A5077623520- Fuzzy Logic and Control Systems
- Neural Networks and Applications
- Multi-Criteria Decision Making
- Fuzzy Systems and Optimization
- Parasites and Host Interactions
- Rough Sets and Fuzzy Logic
- Smart Grid Energy Management
- Energy Load and Power Forecasting
- Stock Market Forecasting Methods
- Complex Systems and Time Series Analysis
- Time Series Analysis and Forecasting
- Bayesian Modeling and Causal Inference
- Cognitive Science and Mapping
- Data Management and Algorithms
- Zoonotic diseases and public health
- Metaheuristic Optimization Algorithms Research
- Electric Power System Optimization
- Mobile Ad Hoc Networks
- Complex Network Analysis Techniques
- Topic Modeling
- Optimization and Mathematical Programming
- Machine Learning in Healthcare
- Financial Markets and Investment Strategies
- Data Stream Mining Techniques
- Data Mining Algorithms and Applications
University of Manchester
2016-2025
Changshu Institute of Technology
2024
Jiangsu Institute of Parasitic Diseases
2000-2024
Shenzhen Second People's Hospital
2024
Shanghai Jiao Tong University
2021-2024
Renji Hospital
2021-2024
Nanchang University
2022
Fuzhou University
2020
Hubei University of Medicine
2017-2020
First People's Hospital of Chongqing
2019
With the rapid development of “Internet plus”, medical care has entered era big data. However, there is little research on data (MBD) from perspectives bibliometrics and visualization. The substantive basic aspects MBD itself also rare. This study aims to explore current status through visualization analysis journal papers related MBD. We analyze a total 988 references which were downloaded Science Citation Index Expanded Social databases Web time span was defined as “all years”. GraphPad...
In this paper, the approximation problem of SISO fuzzy systems is discussed. Based on fact that can be represented by a linear combination basic functions (FBF's), we first give systematic and detailed analysis FBF's present five properties FBF's: structure similarity compatibility between membership FBF's, complementarity less fuzziness composition systems. These provide clear picture shape features FBF's. these obtain some systems: property, uniform convergent property universal property....
The hesitant fuzzy linguistic term set (HFLTS) has turned out to be a powerful and flexible technique in representing decision makers' qualitative assessments the processes of making. aim this paper is develop method solve multicriteria making (MCDM) problem within context HFLTS which criteria conflict with each other. To do so, concepts ideal solutions for HFL-MCDM have been introduced. In addition, order represent closeness one solution one, we propose sort measures, such as group utility...
Schistosoma japonicum causes an infection involving humans, livestock, and snails is a significant cause of morbidity in China.We evaluated comprehensive control strategy two intervention villages along Poyang Lake the southeastern province Jiangxi, where annual synchronous chemotherapy routinely used. New interventions, implemented from 2005 through 2007, included removing cattle snail-infested grasslands, providing farmers with mechanized farm equipment, improving sanitation by supplying...
In this paper, the approximation properties of MIMO fuzzy systems generated by product inference are discussed. We first give an analysis basic functions (FBF's) and present several FBF's. Based on these FBF's, we obtain systems: 1) property which reveals mechanism systems; 2) uniform bounds between desired (control or decision) 3) convergent shows that with defined accuracy can always be obtained dividing input space into finer regions; 4) universal approximators extends some previous...
This paper establishes the approximation error bounds for various classes of fuzzy systems (i.e., generated by different inferential and defuzzification methods). Based on these bounds, accuracy is analyzed compared. It seen that class product inference center-average defuzzifier has better properties than min defuzzifier, defuzzified MoM defuzzifier. In addition, it proved can represent any linear multilinear function explicit expressions method are given.
Group decision making is an essential activity in various fields of operations research and management science. This paper focuses on the intuitionistic fuzzy group problem which all experts use preference relations (IFPRs) to express their preferences. To start our discussion, we first propose novel framework clarify difficulties deriving final result accepted by individuals group. Next, a consistency checking method, based multiplicative consistency, developed check each IFPR furnished...
One of the most important and widely faced optimization problems in real applications is interval multiobjective (IMOPs). The state-of-the-art evolutionary algorithms (EAs) for IMOPs (IMOEAs) need a great deal objective function evaluations to find final Pareto front with good convergence even distribution. Further, uncertainty. In this paper, we incorporate several local searches into an existing IMOEA, propose memetic algorithm (MA) tackle IMOPs. At start, IMOEA utilized explore entire...
This paper presents a novel approach to control general nonlinear systems based on Takagi-Sugeno (T-S) fuzzy dynamic models. It is first shown that system can be approximated by generalized T-S model any degree of accuracy compact set. then the stabilization problem solved as robust developed with approximation errors uncertainty term. Based piecewise quadratic Lyapunov function, semiglobal and <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">H</i>...
Fuzzy C-means has been utilized successfully in a wide range of applications, extending the clustering capability K-means to datasets that are uncertain, vague and otherwise hard cluster. This paper introduces C-means++ algorithm which, by utilizing seeding mechanism K-means++ algorithm, improves effectiveness speed C-means. By careful disperses initial cluster centers through data space, resulting approach samples starting representatives during initialization phase. The well spread input...
In this paper, we propose a profit-maximization-based pricing optimization model for the demand response (DR) management with customer behavior learning in context of smart grids. By recognizing different consumption patterns between shiftable and curtailable appliances, two distinguished models are proposed. For appliances whose energy can be shifted from high price periods to low but total is fixed, probabilistic its algorithm proposed an individual customer's shifting probabilities...