Article
Computer Science, Information Systems
Mohammad Tabasi, Ali Asghar Alesheikh, Mohsen Kalantari, Elnaz Babaie, Abolfazl Mollalo
Summary: The study focused on modeling the spatial variation in COVID-19 prevalence in rural districts of Golestan province in Iran using the ANFIS model. It found that combining PCA with ANFIS significantly improved model accuracy, with migration rate, employment rate, number of days with rainfall, and residential apartment units being the most important factors.
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
(2022)
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
Chemistry, Multidisciplinary
Juan Liu, Xuewei Bai
Summary: The carbonation of reinforced concrete is a significant factor that reduces the service performance of concrete structures. In order to mitigate the corrosion caused by carbonation, it is necessary to predict the carbonation depth. The PCA-ANFIS model, combining principal component analysis (PCA) and adaptive network-based fuzzy inference system (ANFIS), is proposed as an accurate tool for predicting the carbonation of reinforced concrete.
APPLIED SCIENCES-BASEL
(2023)
Article
Automation & Control Systems
Kiarash Keyvan, Mahmoud Reza Sohrabi, Fereshteh Motiee
Summary: This study developed a simple, fast, accurate, and inexpensive chemometrics-assisted spectrophotometric method for the simultaneous determination of sofosbuvir and velpatasvir. Fuzzy inference system and adaptive neuro-fuzzy inference system along with principal component analysis were used for the analysis, resulting in satisfactory results. These methods can be useful for the simultaneous estimation of binary and ternary mixtures in quality control of pharmaceutical formulations.
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
(2022)
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
Energy & Fuels
Muhammad Abbas, Duanjin Zhang
Summary: This paper introduces an intelligent PV fault detection system using the ANFIS methodology, trained with GP and SC strategies. The ANFIS SC approach outperformed the ANFIS GP approach in predicting and classifying PV system faults with high accuracy and performance metrics.
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
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
Chemistry, Analytical
Abror Buriboev, Azamjon Muminov
Summary: The analysis of resource consumption in dynamic systems is crucial for system design and deployment decisions. This study proposes a simplified evaluation method using components' utilization and linguistic values, with the help of the adaptive neuro-fuzzy inference system (ANFIS) model and fuzzy set theory. It examines the impact of memory, cache, storage, and bus on CPU performance to determine the state of the computer system.
Article
Geosciences, Multidisciplinary
Ruhhee Tabbussum, Abdul Qayoom Dar
Summary: This research explores the capability of the adaptive neuro-fuzzy inference algorithm architecture to simulate floods, using multiple statistical performance evaluators to assess the established models and evaluating their validity and predictive power through flood occurrence prediction. The best performability was found in an ANFIS model created with a hybrid training algorithm, indicating the potential use of the model for flood prediction.
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
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
Computer Science, Artificial Intelligence
Ozlem Uzun Araz, Emine Kemiklioglu, Berfin Gurboga
Summary: This study evaluates the application of an ANFIS model in detecting toxic gas vapor. Experimental data using lyotropic cholesteric crystal as a sensor were used to establish the model, and ANFIS and GP were used for model partitioning and prediction. The results show that the ANFIS-GP5 model has high accuracy in predicting the response to toxic gas vapor.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Environmental Sciences
Ruhhee Tabbussum, Abdul Qayoom Dar
Summary: This study explores the potential of AI computing paradigm to model stream flow and develops nine different flood prediction models using AI algorithms. The ANFIS model developed with a hybrid training algorithm shows the best performance, indicating the potential of AI algorithm-based models for flood forecasting. The research reveals the significance of combining multiple inputs and AI algorithms in predicting floods, providing useful techniques for Flood Control Departments globally.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2021)
Article
Chemistry, Multidisciplinary
Hai-Bang Ly, Lu Minh Le, Huan Thanh Duong, Thong Chung Nguyen, Tuan Anh Pham, Tien-Thinh Le, Vuong Minh Le, Long Nguyen-Ngoc, Binh Thai Pham
APPLIED SCIENCES-BASEL
(2019)
Article
Mechanics
Do Quang Chan, Pham Van Hoan, Nguyen Thoi Trung, Le Kha Hoa, Duong Thanh Huan
Summary: This paper investigates the nonlinear buckling and post-buckling of sandwich cylindrical panels with non-uniform porous core and functionally graded face sheets subjected to axial compression load. Governing equations are derived based on the Donnell shell theory with von Karman geometrical nonlinearity, and comparisons with available results show good agreements to validate the proposed method. Various panel geometrical characteristics, boundary conditions, porosity parameters, the thickness of the porous core, and material parameters are investigated for their effects.
Article
Engineering, Civil
Huan Thanh Duong, Hieu Chi Phan, Tien-Thinh Le, Nang Duc Bui
Article
Engineering, Multidisciplinary
Hieu Chi Phan, Tien-Thinh Le, Nang Duc Bui, Huan Thanh Duong, Tiep Duc Pham
Summary: This study establishes an extensive finite element database with 772 samples through finite element analysis, and develops an explicit empirical model for predicting the bending capacity of buried pipes. The model achieves high accuracy by optimizing design variables and reduction factors.
