scholarly journals Prediction of Unconfined Compressive Strength of Microfine Cement Injected Sands Using Fuzzy Logic Method

2021 ◽  
Author(s):  
Eray Yildirim ◽  
Eyubhan Avci ◽  
Nurten Akgün Tanbay
Keyword(s):  
Compressive Strength ◽  
Fuzzy Logic ◽  
Unconfined Compressive Strength ◽  
Injection Pressure ◽  
Coefficient Of Determination ◽  
Rule Base ◽  
Logic Models ◽  
Fuzzy Logic Method ◽  
Microfine Cement ◽  
Logic Method

Abstract In this study, unconfined compressive strength values of sand soil injected with microfine cement were predicted using fuzzy logic method. Mamdani and Sugeno methods were applied in the fuzzy logic models. In addition, a regression analysis was carried out in order to compare these two methods. In the models, water/cement ratio and injection pressure were the input variables, and unconfined compressive strength was the output variable. The dataset includes 427 samples, which were experimentally injected with microfine cement. Predictions for unconfined compressive strength were obtained by creating membership functions and rule base for each input (predictive) parameter in fuzzy logic models. The coefficient of determination (R2) and Mean Square Error (MSE) were used as criteria for evaluating the performance of the developed models. The results suggested that the three applied models (i.e. Mamdani, Sugeno and regression) provided statistically significant results, and these methods could be used in the future prediction-based studies. The results showed that Sugeno model provided the best performance for predicting unconfined compressive strength. It was followed by Mamdani and Regression models, respectively. This study has suggested that the fuzzy logic method can be an alternative to the regression method which traditionally has been used in prediction process.

scholarly journals The Design of Directions and Shot Sound Distance Using Fuzzy Logic Method Based on Raspberry Pi

2021 ◽  
Vol 2 (Oktober) ◽  
pp. 32-41
Author(s):  
Rian Arbianto Prayogo ◽  
Dekki Widiatmoko ◽  
Budi Harijanto
Keyword(s):  
Fuzzy Logic ◽  
Detection System ◽  
Raspberry Pi ◽  
Rule Base ◽  
Inference System ◽  
Input Quantity ◽  
Technological Developments ◽  
Fuzzy Logic Method ◽  
The Republic ◽  
Logic Method

Abstract - The rise of a shooting incident that occurred in the border areas of the Republic of Indonesia is a big loss for the state in terms of personnel. Technological developments can be used as an alternative in the military world to help the role of soldiers so as to reduce personnel losses. This study aims to create a system for detecting the direction and distance of gunshots. This study uses an experimental method. This gunshot detection system also applies the Fuzzy Logic Method which is applied to the Raspberry Pi 4 and Microphone Max 4466 which is expected to detect the direction and distance of gunshots. This Fuzzy Logic method is used as an inference system or decision maker according to the input given. Fuzzy Logic broadly consists of fuzzification, rule base, and defuzzification. Fuzzification is useful for input normalization, so that the input quantity is in accordance with the fuzzy magnitude, namely the value in the range 0 to 1. After that, enter the rule base where in this step, the input set is compared with the rules or provisions of sound decibels so that it can be classified whether the distance and the direction of the captured sound is in the data range that has been programmed, in this step the signal is analyzed how much decibel sound SS2-V1 is by the MAX 4466 sensor. The conclusion is done by defuzzification, so the final result is that the closest distance to a gunshot at 1 meter is 250 Decibels.

