Article
Mathematics
Li-Peng Shao, Jia-Jia Chen, Lu-Wen Pan, Zi-Juan Yang
Summary: This paper proposes a robust optimization model based on credibility theory to address the uncertainty challenge faced by a distributed generator in an electricity market. By introducing option contracts and bilateral contracts, the electricity transaction cost of the distributed generator can be reduced.
Article
Energy & Fuels
Bohong Wang, Qinglai Guo, Tianyu Yang, Luo Xu, Hongbin Sun
Summary: This paper emphasizes the inherent uncertainty in decision-making in energy transactions and proposes a relationship between reducing uncertainty and increasing profit through data acquisition and sharing. It also discusses the role of data products in reducing uncertainty and the corresponding data valuation methods, demonstrating the effectiveness of theoretical results through a case study.
Article
Computer Science, Information Systems
Wei Mei, Limin Liu, Jian Dong
Summary: Randomness and fuzziness are two fundamental types of uncertain phenomena that can be handled by probability theory and possibility theory respectively. The integration of these two uncertainty systems through a hybrid sigma-max mechanism allows for the direct fusion of heterogeneous information, providing a more comprehensive approach to handling uncertainty in practical information processing scenarios. By jointly describing random variables and fuzzy variables, a hybrid distribution of probability and possibility can be achieved, allowing for improved inference and target recognition in scenarios involving both randomness and fuzziness.
INFORMATION SCIENCES
(2021)
Article
Computer Science, Artificial Intelligence
Manish Aggarwal
Summary: A general entropy framework is proposed, which redefines existing fuzzy entropy functions and extends them to the probabilistic-fuzzy domain, demonstrating their usefulness in a real world case study.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Yong Ren, Zhijia Zhao, Choon Ki Ahn, Han-Xiong Li
Summary: This study proposes an adaptive fuzzy control method for an axially moving slung-load cable system (AMSLCS) of a helicopter. The method effectively handles actuator fault, system uncertainty, and disturbances with the aid of a fuzzy logic system (FLS) and a novel adaptive fuzzy control law.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Zhao-Xu Yang, Hai-Jun Rong, Plamen Angelov, Zhi-Xin Yang
Summary: This article proposes a novel incremental statistical evolving fuzzy inference system (SEFIS) that can update system parameters and evolve structure components in the presence of non-Gaussian noises. The system generates new rules based on statistical model sufficiency and deletes inactive rules to improve performance and accuracy. Additionally, an adaptive maximum correntropy extend Kalman filter is introduced to update parameters and enhance robustness. Simulation studies demonstrate that the proposed SEFIS has faster learning speed and higher accuracy compared to existing evolving fuzzy systems (EFSs) in both noise-free and noisy conditions.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Zhaowen Li, Zhihong Wang, Qingguo Li, Pei Wang, Ching-Feng Wen
Summary: This article focuses on uncertainty measurement for a fuzzy set-valued information system, involving the introduction of FSVIS, calculation of the distance between information values, acquisition of tolerance relation, and description of information structure. The statistical effectiveness analysis verifies the validity of these uncertainty measures, providing insights into the intrinsic properties of uncertainty in FSVIS.
INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS
(2021)
Article
Computer Science, Information Systems
Noel Khan, David A. Elizondo, Lipika Deka, Miguel A. Molina-Cabello
Summary: The paper discusses the role of system monitors and the potential of fuzzy logic in predicting and correcting system failures, emphasizing the importance of failure detection and prevention in improving the system's non-functional qualities and avoiding losses.
Editorial Material
Computer Science, Artificial Intelligence
Dongrui Wu, Ruimin Peng, Jerry M. M. Mendel
Summary: Fuzzy sets are used to model linguistic uncertainties and perform inferences based on linguistic rulebases. They have been successfully applied in various applications, especially controls. This short paper introduces newcomers to the basics of type-1 and interval type-2 fuzzy sets and systems. The online full paper at IEEE Xplore provides detailed examples and interactive components for hands-on exploration.
IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE
(2023)
Article
Engineering, Multidisciplinary
Shabir Ahmad, Aman Ullah, Ali Akgul, Thabet Abdeljawad
Summary: This article extends the fractional third order dispersive PDE under singular and non-singular fractional operators using the notion of fuzziness. It investigates fuzzy dispersive PDEs in different dimensions under different fractional operators and provides general algorithm and numerical results. The numerical results confirm the generalized nature of solutions in the fuzzy sense compared to fractional-order solutions.
