Estimating Technology Insertion Risk Using Fuzzy Logic

2001 ◽  
Author(s):  
Don Yates ◽  
Alley Butler
Keyword(s):  
Fuzzy Logic ◽  
Limited Information ◽  
Fuzzy Methods ◽  
Schedule Risk ◽  
Fuzzy Logic Method ◽  
Commercial Off The Shelf ◽  
And Performance ◽  
Available Information ◽  
Spread Sheet ◽  
Excel Spread Sheet

Abstract Technology insertion into an existing system or subsystem requires careful planning and evaluation. Because the technology is new, there is often limited information upon which to base decisions. Further, decisions about technology insertion are typically made in the very early stages of a project when detailed information is sparse. Under these circumstances, the available information is typically linguistic, and fuzzy methods can be used to significant advantage in this environment. The implementation discussed in this paper employs an Excel spread sheet for user interface, and it employs COTS (Commercial Off the Shelf Technology) software for an inference engine. Heuristic based models are developed to evaluate risk in technology insertion. Risk elements include: budget risk, schedule risk, and performance risk. Results with an example problem are described to illustrate the fuzzy logic method, and conclusions are drawn regarding the advantages of this technique.

scholarly journals Design of Parking Control Using Ultrasonic Sensor Based On Fuzzy Logic

2019 ◽  
Vol 3 (1) ◽  
pp. 155
Author(s):  
Insidini Fawwaz ◽  
Fadhillah Azmi ◽  
. Muhathir ◽  
N P Dharshinni
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Ultrasonic Sensor ◽  
Public Places ◽  
Proximity Sensor ◽  
Parking Lots ◽  
Fuzzy Methods ◽  
Infra Red ◽  
Parking Lot ◽  
Fuzzy Logic Method

<span>The number of vehicles in Indonesia is currently increasing, which is not matched by the availability of parking lots, especially cars. Like in public places, namely, offices, shops, and other public places. However, in Indonesia the use of parking lots is still less organized, such as too close the position of one car to another, the position of the vehicle that is not in line with the slot, this can cause inconvenience in the use of parking lots or both parties. Supervision carried out by the manager of the parking lot is still lacking because it can be caused by the vast parking area and the number of supervised vehicles, so that a parking control system is needed that can help overcome this problem. The control system to be designed uses a proximity sensor to detect the proximity of the vehicle to one another, where the position of the vehicle has been determined, not only to detect proximity, but the number of vehicles that have entered the parking area, so parking users know whether the slot provided is still available or not. To detect distance, fuzzy logic method is applied. Fuzzy methods are applied to read the conditions received by the proximity sensor, and calculate the number of vehicles using infra red and photodiode sensors. If information from the proximity sensor that is processed in the microcontroller by fuzzy logic is detected, the output is in the form of an LED indicator and alarm warning.</span>

Application Fuzzy Logic System for Accurate Sheet Trim Shower Position

2019 ◽  
Vol 3 (1) ◽  
pp. 186-192
Author(s):  
Yudi Wibawa
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Dc Motor ◽  
Automation System ◽  
Paper Making ◽  
System A ◽  
Accurate Position ◽  
And Performance ◽  
Better Than ◽  
Logic System

This paper aims to study for accurate sheet trim shower position for paper making process. An accurate position is required in an automation system. A mathematical model of DC motor is used to obtain a transfer function between shaft position and applied voltage. PID controller with Ziegler-Nichols and Hang-tuning rule and Fuzzy logic controller for controlling position accuracy are required. The result reference explains it that the FLC is better than other methods and performance characteristics also improve the control of DC motor.

Pengembangan Aplikasi Pendukung Keputusan Pemilihan Program Studi dengan Metode Fuzzy Logic (Studi Kasus: Universitas Multimedia Nusantara)

2016 ◽  
Vol 7 (1) ◽  
pp. 12-18
Author(s):  
Joko Haryanto ◽  
Seng Hansun
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
System Application ◽  
Prospective Students ◽  
Fuzzy Logic Method ◽  
Index Terms ◽  
Selection Of

This paper describes the development of decision support system application to assist students who want to enter college so that no one choose the majors incorrectly. This application uses fuzzy logic method because fuzzy logic is very flexible in data which are vague and can be represented as a linguistic variable. The purpose of this application is to assist students to choose available majors at University Multimedia Nusantara which are appropriate with his/her capabilities. This application accepts five kinds of input values i.e. Mathematics, Indonesian, English, Physics, and TIK. Received input will be processed by the calculation of the system for decision-making and the application will generate output that shows how great a match for each majors. With this application, prospective students can find out where the majors that match his/her capabilities. This application has ninety nine percentage of match result accuracy. Index Terms—fuzzy logic, decision support system, UMN, selection of major

It's about Time! Introducing Students to the Concept of Billable Hours and Improving Their Excel Skills By Creating a Spreadsheet to Track Their Time