INTERNATIONAL JOURNAL OF PRESSURE VESSELS AND PIPING
(2021)
Article
Computer Science, Artificial Intelligence
Huan Thanh Duong, Hieu Chi Phan, Tu Minh Tran, Ashutosh Sutra Dhar
Summary: This paper proposes a data-driven model using artificial neural network (ANN) for predicting the critical buckling load of functionally graded material (FGM) plates as an alternative to complex analytical methods. By developing an ANN model with sufficient training, the study shows that the critical buckling load can be accurately determined by investigating the stochastic characteristic of input parameters.
NEURAL COMPUTING & APPLICATIONS
(2021)
Article
Engineering, Multidisciplinary
Tran Huu Quoc, Duong Thanh Huan, Hoang Thu Phuong
Summary: This paper investigates the vibration characteristics of rotating functionally graded circular cylindrical shells, establishes a system of motion equations considering various factors, and conducts numerical studies to analyze the effects of these factors on the vibration response.
INTERNATIONAL JOURNAL OF PRESSURE VESSELS AND PIPING
(2021)
Article
Computer Science, Artificial Intelligence
T. H. Duong, T-T Le, S. X. Nguyen, M. Le
Summary: This study develops an Adaptive-Neuro-Fuzzy-Inference-System (ANFIS) model for predicting the ultimate load of rectangular concrete-filled steel tubular structural members. The model outperforms other machine learning models, as indicated by various quality metrics, and shows improvement compared to previous research results.
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2022)
Article
Engineering, Mechanical
Nguyen Tien Khiem, Duong Thanh Huan, Tran Trung Hieu
Summary: The frequency response function of a structure is an important attribute for vibration-based damage detection in structural health monitoring. This study investigates the use of a cracked FGM (Functionally Graded Material) beam bonded with a piezoelectric layer as a distributed sensor under a moving load. The results show that the amplitudes of mechanical and electrical responses are strongly sensitive to cracks, making them viable indicators for crack detection in FGM beams.
JOURNAL OF VIBRATION ENGINEERING & TECHNOLOGIES
(2023)
Article
Computer Science, Interdisciplinary Applications
Van-Hai Nguyen, Tien-Thinh Le, Hoanh-Son Truong, Huan Thanh Duong, Minh Vuong Le
Summary: This study proposes a rapid and robust machine-learning model for predicting the volumetric error of a five-axis machine tool. Several machine learning models are compared to find the best model for the problem at hand. The results show that the models proposed in this paper are more effective than those in the literature. The SVR Regression model has proven to be the best, with an RMSE of 0.03246 mm.
INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING
(2023)
Article
Construction & Building Technology
T. H. Duong, T. -T. Le, M. V. Le
Summary: This paper proposes a support vector machine (SVM) model for predicting the axial capacity of composite concrete-filled steel tubular (CFST) columns with different cross-section shapes. The model is trained and validated using a large database of test results, and its performance is evaluated using various performance indicators. The paper also includes sensitivity analysis, study of the influence of different factors, and comparison with existing literature.
INTERNATIONAL JOURNAL OF STEEL STRUCTURES
(2023)
Article
Engineering, Multidisciplinary
Abraham Mensah, Srinivas Sriramula
Summary: This paper proposes a pathway for developing efficient performance functions to evaluate the probability of failure for interacting pipeline corrosion clustering defects using a probabilistic finite element-based reliability method. The framework reduces computational cost and offers informed decision-making on risk and maintenance management.
INTERNATIONAL JOURNAL OF PRESSURE VESSELS AND PIPING
(2024)
Article
Engineering, Multidisciplinary
Baozhu Zhang, Wenchun Jiang, Yun Luo, Wei Peng, Yingjie Qiao
Summary: This paper studies the distribution of residual stress in thick wall girth welds using narrow-gap welding. The study finds that the heat input, wall thickness, radius thickness ratio, and number of welding passes have an effect on residual stress. A model for the distribution of welding residual stress through the wall thickness is proposed, and its results are in good agreement with finite element calculation results.
INTERNATIONAL JOURNAL OF PRESSURE VESSELS AND PIPING
(2024)
Article
Engineering, Multidisciplinary
Stefan Culafic, Darko Bajic, Tasko Maneski
Summary: This paper presents experimental research on a branch model conducted in laboratory conditions. The study verifies the linear relationship between stress and internal pressure in the field of elasticity and reveals the occurrences when stresses exceed the yield strength of the branch material, such as plastic deformations of the branch model. The research also defines the dependence of stress on internal pressure in both the field of elasticity and the zone of residual stresses.
INTERNATIONAL JOURNAL OF PRESSURE VESSELS AND PIPING
(2024)
Article
Engineering, Multidisciplinary
Wenchun Jiang, Wenlu Xie, Xinyue Qi, Yangguang Deng, Yu Wan, Xuefang Xie
Summary: Various types of solid-state phase transformations (SSPT) occur during the SA508 steel welding process, leading to complex microstructure distribution and significant influence on residual stress distribution. To better control microstructure and residual stress, optimization of process parameters related to welding thermal cycles is necessary.
INTERNATIONAL JOURNAL OF PRESSURE VESSELS AND PIPING
(2024)