Article
Automation & Control Systems
Oscar Castillo, Juan R. Castro, Patricia Melin
Summary: This article proposes a mathematical definition for interval type-3 fuzzy sets, aiming to construct the theory needed for building interval type-3 fuzzy systems. The authors argue that type-2 fuzzy logic outperforms type-1 in situations with uncertainty, dynamics, or nonlinearity, and advocate exploring the new field of type-3 fuzzy logic. They also demonstrate the potential of interval type-3 in quality control and validate its effectiveness in handling uncertainty through comparison with human expert results.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2022)
Article
Engineering, Multidisciplinary
Slavica Prvulovic, Predrag Mosorinski, Dragica Radosav, Jasna Tolmac, Milica Josimovic, Vladimir Sinik
Summary: This article discusses the process of determining the working temperature of the workpiece in the cutting zone when machining plastic on a lathe. The application and programming of a fuzzy logic controller (FLC) can help maintain the processing temperature of the workpiece below 100 degrees C. Experimental results demonstrate the generation of acceptable temperature values for polytetrafluoroethylene (PTFE), also known as teflon, using the fuzzy logic controller.
AIN SHAMS ENGINEERING JOURNAL
(2022)
Article
Geochemistry & Geophysics
Hyunggu Jun, Yongchae Cho
Summary: In this study, a machine learning-based method for processing time-lapse seismic data is proposed to enhance repeatability and capture accurate seismic information. The method involves steps such as training data construction, uniform manifold approximation, and data augmentation to improve the repeatability of time-lapse seismic data and accurately analyze seismic information.
GEOPHYSICAL JOURNAL INTERNATIONAL
(2021)
Article
Geochemistry & Geophysics
Xintao Chai, Taihui Yang, Hanming Gu, Genyang Tang, Wenjun Cao, Yufeng Wang
Summary: Deep learning has made remarkable progress in geophysics. However, the traditional supervised learning framework faces the problem of limited or unavailable labels in seismic data applications, and it cannot generate physically consistent results. Therefore, we provide an open-source package for geophysics-steered self-supervised learning in seismic deconvolution. Experimental results show that this approach outperforms the traditional trace-by-trace method in terms of accuracy and spatial continuity.
GEOPHYSICAL JOURNAL INTERNATIONAL
(2023)
Article
Geochemistry & Geophysics
Hyunggu Jun, Yongchae Cho
Summary: A machine learning-based time-lapse seismic data processing method is proposed, utilizing convolutional autoencoder for feature analysis and data augmentation to enhance data repeatability and accuracy in target change analysis.
GEOPHYSICAL JOURNAL INTERNATIONAL
(2022)
Article
Automation & Control Systems
Ihsan Erozan, Emre Ozel, Damlanur Erozan
Summary: For people who spend a long time indoors during the day, it is crucial to have ergonomically designed environments that provide comfort. This study proposes a two-stage system using type-2 fuzzy logic for the ergonomic control of indoor environments. Through measurements of temperature, humidity, and carbon dioxide levels, the proposed control structure was modeled using both type-1 and type-2 fuzzy logic systems. The results showed that the type-2 fuzzy logic system provided better interpretations for ergonomic control in extremely fuzzy environments.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Computer Science, Artificial Intelligence
Xiangyue Ma, Jindong Xu, Qiangpeng Chong, Shifeng Ou, Haihua Xing, Mengying Ni
Summary: In this paper, the authors propose a new collaborative neural network structure (FCUnet) to solve the refined segmentation of high-resolution remote sensing images (HRRS). They design a fuzzy U-Net classification network to obtain effective feature information and introduce the fuzzy logic unit to handle the ambiguity and uncertainty of HRRS. The authors also incorporate conditional random field (CRF) at the end of FCUnet to optimize the image segmentation results. Experimental results demonstrate the superior performance of FCUnet in refined segmentation and generalization ability compared to state-of-the-art methods.
IET IMAGE PROCESSING
(2023)
Article
Computer Science, Information Systems
Sumit Kushwaha
Summary: SAR is a self-illuminating imaging method that produces high-resolution images in all weather conditions. However, SAR images are distorted by speckle noise, and this study proposes a despeckling approach based on non-subsampled contourlet transform.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Chemistry, Analytical
Paolo Brambilla, Chiara Conese, Davide Maria Fabris, Paolo Chiariotti, Marco Tarabini
Summary: Quality inspection in industrial production is benefiting from the combination of vision-based techniques and artificial intelligence algorithms. This paper discusses the defect identification problem for circularly symmetric mechanical components and compares the performances of a standard algorithm with a Deep Learning (DL) approach. The standard algorithm provides better results in terms of accuracy and computational time, but DL achieves high accuracy in identifying damaged teeth. The possibility of extending the methods and results to other circularly symmetrical components is also analyzed and discussed.
