scholarly journals Assessment of Quality in Saudi Arabian Roadways

2021 ◽  
pp. 209-219
Author(s):  
Muwaffaq Alqurashi
Keyword(s):  
Fuzzy Logic ◽  
Field Survey ◽  
Saudi Arabian ◽  
Fuzzy Logic System ◽  
Assessment Model ◽  
Approximate Reasoning ◽  
Proposed Model ◽  
Study Results ◽  
The Impact ◽  
Logic System

A new assessment model was developed in this work. The developed model introduced a new approach and reference for assessment factors control the quality in Saudi Arabian roads using the fuzzy logic system. Fuzzy logic system was chosen to be used in this research due to its suitability for uncertain and approximate reasoning that involves human intuitive thinking as well as, it requires a little data to achieve the aim of the proposed model. Furthermore, the fuzzy logic has the ability for combining many effects such as the probability of occurrence and the impact of factors on the quality of roadways construction. The methodology of this research included conducting a field survey with construction practitioners in the field of roadways projects across Saudi Arabia. The proposed model was then evaluated and applied using the collected data from the field survey. The study results proved that the proposed model can be successfully used in the assessment of factors affecting quality in roadways. The major factors that found to be significantly affecting the quality in construction of roadways projects were identified according to their importance as; 1) Change order control; 2) Fluctuation default of Subcontractor; 3) Third party delay 4) Contract dispute results from disagreement. The proposed model is considered as a general model that can be easily adapted and applied to other types of projects.

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.

scholarly journals Antidisturbance Control for AUV Trajectory Tracking Based on Fuzzy Adaptive Extended State Observer

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7084
Author(s):  
Song Kang ◽  
Yongfeng Rong ◽  
Wusheng Chou
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic System ◽  
Entire System ◽  
Actuator Faults ◽  
Extended State ◽  
Parameter Uncertainties ◽  
External Disturbances ◽  
Measurement Noises ◽  
Fuzzy Adaptive ◽  
Logic System

In this paper, an output-feedback fuzzy adaptive dynamic surface controller (FADSC) based on fuzzy adaptive extended state observer (FAESO) is proposed for autonomous underwater vehicle (AUV) systems in the presence of external disturbances, parameter uncertainties, measurement noises and actuator faults. The fuzzy logic system is incorporated into both the observers and controllers to improve the adaptability of the entire system. The dynamics of the AUV system is established first, considering the external disturbances and parameter uncertainties. Based on the dynamic models, the ESO, combined with a fuzzy logic system tuning the observer bandwidth, is developed to not only adaptively estimate both system states and the lumped disturbances for the controller, but also reduce the impact of measurement noises. Then, the DSC, together with fuzzy logic system tuning the time constant of the low-pass filter, is designed using estimations from the FAESO for the AUV system. The asymptotic stability of the entire system is analyzed through Lyapunov’s direct method in the time domain. Comparative simulations are implemented to verify the effectiveness and advantages of the proposed method compared with other observers and controllers considering external disturbances, parameter uncertainties and measurement noises and even the actuator faults that are not considered in the design process. The results show that the proposed method outperforms others in terms of tracking accuracy, robustness and energy consumption.

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