ALEXANDRIA ENGINEERING JOURNAL
(2021)
Article
Mathematics
Xin Wang, Seyed Mehdi Abtahi, Mahmood Chahari, Tianyu Zhao
Summary: An adaptive neuro-fuzzy integrated system (ANFIS) was developed for satellite attitude estimation and control. The performance of the proposed ANFIS controller was compared to the optimal PID controller, and the results showed that the ANFIS controller outperformed the PID controller in terms of time and smoothness.
Article
Computer Science, Interdisciplinary Applications
Zongli Dai, Sandun C. Perera, Jian-Jun Wang
Summary: The COVID-19 outbreak has increased the demand for ICUs/wards and created uncertainty in hospital demand dynamics. Hierarchical diagnosis and treatment systems (HDTS) with high- and low-level hospitals have advantages in managing elective surgery scheduling during the pandemic, as postoperative recovery patients can be transferred to low-level hospitals to alleviate resource shortages. However, the cost and benefit tradeoff of patient transfers within an HDTS is challenging due to factors such as patient condition, transfer time, and transfer hospital. This research develops a fuzzy scheduling model and an efficient hybrid algorithm to address this tradeoff and optimize patient transfers in an HDTS.
COMPUTERS & OPERATIONS RESEARCH
(2023)
Article
Construction & Building Technology
Mengxue Guo, Hua Huang, Chunliang Xue, Min Huang
Summary: This paper proposes a fuzzy global seismic vulnerability analysis framework for RC structures, considering stochastic uncertainty and epistemic uncertainty. The framework utilizes Monte Carlo simulation and OpenSeesPy to simulate the impact of these uncertainties. The results show that the framework accurately captures the global vulnerability, influenced by both stochastic and epistemic uncertainties. The study highlights the importance of considering these uncertainties in design, decision-making, and post-earthquake rehabilitation.
JOURNAL OF BUILDING ENGINEERING
(2022)
Article
Computer Science, Theory & Methods
Razieh Abdollahipour, Nasrin Eisaabadi, Khosro Khandani
Summary: This paper examines uncertain fuzzy continuous time linear systems and proposes a state feedback design and stability guarantee method using fuzzy eigenvalues placement. The proposed method can be applied to practical systems and ensures closed-loop stability. The validity of the theoretical results is verified through practical simulation examples.
FUZZY SETS AND SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Songtao Zhang, Yi Cui
Summary: This article investigates how to effectively manage dynamic working capital in uncertain supply chain systems, by introducing fuzzy control theory and designing a robust financing strategy to suppress the impact of uncertainties and reduce financing costs.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2021)
Article
Agriculture, Dairy & Animal Science
Luana Possari Maziero, Marcelo George Mungai Chacur, Camila Pires Cremasco, Fernando Ferrari Putti, Luis Roberto Almeida Gabriel Filho
Summary: This study aims to develop a mathematical model based on fuzzy logic to provide a bovine fertility score based on the evaluation of animal semen characteristics. The model is able to gradually classify semen samples as suitable and indicate which animals are in better conditions, offering a useful tool for livestock producers and managers.
Article
Agricultural Engineering
Luis R. A. Gabriel Filho, Josue F. Silva Junior, Camila P. Cremasco, Angela de Souza, Fernando F. Putti
Summary: This study aims to verify the effect of saline water on biometric variables of pumpkin crop using a fuzzy rules system. It was observed that salinity negatively affects the growth parameters of pumpkin crop. The developed mathematical model was found to be efficient for this evaluation.
ENGENHARIA AGRICOLA
(2022)
Article
Agricultural Engineering
Fernando F. Putti, Camila P. Cremasco, Josue F. Silva Junior, Luis R. A. Gabriel Filho
Summary: The study analyzed the effects of reusing saline water on radish cultivation and developed a fuzzy logical mathematic model for producers to evaluate production. Results showed that salinity reduced fresh and dry matter of the radish bulb and affected ratings throughout the cultivation cycle. The fuzzy model helped in analyzing experimental data and performing simulations to infer points not experimentally determined.
ENGENHARIA AGRICOLA
(2022)
Article
Agronomy
Luis Claudio Lopes Andrade, Fernando Ferrari Putti, Camila Pires Cremasco, Luis Roberto Almeida Gabriel Filho
Summary: This study evaluated the hydroponic cultivation of lettuce, watercress, and chicory using a fertilizer developed from vinasse. The results showed that vinasse has a positive effect on plant growth and development, and the hydroponic solution with vinasse can be a sustainable way to reuse it.
Article
Agriculture, Multidisciplinary
Mauricio Bruno Prado da Silva, Valter Cesar De Souza, Caroline Pires Cremasco, Marcus Vinicius Contes Calca, Cicero Manoel Dos Santos, Camila Pires Cremasco, Luis Roberto Almeida Gabriel Filho, Sergio Augusto Rodrigues, Joao Francisco Escobedo
Summary: Machine learning techniques were used to model reference evapotranspiration based on climatic data from automatic weather stations in the State of Sao Paulo, Brazil. The EToMLP4 model showed the best performance, indicating its potential for estimating reference evapotranspiration.
