Prediction on Aging of Reconstitutive Clayey Marine Soils Using Fuzzy-Logic

2003 ◽  
Author(s):  
Jorge Sa´nchez Moreno ◽  
Edison Castro Prates de Lima ◽  
Gilberto Bruno Ellwanger
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Rule ◽  
Experimental Tests ◽  
Optimization Method ◽  
Soil Strength ◽  
Evolutionary Strategy ◽  
Rule Base ◽  
Engineering Practice ◽  
Aging Effects ◽  
Effective Normal Stress

This paper presents an application of the fuzzy logic theory for the prediction of the soil strength depth variation due to aging effects. The results of experimental tests with reconstituted clayey soils of the Bay of Campeche in Mexico were used for the fuzzy rule-based system training. The Evolutionary Strategy (ES) was employed as an optimization method for the learning of the Mamdani-type fuzzy rule base. Fuzzy logic provides an easy and transparent method for incorporating common-sense type reasoning. The fuzzy logic model is based on a decision (inference) process that can be better described on a linguistic level using rules with soft facts. In this manner the clay soil strength through the time could be fuzzily predicted as a function of the mean effective normal stress, the time of consolidation and the water content. Illustrative examples showed that the result of prediction seems to be acceptable in engineering practice.

scholarly journals Design of Indoor Room Gas CO and SO2 Detection Based on Microcontroller Using Fuzzy Logic

2019 ◽  
Vol 125 ◽  
pp. 23013
Author(s):  
Slamet Widodo ◽  
M.Miftakhul Amin ◽  
Ahyar Supani
Keyword(s):  
Carbon Monoxide ◽  
Fuzzy Logic ◽  
Fuzzy Rule ◽  
Rule Base ◽  
Motor Speed ◽  
Fuzzy Rule Base ◽  
A Value ◽  
Base Logic ◽  
So2 Gas ◽  
Co Gas

The incidence of poisoning due to carbon monoxide gas arising from drilling activities on the first floor of a building in the Kelapa Gading beauty clinic in Jakarta resulted in 17 people experiencing poisoning. In this study developing a device on the sensor used to detect CO and SO2 gas, in the air of a closed room using gas sensor MQ 135 and MQ 136. The results of testing the CO and SO2 gas gauges using samples of cigarette smoke and sulfur powder using MQ 135 and MQ 136 sensors with fuzzy rule base logic for motor speed to produce CO and SO2 gas, that obtained a value of 0.233 ppm SO2 gas safe conditions and gas input CO with the sensor obtained a value of 0.513 ppm, the condition is safe so that the output is 49.8 ppm, the condition of the fan blower does not rotate. Whereas when the reading value of 5.0 ppm is very concentrated and the CO gas input with the sensor is 13.8 ppm the condition is very concentrated producing an output of 228 ppm the very danger.

Fuzzy logic approach for investigation of microstructure and mechanical properties of Sn96.5-Ag3.0-Cu0.5 lead free solder alloy

2017 ◽  
Vol 29 (4) ◽  
pp. 191-198 ◽  
Author(s):  
Muhammad Aamir ◽  
Izhar Izhar ◽  
Muhammad Waqas ◽  
Muhammad Iqbal ◽  
Muhammad Imran Hanif ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Fuzzy Logic ◽  
Solder Alloy ◽  
Thermal Aging ◽  
Fuzzy Rule ◽  
Rule Base ◽  
Content Type ◽  
Wide Range ◽  
Fuzzy Logic Approach ◽  
Free Solder

Purpose This paper aims to develop a fuzzy logic-based algorithm to predict the intermetallic compound (IMC) size and mechanical properties of soldering material, Sn96.5-Ag3.0-Cu0.5 (SAC305) alloy, at different levels of temperature. The reliability of solder joint in materials selection is critical in terms of temperature, mechanical properties and environmental aspects. Owing to a wide range of soldering materials available, the selection space finds a fuzzy characteristic. Design/methodology/approach The developed algorithm takes thermal aging temperature for SAC305 alloy as input and converts it into fuzzy domain. These fuzzified values are then subjected to a fuzzy rule base, where a set of rules determines the IMC size and mechanical properties, such as yield strength (YS) and ultimate tensile strength (UTS) of SAC305 alloy. The algorithm is successfully simulated for various input thermal aging temperatures. To analyze and validate the developed algorithm, an SAC305 lead (Pb)-free solder alloy is developed and thermally aged at 40, 60 and 100°C temperature. Findings The experimental results indicate an average IMCs size of 5.967 (in Pixels), 19.850 N/mm2 YS and 22.740 N/mm2 UTS for SAC305 alloy when thermally aged at an elevated temperature of 140°C. In comparison, the simulation results predicted 5.895 (in Pixels) average IMCs size, 19.875 N/mm2 YS and 22.480 N/mm2 UTS for SAC305 alloy at 140°C thermally aged temperature. Originality/value From the experimental and simulated results, it is evident that the fuzzy-based developed algorithm can be used effectively to predict the IMCs size and mechanical properties of SAC305 at various aging temperatures, for the first time.

