Prediction of drilling rate index from rock strength and cerchar abrasivity index properties using fuzzy inference system

Sakız, Utku; Kaya, Gulhan Ustabas; Yaralı, Olgay

doi:10.1007/s12517-021-06647-w

Cited by 11 publications

(4 citation statements)

References 59 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Salah satu pendekatan FIS yaitu Fuzzy Tsukamoto digunakan dalam penelitian ini [24]. Metode ini dipilih karena kemampuannya dalam menyelesaikan masalah ketidakpastian bersama dengan dua metode lainnya, yaitu probabilitas dan kepastian [25].…”

Section: Pendahuluanunclassified

Optimasi Pengendalian Suhu dan Kelembapan Ruangan di Kota Yogyakarta Menggunakan Metode Fuzzy

2022

View full text Add to dashboard Cite

The dry season is a season where most regions in Indonesia experience an increase in temperature. This unstable temperature can have a negative effect on the human body, so a control device is needed according to the needs of the body automatically. This study focuses on optimizing room temperature and humidity control in Yogyakarta City using a fan duty cycle unit with the Fuzzy Tsukamoto method. The ideal temperature and humidity range is obtained from measurements by the Indonesian Board of Meteorology, Climatology, and Geophysics (BMKG). The purpose of this study is to reduce the hot temperature in the room to normal temperature conditions. The calculation results with a temperature of 28.29°C and humidity of 79.06% resulted in a duty cycle of 40.92%. Based on 50 sample data taken each fan rotated for five minutes showed that the average change in temperature was -0.01°C and humidity -0.032%, meaning it could lower 0.01°C and humidity 0.032% every five minutes. This result is considered inefficient considering the very small changes, so in subsequent studies it is recommended to use technology such as air conditioning as a control tool

show abstract

Section: Pendahuluanunclassified

Optimasi Pengendalian Suhu dan Kelembapan Ruangan di Kota Yogyakarta Menggunakan Metode Fuzzy

2022

View full text Add to dashboard Cite

show abstract

“…The classification of rock mass is not only multi-index, but also the connotation of some incompletely clear evaluation indicators, that is, the classification indicators of rock mass have fuzziness and uncertainty. In response to these characteristics of rock masses, scholars have introduced fuzzy mathematical theory into geotechnical engineering and used fuzzy comprehensive evaluation method to classify rock masses, achieving a series of results [7][8][9][10][11][12]. Sakız [8] uses fuzzy inference system (FIS) to predict drilling rate index (DRI) by using experimental data obtained with 37 different rocks.…”

Section: Introductionmentioning

confidence: 99%

“…In response to these characteristics of rock masses, scholars have introduced fuzzy mathematical theory into geotechnical engineering and used fuzzy comprehensive evaluation method to classify rock masses, achieving a series of results [7][8][9][10][11][12]. Sakız [8] uses fuzzy inference system (FIS) to predict drilling rate index (DRI) by using experimental data obtained with 37 different rocks. Ali [9] proposes an evaluation model based on combining the analytic hierarchy process and the fuzzy Delphi method to evaluate the potential of groundwater inflow.…”

Section: Introductionmentioning

confidence: 99%

Comparison of different scale indicators and verification of rock mass classification

Hong,

Zhou,

et al. 2024

Eng. Res. Express

View full text Add to dashboard Cite

The basic principle of fuzzy comprehensive evaluation is introduced, and different scales of determining indicator weights using Analytic Hierarchy Process (AHP) are summarized and organized. The inspection indicators for evaluating the quality of the judgment matrix are provided. Taking the underground station of a planned intercity railway as the engineering background, a comparative study is conducted on the advantages and disadvantages of the indicator judgment matrix and the comprehensive evaluation results about a n scale, 10/10 ∼ 18/2 scale, 9/9 ∼ 9/1 scale, 1 ∼ 9 scale. The results show that the consistency of the judgment matrix constructed by 1–9 scale is poor and may lead to incorrect evaluation results. The consistency of judgment matrix constructed by a n scale is optimal and the fuzzy comprehensive evaluation results are the closest to the actual situation. It can provide useful guidance for the classification work of surrounding rocks in underground engineering projects.

show abstract

“…One of the fuzzy methods is the Fuzzy Inference System (FIS) approach. This type of fuzzy has three models, one of which is the Tsukamoto model chosen for use in this study [16]. This method was chosen because of its ability to solve uncertainty problems along with two other methods, namely probability and certainty factor [17].…”

Section: Introductionmentioning

confidence: 99%

Temperature and Humidity Control System with Air Conditioner Based on Fuzzy Logic and Internet of Things

Furizal,

Sunardi,

Yudhana

2023

Journal of Robotics and Control

View full text Add to dashboard Cite

Work is an activity that takes most of the day to earn a living and improve the standard of living. During work, many people have to work indoors, which can be a less comfortable and unhealthy place if the temperature and humidity are not well controlled. Unsuitable temperature and humidity conditions can negatively affect the health and comfort of workers, as well as interfere with productivity and work quality. However, the problem that often arises is the difficulty of controlling room temperature and humidity effectively, especially in rooms that are closed and do not get air circulation from outside. Therefore, an effective solution is needed to control the temperature and humidity of the room automatically and remotely via the internet. The contribution of this research is to develop an effective and efficient AC control system in controlling room temperature and humidity using Tsukamoto's Fuzzy Inference System (FIS) method and the Internet of Things (IoT). Tsukamoto's FIS is used to produce AC temperature values in room temperature and humidity control as measured by the DHT22 sensor directly integrated with the ESP32 microcontroller. This control system is monitored remotely using IoT concepts through a mobile application interface. The results of this study show that room temperature can be controlled under normal conditions, with an average change of -1.67°C and an overall average temperature of 25.95°C. While the average humidity is at a value of 80.16% which is included in the Wet set. This suggests that humidity cannot be controlled under normal conditions, so it still requires further development. In addition, it is also necessary to further investigate the effectiveness of the tool in various sizes and more complex layouts of rooms.

show abstract

Prediction of drilling rate index from rock strength and cerchar abrasivity index properties using fuzzy inference system

Cited by 11 publications

References 59 publications

Optimasi Pengendalian Suhu dan Kelembapan Ruangan di Kota Yogyakarta Menggunakan Metode Fuzzy

Optimasi Pengendalian Suhu dan Kelembapan Ruangan di Kota Yogyakarta Menggunakan Metode Fuzzy

Comparison of different scale indicators and verification of rock mass classification

Temperature and Humidity Control System with Air Conditioner Based on Fuzzy Logic and Internet of Things

Contact Info

Product

Resources

About