Article
Computer Science, Artificial Intelligence
Poria Pirozmand, Kimia Rezaei Kalantari, Ali Ebrahimnejad, Homayun Motameni
Summary: This study aims to identify the importance of each feature according to user's opinion in every feedback stage through weighted feature vector, rough theory and fuzzy logic, in order to achieve higher accuracy in image quality retrieval.
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Enrique Brazalez, Hermenegilda Macia, Gregorio Diaz, Maria-Teresa Baeza-Romero, Edelmira Valero, Valentin Valero
Summary: This study presents a decision support system called FUME, which processes real-time data to provide recommendations for reducing urban air pollution. The system combines fuzzy logic and complex event processing technology to improve the decision-making process by considering environmental conditions and providing action recommendations for different sources of pollution.
APPLIED SOFT COMPUTING
(2022)
Article
Physics, Multidisciplinary
V. Ramani Bai, A. Chun Kit, G. Kangadharan, R. Gopinath, P. Varadarajan, A. J. Hao
Summary: Water quality has become a global concern due to rapid development, especially in Malaysia, where poor water management is the primary cause of water quality problems. Research aims to identify the causes of infractions, detect dangerous germs, and develop tests for violations in water treatment plants and distribution systems. Disinfecting treated water safely and effectively is crucial for protecting human health and preventing waterborne diseases.
EUROPEAN PHYSICAL JOURNAL PLUS
(2022)
Article
Geochemistry & Geophysics
Zhicheng Geng, Zeyu Zhao, Yunzhi Shi, Xinming Wu, Sergey Fomel, Mrinal Sen
Summary: This paper proposes the application of deep learning techniques to automatically construct subsurface velocity models, achieving promising results. By generating pairs of synthetic velocity models and CIG volumes for training, the traditional computational expensive issue in highly nonlinear relationships is successfully addressed.
GEOPHYSICAL JOURNAL INTERNATIONAL
(2021)
Article
Geochemistry & Geophysics
Zhicheng Geng, Zeyu Zhao, Yunzhi Shi, Xinming Wu, Sergey Fomel, Mrinal Sen
Summary: This paper proposes a method using deep learning techniques to automatically construct subsurface velocity models from common-image gather (CIG) volumes. By training a convolutional neural network with pairs of synthetic velocity models and CIG volumes, promising results are achieved on different synthetic data sets. The training performance of several commonly used loss functions is also studied.
GEOPHYSICAL JOURNAL INTERNATIONAL
(2022)
Article
Multidisciplinary Sciences
Oscar Castillo, Patricia Melin
Summary: This paper presents an initial proposal for the utilization of mediative fuzzy logic in control problems. It extends the concept of fuzzy control to mediative fuzzy logic for situations involving two or more control experts, aiming to improve control results by combining their knowledge. The study demonstrates the effectiveness of type-3 mediative fuzzy control in handling uncertainty from noise in the control process.
Article
Agricultural Engineering
Cemil Sungur, Sedat Calisir, Ender Kaya
JOURNAL OF IRRIGATION AND DRAINAGE ENGINEERING
(2016)
Article
Agricultural Engineering
Cemil Sungur, Sedat Calisir, Ender Kaya
JOURNAL OF IRRIGATION AND DRAINAGE ENGINEERING
(2016)
Article
Green & Sustainable Science & Technology
Cemil Sungur
Article
Computer Science, Information Systems
Abdullah Yusefi, Akif Durdu, Muhammet Fatih Aslan, Cemil Sungur
Summary: In this study, deep learning based solutions were proposed for global localization of UAVs, presenting a novel visual-inertial localization framework, and conducting comparisons in terms of accuracy and time efficiency in indoor scenarios.
Proceedings Paper
Computer Science, Information Systems
Cemil Sungur, Haci Bekir Gokgunduz, Adem Alpaslan Altun
FEDERATED CONFERENCE ON COMPUTER SCIENCE AND INFORMATION SYSTEMS, 2014
(2014)
Article
Energy & Fuels
Cemil Sungur, A. Alpaslan Altun, Hakan Terzioglu
ENERGY EDUCATION SCIENCE AND TECHNOLOGY PART A-ENERGY SCIENCE AND RESEARCH
(2012)
Article
Thermodynamics
Cemil Sungur
INTERNATIONAL JOURNAL OF GREEN ENERGY
(2007)
