scholarly journals Investigation of Critical Gap for Pedestrian Crossing Using Fuzzy Logic System

2020 ◽  
Vol 10 (10) ◽  
pp. 3653 ◽  
Author(s):  
Wafaa Shoukry Saleh ◽  
Maha M A Lashin
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic System ◽  
Transport Infrastructure ◽  
Membership Functions ◽  
Triangular Form ◽  
Critical Gap ◽  
Infrastructure Design ◽  
Input Variables ◽  
Pedestrian Crossing ◽  
Logic System

This paper assesses pedestrian crossing behavior and critical gaps at a two-way midblock crossing location. A critical gap is the shortest gap that a pedestrian accepts when crossing a road. A dataset was collected in 2017 in Edinburgh (UK). The analysis was performed using the fuzzy logic system. The adopted membership function of the fuzzy logic system is of a triangular form since it has a simple and convenient structure. The input variables that are used in the analysis are the number and length of rejected gaps and length of accepted gaps at the crossing location. The output variables are the critical gaps. The results show that assessing critical gap estimation of pedestrians crossing using fuzzy logic is achievable and produces reasonable values that are comparable to values that are reported in the literature. This outcome improves the understanding of pedestrian crossing behavior and could therefore have implications for transport infrastructure design. Further analysis using additional parameters including waiting time and demographic characteristics and alternative forms for membership functions are strongly encouraged.

scholarly journals Model for selecting a route for the transport of hazardous materials using a fuzzy logic system

2021 ◽  
Vol 69 (2) ◽  
pp. 355-390
Author(s):  
Teodora Milošević ◽  
Dragan Pamučar ◽  
Prasenjit Chatterjee
Keyword(s):  
Fuzzy Logic ◽  
Hazardous Materials ◽  
Fuzzy Logic System ◽  
Membership Functions ◽  
Fuzzy Logic Systems ◽  
Input Variables ◽  
Weighting Coefficients ◽  
Consistency Method ◽  
Selection Of ◽  
Logic System

Introduction/purpose: The paper presents a model for the selection of a route for the transport of hazardous materials using fuzzy logic systems, as a type of artificial intelligence systems. The system presented in the paper is a system for assistance in the decisionmaking process of the traffic service authorities when choosing one of several possible routes on a particular path when transporting hazardous materials. Methods: The route evaluation is performed on the basis of five criteria. Each input variable is represented by three membership functions, and the output variable is defined by five membership functions. All rules in a fuzzy logic system are determined by applying the method of weight premise aggregation (ATPP), which allows the formation of a database based on experience and intuition. Based on the number of input variables and the number of their membership functions, the basic base of 243 rules is defined. Three experts from the Ministry of Defense were interviewed to determine the weighting coefficients of the membership functions, and the values of the coefficients were determined using the Full Consistency Method (FUCOM). Results: A user program which enables the practical application of this model has been created for the developed fuzzy logic system. Conclusion: The user platform was developed in the Matlab 2008b software package.

Fuzzy Logic System in Quantifying Human Driving Skill for Human Adaptive Mechatronics

2015 ◽  
Vol 735 ◽  
pp. 304-310 ◽  
Author(s):  
Mohamad Hafis Izran Ishak ◽  
A.W.A. Aziz ◽  
M.F.A.M. Kasai
Keyword(s):  
Computer Simulation ◽  
Fuzzy Logic ◽  
Fuzzy Logic System ◽  
Simulation Software ◽  
Membership Functions ◽  
Human Skill ◽  
Input And Output ◽  
Driving Skill ◽  
Human Skills ◽  
Logic System

Human Adaptive Mechatronic (HAM) is an enhance system for Human Machine System (HMS). Instead of one-way relationship between human and machine, HAM system provides two-way relationship between human and machine in order to assist human and to improve human skills in operating the machine. Driving a car is an example of applications where HAM system can be applied. One of the problems of HAM is to quantify the human skill for operating the machine. Therefore, this paper proposed a method to quantify human driving skill using Fuzzy Logic System (FLS). In order to get the best design of FLS for quantifying human driving skill, twelve designs of FLS were designed and tested using computer simulation software. The best design from all twelve designs is then been compared with other method of quantifying human skill for verification. Results show that the design of membership functions for input and output have big impact to the accuracy of the output.

