A5103132734- Multi-Criteria Decision Making
- Risk and Portfolio Optimization
- Fuzzy Systems and Optimization
- Metaheuristic Optimization Algorithms Research
- Evaluation Methods in Various Fields
- Advanced Algorithms and Applications
- Evaluation and Optimization Models
- Advanced Decision-Making Techniques
- Neural Networks and Applications
- Optimization and Mathematical Programming
- Stock Market Forecasting Methods
- Rough Sets and Fuzzy Logic
- Financial Distress and Bankruptcy Prediction
- Industrial Technology and Control Systems
- Mathematical and Theoretical Epidemiology and Ecology Models
- Safety and Risk Management
- Simulation and Modeling Applications
- Advanced Sensor and Control Systems
- Artificial Immune Systems Applications
- Distributed Control Multi-Agent Systems
- Enhanced Recovery After Surgery
- Extenics and Innovation Methods
- Advanced Measurement and Detection Methods
- Auction Theory and Applications
- Advanced Aircraft Design and Technologies
China Academy of Space Technology
2022-2025
Wuhan Botanical Garden
2022
South China University of Technology
2005-2021
China Academy of Chinese Medical Sciences
2021
Jinan University
2019
Shenzhen University
2012
The Third People's Hospital of Dalian City
2012
South University
2010
Southwest Hospital
2009
Nanning Normal University
2009
Focusing on a plunger type constant current output device designed for high sealing and long-life with complex multi-component coupling composition, assembly precision, many influencing factors other manufacturing problems, based the in-depth analysis of precision mechanism operational performance, surface quality structure, axial runout system structural dimensional accuracy are accurately controlled by error corresponding design; The decouples rotational screw to propose directional method...
The transjugular intrahepatic portosystemic shunt (TIPS) is technically divided into TIPS through the left branch of portal vein (TIPS-LBPV) and right (TIPS-RBPV). In order to compare their advantages disadvantages, this randomized, controlled trial was designed investigate outcomes in advanced cirrhotic patients.Seventy-two patients were randomly placed TIPS-LBPV (36 patients) TIPS-RBPV patients, with four failures) groups, they prospectively followed for 2 years after implantation.Patients...
Neural networks have been widely used to forecast indices and prices of stock market due the significant properties treating non-linear data with self-learning capability. However, neural suffer from difficulty deal qualitative information "black box" syndrome that more or less limited their applications in practice. To overcome drawbacks networks, this study we proposed a fuzzy network is class adaptive functionally equivalent inference system. The experiment results based on comprehensive...
In this paper, a new hybrid algorithm is introduced to improve the efficiency, accuracy and overcome drawbacks of weak ability perceive environment vulnerable perception local extreme in optimization process bacterial foraging (BFO) algorithm. algorithm, idea particle swarm (PSO) merged into chemotaxis algorithms elimination probability proposed elimination-dispersion according energy bacteria. order compare performance with BFO PSO, some typical high dimensional complex functions was test...
The effect of perioperative acupuncture on accelerating gastrointestinal function recovery has been reported in colorectal surgery and distal gastrectomy (Billroth-II). However, the evidence pancreatectomy other is still limited. A prospective, randomized controlled trial was conducted between May 2018 August 2019. Consecutive patients undergoing or our hospital were randomly assigned to electroacupuncture (EA) group control group. EA received transcutaneous Bai-hui (GV20), Nei-guan (PC6),...
Particle Swarm Optimization (PSO) algorithm and Fuzzy Neural Network (FNN) system has been widely used to solve complex decision making problems in practice. However, both of them more or less suffer from the slow convergence occasionally involve a local optimal solution. To overcome these drawbacks PSO FNN, this study modified particle swarm optimization (MPSO) is developed then combined with neural network optimize weight training process. Furthermore, new MPSO-FNN model applied financial...
To choose the appropriate value of inertia weight can improve performance PSO by means making a good balance between exploration and exploitation in search process. This paper presents novel variation method based on piecewise function, which there are two parts: one is nonlinear decreasing to enhance explorative ability; other linear just as standard algorithm. The key parameters proposed algorithm (PSO-PIW) identified through experimental simulations. results several benchmark functions...
The uncertainty of a financial market is traditionally dealt with probabilistic approaches. However, there are many non-probabilistic factors that affect the markets such return rate risky assets may be regarded as fuzzy number, which powerful tool used to describe an uncertain environment vagueness and ambiguity some type fuzziness. In this paper, conventional mean-variance model can simplified bi-objective linear programming based on possibility theory. Furthermore, two-stage algorithm...
Simple genetic algorithm (GA) involves only one initial population with fixed operational parameters selected in advance. This paper presents a modified (MGA) multiple subpopulations and dynamic parameters. In the new algorithm, operations are carried out on each subpopulation separately changed dynamically. meanwhile, information of individuals is transferred among all by means migration operator throughout evolution processes. Furthermore, has been applied to conditional value-at-risk...
Neural networks have been widely used to solve financial distress problems because of their excellent performances treating non-linear data with self-learning capability. However, the shortcoming NNs is also significant due "black box" syndrome. Moreover, in many situations more or less suffer from slow convergence and occasionally involve a local optimal solution, which strongly limited applications practice. To overcome NN's drawbacks, this paper presents hybrid system that merges three...
Compared with the conventional probabilistic mean-variance methodology, fuzzy number can better describe an uncertain environment vagueness and ambiguity. Based on this fact, possibilistic utilities to portfolio selection for bounded assets are discussed in paper. The mean value of expected return is termed measure investment variance risk. Moreover, we propose three kinds optimization models under assumption each investor’s utility type function: (I) a quadratic programming model upper...
Portfolio selection is an important issue for researchers and practitioners. Compared with the conventional probabilistic mean-variance method, fuzzy number can better describe uncertain environment vagueness ambiguity. In this paper, portfolio model transaction costs lending proposed by means of possibilistic mean variance under assumption that returns assets are numbers. Furthermore, a nonlinear bi-objective programming problem presented maximizing future expected return minimizing risk...
Neural networks (NNs) have been widely used to evaluate credit risk because of their excellent performances treating non-linear data with learning capability. However, the shortcoming neural is also significant due a "black box" syndrome and difficulty in dealing qualitative information, which limited its applications practice. To overcome these drawbacks NNs, this study we suggested an adaptive network-based fuzzy inference system (ANFIS), kind network models, on Chinese listed...
Equal weight portfolio is an effective way of dispersing investment risk on the research investment. The purpose this paper to present more accurate value ranges and some recent results variance return rate for equal investment, obtain sufficient necessary conditions being optimal These obtained in theory have a significant effect modern Finally, two numerical examples show effectiveness our results.