Optimized Fuzzy Logic Control Strategy for Parallel Hybrid Electric Vehicle Based on Genetic Algorithm

2013 ◽  
Vol 274 ◽  
pp. 345-349 ◽  
Author(s):  
Mei Lan Zhou ◽  
Deng Ke Lu ◽  
Wei Min Li ◽  
Hui Feng Xu
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Logic ◽  
Electric Vehicle ◽  
Control Strategy ◽  
Fuzzy Logic Control ◽  
Hybrid Electric Vehicle ◽  
Fuzzy Rule ◽  
Rule Base ◽  
Membership Functions ◽  
Logic Control

For PHEV energy management, in this paper the author proposed an EMS is that based on the optimization of fuzzy logic control strategy. Because the membership functions of FLC and fuzzy rule base were obtained by the experience of experts or by designers through the experiment analysis, they could not make the FLC get the optimization results. Therefore, the author used genetic algorithm to optimize the membership functions of the FLC to further improve the vehicle performance. Finally, simulated and analyzed by using the electric vehicle software ADVISOR, the results indicated that the proposed strategy could easily control the engine and motor, ensured the balance between battery charge and discharge and as compared with electric assist control strategy, fuel consumption and exhaust emissions have also been reduced to less than 43.84%.

scholarly journals Rain Prediction using Fuzzy Logic

2019 ◽  
Vol 9 (1) ◽  
pp. 2796-2799
Keyword(s):  
Fuzzy Logic ◽  
Power System ◽  
Unit Commitment ◽  
Load Forecasting ◽  
Fuzzy Rule ◽  
Conventional Technique ◽  
Rule Base ◽  
Spinning Reserve ◽  
Generation Cost ◽  
Triangular Membership Function

Power system energy management system is observed as the breakthrough element for load forecasting. Load forecasting is advantageous so as to reduce the generation cost, spinning reserve capacity and increase the reliability of power system. The unit commitment, economic allotment of generation preservation schedule is crucial for short term load forecasting (STLF). In the current times, many techniques are being utilized for load forecasting, but Artificial Intelligence Technique (Fuzzy Logic and ANN) provides improved efficiency as in contrast with conventional technique (Regression and Time Series). In this particular paper, the author main purpose is to reduce flood conditions and drought. The main focus of the author is in the prediction of rainfall with the help of wind variation and temperature, speed. The paper represents a technique of STLF using fuzzy logic. Using Mamdani implication the fuzzy rule base is prepared. The software used for this is Matlab Simulink and fuzzy tool box. By using triangular membership function the forecasted results are obtained.

Implementation of a hexapod mobile robot with a fuzzy controller

Robotica ◽  
2005 ◽  
Vol 23 (6) ◽  
pp. 681-688 ◽  
Author(s):  
Makoto Kern ◽  
Peng-Yung Woo
Keyword(s):  
Fuzzy Logic ◽  
Mobile Robot ◽  
Fuzzy Controller ◽  
Robot Navigation ◽  
Fuzzy Rule ◽  
Sensor Data ◽  
Rule Base ◽  
Fuzzy Rule Base ◽  
Different Types ◽  
Autonomous Robot Navigation

Fuzzy logic has features that are particular attractive in light of the problems posed by autonomous robot navigation. Fuzzy logic allows us to model different types of uncertainty and imprecision. In this paper, the implementation of a hexapod mobile robot with a fuzzy controller navigating in unknown environments is presented. The robot, MKIII, interprets input sensor data through the comparison of values in its fuzzy rule base and moves accordingly to avoid obstacles. Results of trial run experiments are presented.

scholarly journals Software Quality Prediction Method Using Fuzzy Logic

2021 ◽  
Vol 12 (11) ◽  
pp. 807-817
Author(s):  
Ritu, Et. al.
Keyword(s):  
Fuzzy Logic ◽  
Software Quality ◽  
Reference Model ◽  
Fuzzy Model ◽  
Prediction Method ◽  
Fuzzy Rule ◽  
Rule Base ◽  
Development Organization ◽  
Soft Computing Techniques

: Software Quality is the key priority of today’s marketplace and software development organization to which a system, technique, or factor meets particular requirements and conditions. Soft computing techniques play a vital role in developing software engineering applications. In this paper, we have identified five parameters: Reliability, Efficiency, Usability, Maintainability, and Portability for accessing the level of quality of software. A fuzzy logic-based intelligent identification methodology has been proposed to access the quality of particular software-based on five parameters. The proposed identification scheme takes these five parameters as input and predicts the quality of the software using the fuzzy rule base which is generated using various studies. As this scheme takes five inputs and each input is divided into three regions i.e. ‘Low’, ‘Medium’, ‘High’ and thus a total of 35 i.e. 243 rules has been generated to analyze the software quality. Furthermore, Mamdani fuzzy model has been used as the reference model. To show the effectiveness of the proposed methodology, simulation results have been performed in MATLAB, which shows that the software's quality closely matches with the actual one.

scholarly journals Fuzzy-based quantification of congestion for traffic control

2021 ◽  
Vol 72 (1) ◽  
pp. 1-8
Author(s):  
Dinh Toan Trinh
Keyword(s):  
Fuzzy Logic ◽  
Traffic Flow ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Fuzzy Rule ◽  
Gradual Transition ◽  
Rule Base ◽  
State Variables ◽  
Study Results ◽  
Traffic Stream

This paper presents a methodology for appraisal of congestion level for traffic control on expressways using fuzzy logic. The congestion level indicates the severity of congestion and is estimated using speed and density, being the basic traffic parameters that describe state of a traffic stream. Formulation of the fuzzy rule base is made based on knowledge on traffic flow theory and engineering judgments. Field data on a segment of the Pan-Island Expressway of Singapore were used to estimate the congestion levels for three scenarios: single input variable (speed or density) and combined input variables (speed and density), represented by congestion level on a [0 1] scale. The results showed that there were big gaps between the congestion levels evaluated based specifically on speed and density alone (single state variable), and the congestion levels estimated from both variables lie in between. Given the uncertainty in traffic data collection and dynamic nature of traffic flow, this indicates that it may be inadequate to evaluate traffic congestion level using a single variable, and the use of both speed and density represent the state of a traffic stream more properly. The study results also show that the fuzzy logic approach provides flexible combination of state variables to obtain the congestion level and to describe gradual transition of traffic state, which is particularly important under the heavy congested conditions.

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