Fuzzy Logic System for Abnormal Audio Event Detection Using Mel Frequency Cepstral Coefficients

2017 ◽  
Vol 21 (2) ◽  
pp. 205-210
Author(s):  
Cristina P. Dadula ◽  
◽  
Elmer P. Dadios
Keyword(s):  
Fuzzy Logic ◽  
Event Detection ◽  
Fuzzy Logic System ◽  
Membership Functions ◽  
Mel Frequency Cepstral Coefficients ◽  
Average Accuracy ◽  
Audio Event ◽  
Cepstral Coefficients ◽  
Range Of Values ◽  
Logic System

This paper presents a fuzzy logic system for audio event detection using mel frequency cepstral coefficients (MFCC). Twelve MFCC of audio samples were analyzed. The range of values of MFCC were obtained including its histogram. These values were normalized so that its minimum and maximum values lie between 0 and 1. Rules were formulated based on the histogram to classify audio samples as normal, gunshot, or crowd panic. Five MFCC were chosen as input to the fuzzy logic system. The membership functions and rules of the fuzzy logic system are defined based on the normalized histograms of MFCC. The system was tested with a total of 150 minutes of normal sounds from different buses and 72 seconds audio clips abnormal sounds. The designed fuzzy logic system was able to classify audio events with an average accuracy of 99.4%.

A New Hardware Architecture for Fuzzy Logic System Acceleration

2016 ◽  
Vol 12 (2) ◽  
pp. 188-197
Author(s):  
A yahoo.com ◽  
Aumalhuda Gani Abood aumalhuda ◽  
A comp ◽  
Dr. Mohammed A. Jodha ◽  
Dr. Majid A. Alwan
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic System ◽  
Hardware Architecture ◽  
Logic System

Penerapan Logika Samar dalam Peramalan Data Runtun Waktu

2011 ◽  
Vol 3 (2) ◽  
pp. 11-15
Author(s):  
Seng Hansun
Keyword(s):  
Time Series ◽  
Fuzzy Logic ◽  
Time Series Analysis ◽  
Fuzzy Sets ◽  
Fuzzy System ◽  
Time Series Data ◽  
Fuzzy Logic System ◽  
Series Data ◽  
Series Analysis ◽  
Logic System

Recently, there are so many soft computing methods been used in time series analysis. One of these methods is fuzzy logic system. In this paper, we will try to implement fuzzy logic system to predict a non-stationary time series data. The data we use here is Mackey-Glass chaotic time series. We also use MATLAB software to predict the time series data, which have been divided into four groups of input-output pairs. These groups then will be used as the input variables of the fuzzy logic system. There are two scenarios been used in this paper, first is by using seven fuzzy sets, and second is by using fifteen fuzzy sets. The result shows that the fuzzy system with fifteen fuzzy sets give a better forecasting result than the fuzzy system with seven fuzzy sets. Index Terms—forecasting, fuzzy logic, Mackey-Glass chaotic, MATLAB, time series analysis

IMPROVING EIGENSPACE-BASED FUZZY LOGIC SYSTEM USING A LINEAR INTERPOLATION SCHEME FOR SPEECH PATTERN RECOGNITION

2013 ◽  
Vol 37 (3) ◽  
pp. 611-620
Author(s):  
Ing-Jr Ding ◽  
Chih-Ta Yen
Keyword(s):  
Pattern Recognition ◽  
Fuzzy Logic ◽  
Recognition Performance ◽  
Linear Interpolation ◽  
Fuzzy Logic System ◽  
Interpolation Scheme ◽  
Speech Pattern ◽  
Eigen Value ◽  
Target Speaker ◽  
Logic System

The Eigen-FLS approach using an eigenspace-based scheme for fast fuzzy logic system (FLS) establishments has been attempted successfully in speech pattern recognition. However, speech pattern recognition by Eigen-FLS will still encounter a dissatisfactory recognition performance when the collected data for eigen value calculations of the FLS eigenspace is scarce. To tackle this issue, this paper proposes two improved-versioned Eigen-FLS methods, incremental MLED Eigen-FLS and EigenMLLR-like Eigen-FLS, both of which use a linear interpolation scheme for properly adjusting the target speaker’s Eigen-FLS model derived from an FLS eigenspace. Developed incremental MLED Eigen-FLS and EigenMLLR-like Eigen-FLS are superior to conventional Eigen-FLS especially in the situation of insufficient data from the target speaker.

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