2015 ◽  
Vol 10 (1) ◽  
pp. 37-43 ◽  
Author(s):  
Timothy C. Hinson ◽  
Lorraine S. Lee ◽  
David C. Hayes
Keyword(s):  
Public Accounting ◽  
Tracking Time ◽  
Spread Sheet ◽  
Excel Spread Sheet

ABSTRACT The concepts of billable hours and tracking time are a reality in public accounting. The purpose of this case is to educate students on the concept of billable hours and to improve the student's Excel skills through the development of a spreadsheet to track their time. Students were required to create the time-tracking Excel spread-sheet and to track all (personal and school-related) of their time for two weeks. Students were given pre/post tests and surveys and the results reflect that students significantly increased their performance in intermediate and advanced Excel skills, billable hours concepts and realize the difficulty in tracking time. Even though the students acknowledged the difficulty in tracking time, they did enjoy learning more about billable hours that they may encounter in their future professions.

The Integrated Control of Semi-Active Suspension and Electronic Stability Program Based on Fuzzy Logic Method

2010 ◽  
Vol 29-32 ◽  
pp. 2059-2064
Author(s):  
Jian Hua Guo ◽  
Liang Chu ◽  
Xiao Bing Zhang ◽  
Fei Kun Zhou
Keyword(s):  
Fuzzy Logic ◽  
Integrated Control ◽  
Integrated System ◽  
Ride Quality ◽  
Electronic Stability Program ◽  
Vehicle Handling ◽  
Logic Control ◽  
Fuzzy Logic Method ◽  
The Individual ◽  
Integrated Control System

In this paper, an integrated system of SAS/ESP is proposed to improve vehicle handling performance and stability. The 15DOF vehicle model which describes the dynamics of the integrated system is established. A fuzzy logic control strategy is presented to control the integrated system. The simulation results show that the integrated control system can obviously improve vehicle maneuverability and ride quality much more than the individual control.

Prediction of State of Charge (SOC) of Battery Electric Vehicle

2021 ◽  
Vol 104 ◽  
pp. 65-71
Author(s):  
Illa Rizianiza ◽  
Dian Mart Shoodiqin
Keyword(s):  
Fuzzy Logic ◽  
Maximum Energy ◽  
State Of Charge ◽  
Battery Management ◽  
Charge Condition ◽  
Available Energy ◽  
Energy Needs ◽  
Fuzzy Logic Method ◽  
Input Variables ◽  
Charging And Discharging Processes

Batteries have an important thing in development of energy needs. A good performance battery, will support the device it supports. The energy that can save a battery is limited, so the battery will increase its charge and discharge cycles. Incorrect charging and discharging processes can cause battery performance to decrease. Therefore battery management is needed so that the battery can reach the maximum. One aspect of battery management is setting the state which is the ratio of available energy capacitance to maximum energy capacity. One method for estimating load states is the fuzzy logic method, namely by assessing the input and output systems of prediction. Predictor of State of Charge use Mamdani Fuzzy Logic that have temperature and voltage as input variables and State of Charge as output variable. A result of prediction State of Charge battery is represented by the number of Root Mean Square Error. Battery in charge condition has 2.7 for RMSE and level of accuracy 81.5%. Whereas Battery in discharge condition has RMSE 1.5 and level of accuracy 84.7%.

scholarly journals Using WSR-88D Polarimetric Data to Identify Bird-Contaminated Doppler Velocities

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Yuan Jiang ◽  
Qin Xu ◽  
Pengfei Zhang ◽  
Kang Nai ◽  
Liping Liu
Keyword(s):  
Fuzzy Logic ◽  
Real Data ◽  
Radar Data ◽  
Second Step ◽  
Doppler Velocity ◽  
Data Quality Control ◽  
Fuzzy Logic Method ◽  
Automated Technique ◽  
Migrating Birds ◽  
Logic Method

As an important part of Doppler velocity data quality control for radar data assimilation and other quantitative applications, an automated technique is developed to identify and remove contaminated velocities by birds, especially migrating birds. This technique builds upon the existing hydrometeor classification algorithm (HCA) for dual-polarimetric WSR-88D radars developed at the National Severe Storms Laboratory, and it performs two steps. In the first step, the fuzzy-logic method in the HCA is simplified and used to identify biological echoes (mainly from birds and insects). In the second step, another simple fuzzy logic method is developed to detect bird echoes among the biological echoes identified in the first step and thus remove bird-contaminated velocities. The membership functions used by the fuzzy logic method in the second step are extracted from normalized histograms of differential reflectivity and differential phase for birds and insects, respectively, while the normalized histograms are constructed by polarimetric data collected during the 2012 fall migrating season and sorted for bird and insects, respectively. The performance and effectiveness of the technique are demonstrated by real-data examples.

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