Article
Mathematics, Applied
Aditya Khamparia, Rajat Jain, Poonam Rani, Deepak Gupta, Ashish Khanna, Oscar Castill
Summary: The study aims to design a system for diagnosing COVID-19 using ANFIS, and comparative analysis reveals that ANFIS model outperforms fuzzy systems in accuracy.
APPLIED AND COMPUTATIONAL MATHEMATICS
(2021)
Article
Engineering, Industrial
Choayb Djeddi, Ahmed Hafaifa, Abdelhamid Iratni, Nadji Hadroug, XiaoQi Chen
Summary: The development of new monitoring and diagnostic procedures is essential for modern industry to enhance operational safety and availability. The proposed solution for gas turbine monitoring incorporates an adaptive neural-fuzzy inference system to predict component degradation and achieve high efficiency and reliability.
JOURNAL OF MANUFACTURING SYSTEMS
(2021)
Article
Energy & Fuels
Engin Baker, Secil Varbak Nese, Erkan Dursun
Summary: The essential components of a transformer, including the core, windings, and insulation materials, are in the oil-filled tank, making it challenging to detect faults in these materials within a closed area. Fault diagnosis methods based on Dissolved Gas Analysis (DGA) can predict potential transformer faults and take necessary precautions before they escalate. Despite their accuracy of over 95%, the validity of these fault diagnosis methods is disputed due to limited data used in studies. The success rates and reliability of fault diagnosis methods for transformers, one of the most crucial power system equipment, need to be enhanced. This study presents a hybrid fault diagnosis system utilizing DGA-based methods and Fuzzy Logic. A mathematical approach and Support Vector Machines (SVMs) were employed as decision-making methods in the hybrid system. Experimental tests conducted with 317 real fault datasets associated with transformers demonstrated an accuracy of 95.58% using the mathematical approach and 96.23% using SVMs.
Review
Transportation
Matthew Vechione, Ruey Long Cheu
Summary: This study investigates the adaptation of Fuzzy Inference System (FIS) model for mandatory lane changing decisions and compares its performance with Adaptive FIS (AFIS) and Adaptive Neuro-Fuzzy Inference Systems (ANFIS) models on a test data set. Results suggest that an ANFIS model is recommended for mandatory lane changes due to its higher overall correct decision rate.
JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Multidisciplinary
Francesco Abbondati, Salvatore Antonio Biancardo, Rosa Veropalumbo, Xinqiang Chen, Gianluca Dell 'Acqua
Summary: The study presents a method of modelling runway friction decay using an adaptive neuro-fuzzy inference system (ANFIS). By tuning the membership function parameters of a fuzzy inference system (FIS) using an optimization algorithm, the ANFIS is trained to learn from the given input/output data set and accurately predict the current or future friction of runways. This model provides an effective and efficient forecasting tool for airport managers in making maintenance decisions, without the need for on-site measurements or complex calculations.
Article
Mathematics
Narayan Nayak, Soumya Ranjan Das, Tapas Kumar Panigrahi, Himansu Das, Soumya Ranjan Nayak, Krishna Kant Singh, S. S. Askar, Mohamed Abouhawwash
Summary: In this paper, an adaptive depth and heading control of an autonomous underwater vehicle using the concept of an adaptive neuro-fuzzy inference system (ANFIS) is designed. The proposed control design combines fuzzy logic and neural network control blocks to control the depth and heading angle of the vehicle. Simulations show that the proposed adaptive controller exhibits superior performance compared to other control methods.
Article
Chemistry, Multidisciplinary
Yunhui Luo, Xingguang Wang, Qing Wang, Yehong Chen
Summary: The proposed method utilizes a two-step strategy to cluster training images and train ANFIS models to map image features to illuminant color, achieving reliable illuminant estimation. Experimental results demonstrate the effectiveness of this approach, particularly suitable for implementation in imaging signal processors.
APPLIED SCIENCES-BASEL
(2021)
Article
Engineering, Biomedical
Jianfang Wu, Ruo Hu, Ming Li, Shanshan Liu, Xizheng Zhang, Jun He, Jiaxu Chen, Xiangjun Li
Summary: The study introduces the use of an Adaptive neuro-fuzzy inference system (ANFIS) to diagnose sleep disorders in Traditional Chinese Medicine, achieving an accuracy of 97.6% and 100% correct testing results in 100 medical cases. Comparison tests with six TCM doctors show that the proposed model has the ability of objective reasoning in diagnosing sleep disorders.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2021)
Review
Nanoscience & Nanotechnology
M. Sundar Rajan, Golda Dilip, Nithiyananthan Kannan, M. Namratha, Sankararao Majji, Srikanta Kumar Mohapatra, Tulasi Radhika Patnala, Santoshachandra Rao Karanam
Summary: This article highlights the importance and applications of wireless sensor networks (WSNs) and proposes a method using a neuro-fuzzy optimization model estimator to enhance fault detection. By introducing an ANFIS method, distributed fault nodes can be more effectively identified and classified.
APPLIED NANOSCIENCE
(2021)
Article
Computer Science, Artificial Intelligence
Dheeraj Jutury, Neetesh Kumar, Anuj Sachan, Yash Daultani, Naveen Dhakad
Summary: This study proposes a neuro-fuzzy based intelligent traffic light control system that dynamically generates traffic light phase duration based on real-time heterogeneous traffic load to address traffic congestion.
