Fuzzy logic based interactive recovery of software design

2003 ◽  
Author(s):  
J. Niere
Keyword(s):  
Fuzzy Logic ◽  
Software Design

scholarly journals Design and Construction of Crop Suitability Prediction System Using Fuzzy Logic Classifier Method

2021 ◽  
Vol 21 (3) ◽  
pp. 139-148
Author(s):  
Meli Gustina ◽  
◽  
Irma Salamah ◽  
Lindawati Lindawati ◽  
◽  
...  
Keyword(s):  
Land Use ◽  
Fuzzy Logic ◽  
Soil Temperature ◽  
Soil Ph ◽  
Software Design ◽  
Agricultural Land ◽  
Prediction System ◽  
Crop Suitability ◽  
Input Variables ◽  
Two Stages

The potential of land in Indonesia which is quite large and has not been used optimally is one of the problems. this study focused on developing fuzzy logic models to predict plants that are suitable for planting on agricultural land to enable the land use more optimal. In conducting this study, there were two stages of implementation, namely hardware design, and software design which included system workflow design using the Fuzzy Logic Classifier method where three input variables were used, namely soil pH, soil temperature, and humidity. The findings of this study are in the form of predictions consisting of eight outputs, namely Unfavorable Land, Spinach, Cayenne Pepper, Beans, Long Beans, Cucumber, Eggplant, and Tomatoo. The prediction results generated were directly displayed on the LCD of the instrument that has been designed.

scholarly journals DESIGN OF FUZZY LOGIC CONTROLLER FOR CHARGING SYSTEM WITH TEMPERATURE CONDITION SYSTEM IN EXCAVATOR

2019 ◽  
Vol 1 (1) ◽  
pp. 27-30
Author(s):  
Frendit Wijaya
Keyword(s):  
Fuzzy Logic ◽  
Software Design ◽  
Fuzzy Logic Controller ◽  
Battery Management ◽  
Motor Speed ◽  
Charging System ◽  
Energy Needs ◽  
A Charge ◽  
The Ideal

Batteries have an important role in the development of energy needs. A good battery performance, will support the device it supports. The amount of battery that can be stored is limited, the battery will experience a charge and discharge cycle. One aspect of battery management is how the temperature in the battery is always controlled. This will place the battery always in the ideal temperature so that it can work optimally. The stages in software design consist of designing a fuzzy logic controller that uses Arduino software. To display the results of reading the system, the Serial Monitor is used in the Arduino software. From the data, the response from the control used will be observed. The system is controlled using the Fuzzy Logic Controller method. In this experiment, the input used is the LM35 temperature sensor. This value will affect the speed of the DC motor which in this experiment is regulated through the determination of the PWM value. There are 3 PWM values, namely 100 for slow motor speed, 200 for medium motor speed and 255 for fast motor speed.

scholarly journals FPGA based co-design of a speed fuzzy logic controller applied to an autonomous car

2021 ◽  
Vol 10 (3) ◽  
pp. 195
Author(s):  
Emna Aridhi ◽  
Decebal Popescu ◽  
Abdelkader Mami
Keyword(s):  
Signal Processing ◽  
Fuzzy Logic ◽  
Digital Signal Processing ◽  
Ambient Temperature ◽  
Software Design ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Digital Signal ◽  
Execution Cycle ◽  
Simulation Results

This paper invests in FPGA technology to control the speed of an autonomous car using fuzzy logic. For that purpose, we propose a co-design based on a novel fuzzy controller IP. It was developed using the hardware language VHDL and driven by the Zynq processor through an SDK software design written in C. The proposed IP acts according to the ambient temperature and the presence or absence of an obstacle and its distance from the car. The partitioning of the co-design tasks divides them into hardware and software parts. The simulation results of the fuzzy IP and those of the complete co-design implementation on a Xilinx Zynq board showed the effectiveness of the proposed controller to meet the target constraints and generate suitable PWM signals. The proposed hardware architecture based on 6-LUT blocks uses 11 times fewer logic resources than other previous similar designs. Also, it can be easily updated when new constraints on the system are to be considered, which makes it suitable for many related applications. Fuzzy computing was accelerated thanks to the use of digital signal processing blocks that ensure parallel processing. Indeed, a complete execution cycle takes only 7 us.

Hysteresis in Categorization: Fuzzy Logic Makes Fuzzy Boundaries

2012 ◽  
Author(s):  
Thomas M. Crawford ◽  
Justin Fine ◽  
Donald Homa
Keyword(s):  
Fuzzy Logic

Continuous Estimation of CO2 Production during Exercise

1997 ◽  
Vol 36 (04/05) ◽  
pp. 368-371
Author(s):  
R. Soma ◽  
Y. Yamamoto
Keyword(s):  
Fuzzy Logic ◽  
Steady State ◽  
Infusion Rate ◽  
Feedback System ◽  
Whole Body ◽  
Co2 Production ◽  
Cycle Exercise ◽  
Continuous Estimation ◽  
Breath Measurement ◽  
13Co2 Enrichment

Abstract.A new method was developed for continuous isotopic estimation of human whole body CO2 rate of appearance (Ra) during non-steady state exercise. The technique consisted of a breath-by-breath measurement of 13CO2 enrichment (E) and a real-time fuzzy logic feedback system which controlled NaH13CO3 infusion rate to achieve an isotopic steady state. Ra was estimated from the isotope infusion rate and body 13CO2 enrichment which was equal to E at the isotopic steady state. During a non-steady state incremental cycle exercise (5 w/min or 10 w/min), NaH13CO3 infusion rate was successfully increased by the action of feedback controller so as to keep E constant.

Modified fuzzy-based greedy routing protocol for VANETs

2020 ◽  
Vol 39 (6) ◽  
pp. 8357-8364
Author(s):  
Thompson Stephan ◽  
Ananthnarayan Rajappa ◽  
K.S. Sendhil Kumar ◽  
Shivang Gupta ◽  
Achyut Shankar ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Routing Protocol ◽  
Intelligent Transportation Systems ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
Research Area ◽  
Transportation Systems ◽  
Delivery Ratio ◽  
Greedy Routing ◽  
Hoc Networks

Vehicular Ad Hoc Networks (VANETs) is the most growing research area in wireless communication and has been gaining significant attention over recent years due to its role in designing intelligent transportation systems. Wireless multi-hop forwarding in VANETs is challenging since the data has to be relayed as soon as possible through the intermediate vehicles from the source to destination. This paper proposes a modified fuzzy-based greedy routing protocol (MFGR) which is an enhanced version of fuzzy logic-based greedy routing protocol (FLGR). Our proposed protocol applies fuzzy logic for the selection of the next greedy forwarder to forward the data reliably towards the destination. Five parameters, namely distance, direction, speed, position, and trust have been used to evaluate the node’s stability using fuzzy logic. The simulation results demonstrate that the proposed MFGR scheme can achieve the best performance in terms of the highest packet delivery ratio (PDR) and minimizes the average number of hops among all protocols.

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