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.

scholarly journals Feature Extraction in Six Blocks to Detect and Recognize English Numbers

2021 ◽  
pp. 3790-3803
Author(s):  
Heba Kh. Abbas ◽  
Haidar J. Mohamad
Keyword(s):  
Fuzzy Logic ◽  
Feature Extraction ◽  
Computational Cost ◽  
Absolute Error ◽  
Suggested Method ◽  
Support Vector ◽  
Horizontal Line ◽  
Svm Algorithm ◽  
Fuzzy Logic Method ◽  
Logic Method

    The Fuzzy Logic method was implemented to detect and recognize English numbers in this paper. The extracted features within this method make the detection easy and accurate. These features depend on the crossing point of two vertical lines with one horizontal line to be used from the Fuzzy logic method, as shown by the Matlab code in this study. The font types are Times New Roman, Arial, Calabria, Arabic, and Andalus with different font sizes of 10, 16, 22, 28, 36, 42, 50 and 72. These numbers are isolated automatically with the designed algorithm, for which the code is also presented. The number’s image is tested with the Fuzzy algorithm depending on six-block properties only. Groups of regions (High, Medium, and Low) for each number showed unique behavior to recognize any number. Normalized Absolute Error (NAE) equation was used to evaluate the error percentage for the suggested algorithm. The lowest error was 0.001% compared with the real number. The data were checked by the support vector machine (SVM) algorithm to confirm the quality and the efficiency of the suggested method, where the matching was found to be 100% between the data of the suggested method and SVM. The six properties offer a new method to build a rule-based feature extraction technique in different applications and detect any text recognition with a low computational cost.

scholarly journals Pemetaan Tingkat Kerawanan Longsor Berdasarkan Curah Hujan dan Geologi Menggunakan Metode Fuzzy Logic Di Kecamatan Leupung Kabupaten Aceh Besar

2018 ◽  
Vol 3 (2) ◽  
pp. 434-441
Author(s):  
Rasyid Alkhoir Lubis ◽  
Muhammad Rusdi ◽  
Hairul Basri
Keyword(s):  
Fuzzy Logic ◽  
Data Analysis ◽  
Analysis Data ◽  
Fuzzy Logic Method ◽  
Input Variables ◽  
Logic Method

Abstrak. Penelitian ini bertujuan untuk mengetahui tingkat kerawanan longsor di Kecamatan Leupung Kabupaten Aceh Besar. Penelitian ini dilakukan menggunakan SIG dengan Metode Fuzzy Logic. Curah Hujan dan Geologi sebagai variabel input dan tingkat kerawanan longsor sebagai variabel output metode fuzzy logic. Beberapa tahapan yang dilakukan dalam metode ini antara lain : fuzzyfication, inferensi dan defuzzyfication. Secara umum, tahapan penelitian persiapan, pra analisis data, analisis data dan output.. Penelitian ini dilakukan karena Kecamatan Leupung berbukit, berlereng, tersusun dari material sedimen termasuk batuan pegunungan dan memiliki curah hujan yang lebih tinggi dibandingkan dengan kecamatan lainnya di lingkup Kabupaten Aceh Besar.Hasil penelitian memperoleh hasil bahwa Kecamatan Leupung didominasi dengan tingkat kerawanan longsor kategori rendah dan sedang. Tingkat kerawanan longsor rendah seluas 16.486,01 ha (97,97 %) dan tingkat kerawanan longsor sedang seluas 342,37 ha (2,03 %). Kedua faktor yaitu curah hujan dan geologi saling mempengaruhi sehingga membedakan nilai defuzzyfication serta kelas kerawanan longsor. Abstract. This study aims to determine the level of landslide vulnerability in Leupung District, Aceh Besar District. This research was conducted using GIS with Fuzzy Logic Method. Rainfall and Geology as input variables and landslide vulnerability as output variables fuzzy logic method. Some of the steps performed in this method include: fuzzyfication, inference and defuzzyfication. In general, the stages of preparatory research, pre-data analysis, data analysis and output. This research was conducted because the hilly Leupung District, the slopes, composed of sedimentary materials including mountainous rocks and had higher rainfall compared to other sub-districts in Aceh Besar .The result of this research is that Leupung District is dominated by low and medium category avalanche vulnerability. Low landslide vulnerability of 16,486.01 ha (97.97%) and moderate landslide vulnerability of 342.37 ha (2.03%). Both factors are rainfall and geology influence each other so as to distinguish the defuzzyfication value and the class of landslide vulnerability.

Sign in / Sign up

Export Citation Format

Share Document