APPLIED INTELLIGENCE
(2023)
Article
Computer Science, Artificial Intelligence
Kishore Balasubramanian, N. P. Ananthamoorthy
Summary: This study presents a predictive model for detecting neurodegenerative diseases and cancer, focusing on enhancing the efficiency of the adaptive neuro-fuzzy inference system. Experimental results demonstrate the superior performance of the DE-GSO-ANFIS in predicting medical disorders.
NEURAL COMPUTING & APPLICATIONS
(2021)
Article
Telecommunications
P. J. Beslin Pajila, E. Golden Julie, Y. Harold Robinson
Summary: This paper presents a method based on fuzzy inference system and adaptive neuro-fuzzy inference system (ANFIS) for detecting flooding attacks in wireless sensor networks. By using parameters such as energy consumption of node and packet transfer rate, and by calculating metrics like mobility factor, residual energy, and trust factor to elect cluster head, this method can detect flooding attacks more efficiently.
WIRELESS PERSONAL COMMUNICATIONS
(2023)
Article
Optics
Maryam Valizadeh, Zahra Ameri Braki, Rashed Rashidi, Maryam Maghfourian, Ahmad Tabiat Shenas
Summary: The study proposed a method combining spectrophotometry, FIS, and ANFIS as chemometrics for simultaneous determination of SMT and FLU in mixtures and anti-asthma spray. The method showed high accuracy, good recovery rates, and ease of operation compared to HPLC, without the need for time-consuming initial sample preparation steps.
Article
Engineering, Electrical & Electronic
Mehdi Mousavi, Amirreza Mostafavi, Milad Moradi, Ali Chaibakhsh, Mojtaba Kordestani, Mohsen Derakhshanfar, Mehrdad Saif
Summary: This article presents a robust fault detection and isolation (FDI) method for industrial gas turbines. By utilizing a nonlinear feedforward network and a Takagi-Sugeno fuzzy inference system, the proposed approach efficiently deals with nonlinearity and uncertainty, resulting in accurate fault diagnosis and isolation.
IEEE SENSORS JOURNAL
(2023)
Article
Thermodynamics
Boudy Bilal, Kondo Hloindo Adjallah, Alexandre Sava, Kaan Yetilmezsoy, Emel Kiyan
Summary: This study introduces an original adaptive neuro-fuzzy inference system modeling approach to predict wind turbine output power. The proposed model demonstrates higher accuracy in estimating power output compared to existing approaches, showcasing superior forecasting performance and accuracy. Multiple experiments validate the effectiveness and reliability of the proposed methodology.
Article
Engineering, Electrical & Electronic
Mohammad Hadi Andishgar, Eskandar Gholipour, Rahmat-Allah Hooshmand
IET GENERATION TRANSMISSION & DISTRIBUTION
(2018)
Article
Engineering, Electrical & Electronic
Ali Khorasani Ferdavani, Rahmat-Allah Hooshmand, Hoay Beng Gooi
IET GENERATION TRANSMISSION & DISTRIBUTION
(2018)
Article
Green & Sustainable Science & Technology
Mohammad Hossein Oboudi, Rahmat-Allah Hooshmand, Farshad Faramarzi, Mohammad Javad Amroony Boushehri
IET RENEWABLE POWER GENERATION
(2018)
Article
Engineering, Electrical & Electronic
Mohammad Reza Esmaili, Amin Khodabakhshian, Rahmat-allah Hooshmand, Pierluigi Siano
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2018)
Article
Engineering, Electrical & Electronic
Yaser Raeisi-Gahrooei, Amin Khodabakhshian, Rahmat-Allah Hooshmand
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2018)
Article
Green & Sustainable Science & Technology
Rahmat-Allah Hooshmand, Seyyed Mostafa Nosratabadi, Eskandar Gholipour
JOURNAL OF CLEANER PRODUCTION
(2018)
Article
Energy & Fuels
Najmeh Shahidirad, Mehdi Niroomand, Rahmat-Allah Hooshmand
IEEE JOURNAL OF PHOTOVOLTAICS
(2018)
Article
Engineering, Electrical & Electronic
Mohammad Reza Esmaili, Amin Khodabakhshian, Rahmat-allah Hooshmand
INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS
(2018)
Article
Engineering, Electrical & Electronic
Omid Abdoli, Eskandar Gholipour, Rahmat-Allah Hooshmand
ELECTRIC POWER COMPONENTS AND SYSTEMS
(2018)
Article
Thermodynamics
Ebrahim Akbari, Rahmat-Allah Hooshmand, Mehdi Gholipour, Moein Parastegari
Article
Engineering, Electrical & Electronic
Amin Saadat, Rahmat-Allah Hooshmand, Arash Kiyoumarsi, Mahdi Tadayon
IET GENERATION TRANSMISSION & DISTRIBUTION
(2019)
Article
Engineering, Electrical & Electronic
Sasan Ghasemi, Amin Khodabakhshian, Rahmat-allah Hooshmand
IET GENERATION TRANSMISSION & DISTRIBUTION
(2019)
Article
Automation & Control Systems
Masoud Ayoubi, Rahmat-Allah Hooshmand
Article
Green & Sustainable Science & Technology
Mosayeb Bornapour, Rahmat-Allah Hooshmand, Moein Parastegari
Article
Green & Sustainable Science & Technology
Pouya Firouzmakan, Rahmat-Allah Hooshmand, Mosayeb Bornapour, Amin Khodabakhshian
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2019)