Review
Green & Sustainable Science & Technology
Natalia Dadario, Luis Roberto Almeida Gabriel Filho, Camila Pires Cremasco, Felipe Andre dos Santos, Maria Cristina Rizk, Mario Mollo Neto
Summary: Inadequate disposal of Municipal Solid Waste (MSW) is a major environmental issue today. Incineration, also known as mass burning, is a controversial but widely used method for MSW disposal in Europe, Japan, the US, and China. This article reviews the global progress of waste-to-energy recovery and mass-burning technologies, focusing on the Brazilian context. The study examines the benefits, impacts, and regulatory frameworks of these technologies, and provides insights into the electricity generation capacity and licensing processes of Waste-to-Energy Plants (WtEPs) in Sao Paulo state.
Article
Horticulture
Fernando Ferrari Putti, Eduardo Festozo Vicente, Prinscilla Pamela Nunes Chaves, Luis Paulo Benetti Mantoan, Camila Pires Cremasco, Bruna Arruda, Juliane Cristina Forti, Josue Ferreira Silva, Marcelo Campos, Andre Rodrigues dos Reis, Luis Roberto Almeida Gabriel
Summary: Climate change is affecting vegetable production through changes in rainfall patterns and soil moisture. To mitigate this, technologies such as magnetically treated water are being explored to maintain ideal soil moisture for plant uptake. This study investigated the effect of magnetically treated water on lettuce biomass and nutrient uptake, finding that it improved nitrogen assimilation and resulted in higher agronomical characteristics and yield.
Article
Agricultural Engineering
Luis R. A. Gabriel Filho, Cristhian A. Rodrigues, Maria C. R. Halmeman, Sandra C. de Oliveira
Summary: This study aims to evaluate the energy efficiency of a Brazilian agribusiness company's meat retail sector using PROCEL energy evaluation methods. By using PROCEL's RTQ-C manual, conducting literature research on energy issues, and understanding the company's environment, the commercial establishment received a B classification index, which is considered good but needs improvement in areas such as air conditioning for better energy efficiency. Therefore, improving these areas can lead to economic and environmental benefits for the company, and this research serves as a basis for evaluating energy efficiency in other companies in the same sector.
ENGENHARIA AGRICOLA
(2023)
Article
Agricultural Engineering
Luis R. A. Gabriel Filho, Golbery R. O. Rodrigueiro, Alexsandro O. da Silva, Antonio V. R. de Almeida, Camila P. Cremasco
Summary: This study aims to evaluate the neuro-fuzzy inference method as a decision support for irrigated coriander cultivation. The experiment was conducted in two cultivation cycles in Pentecoste-CE, Brazil, and the results showed that the best results occurred at 55% irrigation depth and a range of 40 to 50% of mulch in the first cycle, while in the second cycle, the water consumption was reduced by 50 to 80%. The neuro-fuzzy model could be a viable option for decision-making in irrigated crops in semi-arid regions.
ENGENHARIA AGRICOLA
(2023)
Review
Environmental Sciences
Stephen Kunihiro, Juliana Ribeiro da Silva Vernasque, Celso da Silva, Marcela Facina dos Santos, Camila Pires Cremasco, Luis Roberto Almeida Gabriel Filho
Summary: This study demonstrates the effectiveness of biomedical interventions in addressing obesity, diabetes, and hypertension (NCDs). However, it highlights the scarcity of innovative and intersectoral actions in combating and preventing these diseases.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
(2022)
Article
Agricultural Engineering
Evanize R. Castro, Joao C. C. Saad, Luis R. A. Gabriel Filho
Summary: This study used fuzzy linear programming to find optimal solutions for minimizing the equivalent annual cost of micro-irrigation systems on sloping terrains. By increasing the use of 50mm pipes, it was found that fuzzy linear programming can provide better solutions.
ENGENHARIA AGRICOLA
(2022)
Article
Environmental Sciences
Bruno Cesar Goes, Renato Jaqueto Goes, Camila Pires Cremasco, Luis Roberto Almeida Gabriel Filho
Summary: This study aimed to analyze the effects of nitrogen on sorghum and millet crops used as cover crops under different nitrogen levels on dry matter production variables. Triangular fuzzy modeling showed the best statistical parameters in comparison to the Gaussian fuzzy model and second-degree polynomial regression. However, the Gaussian model was found to be more consistent with the agronomic reality due to smoothing of the curve over the data set.
MODELING EARTH SYSTEMS AND ENVIRONMENT
(2022)
