In the name of God.
Facoltà di Scienze Economiche, Giuridiche e Politiche
Mathematics Murder Mystery
Homework 9 Min Max “Temperature is low” AND “Temperature is middle”
Lecture 2.2: Speed, Velocity, Acceleration
Velocity & Distance vs Time Graphs
Слайд-дәріс Қарағанды мемлекеттік техникалық университеті
Chapter 2 Acceleration.
.. -"""--..J '. / /I/I =---=-- -, _ --, _ = :;:.
II //II // \ Others Q.
I1I1 a 1·1,.,.,,I.,,I · I 1··n I J,-·
A car is decelerated to 20 m/s in 6 seconds
Velocity & Distance vs Time Graphs
Marzia Sorrentino Operations Project Manager Work Experience Education
September 10th SWBAT create & analyze position vs. time graphs.
The Kinematics Equations
MAY Grab the paper and your folder from the side counter.
EL Science--Component 5 Physics (Speed)
Calculating speed.
BETONLINEBETONLINE A·+A·+
. '. '. I;.,, - - "!' - -·-·,Ii '.....,,......, -,
Ferrari Company Presentation & «F-Factor: The Ferrari Case Study»
Increasing V Torque Speed Characteristic of Regenerative Braking T.
Presentation transcript:

Sistemi per la Gestione Aziendale. AA. 2006-07 Ingegneria Gestionale (LS) Facoltà di Ingegneria di Napoli SGA0607 LEZ29 Sistemi Fuzzy

The compositional rule of inference Pag.

Pag.

Giuseppe Zollo - DIS, Facoltà di Ingegneria, Università di Napoli Federico II - Piazzale Tecchio 80, 80125 Napoli (I) - email: giuzollo@unina.it Lez.GA.01.AA.98/99 Pag.

Fuzzy Sets for driving reasoning SHORT = A1 = [1.0, 0.5, 0] LONG = A2 = [0, 0.5, 1. 0] DISTANCE X1 = 10 m, X2 = 20 m, X3 = 30 m x1 x2 x3 B1 B2 SLOW = B1 = [1.0, 0.5, 0] FAST =B2 = [0, 0.5, 1.0] SPEED Y1 = 30 km/h, Y2 = 50 km/h, Y3 = 70 km/h y1 y2 y3 C2 C3 C1 HOLD = C1 = [0, 1, 0] BRAKE = C2 = [1.0, 0, 0] SPEED = C3 = [0, 0, 1] ACTION Z1 = -10 km/h, Z2 = 0 km/h, Z3 = +10 km/h z1 z2 z3

R1 10 20 30 30 50 70 -10 10 Km/h2 m Km/h R2 10 20 30 30 50 70 -10 10 R3 10 20 30 30 50 70 -10 10 R4 10 20 30 30 50 70 -10 10

R1 10 20 30 30 50 70 -10 10 Km/h2 m Km/h R2 10 20 30 30 50 70 -10 10 R3 10 20 30 30 50 70 -10 10 R4 10 20 30 30 50 70 -10 10 15 m 60 km/h

R1 10 20 30 30 50 70 -10 10 Km/h2 m Km/h R2 10 20 30 30 50 70 -10 10 R3 10 20 30 30 50 70 -10 10 R4 10 20 30 30 50 70 -10 10 15 m 60 km/h -10 10

R1 Km/h2 m Km/h R2 R3 R4 15 m 60 km/h -7 Km/h2 10 20 30 30 50 70 -10 10 Km/h2 m Km/h R2 10 20 30 30 50 70 -10 10 R3 10 20 30 30 50 70 -10 10 R4 10 20 30 30 50 70 -10 10 15 m 60 km/h -10 10 -7 Km/h2

R1 10 20 30 30 50 70 -10 10 Km/h2 m Km/h R2 10 20 30 30 50 70 -10 10 R3 10 20 30 30 50 70 -10 10 R4 10 20 30 30 50 70 -10 10 10 20 30 30 50 70

R1 10 20 30 30 50 70 -10 10 Km/h2 m Km/h R2 10 20 30 30 50 70 -10 10 R3 10 20 30 30 50 70 -10 10 R4 10 20 30 30 50 70 -10 10 10 20 30 30 50 70

R1 10 20 30 30 50 70 -10 10 Km/h2 m Km/h R2 10 20 30 30 50 70 -10 10 R3 10 20 30 30 50 70 -10 10 R4 10 20 30 30 50 70 -10 10 10 20 30 30 50 70

Rules 1 and 2

Rules 3 and 4

The Total Fuzzy Rule

Application