A5100385410- Stock Market Forecasting Methods
- Complex Systems and Time Series Analysis
- Time Series Analysis and Forecasting
- Occupational Health and Safety Research
- Blockchain Technology Applications and Security
- Financial Markets and Investment Strategies
- Fuzzy Logic and Control Systems
- Forecasting Techniques and Applications
- Banking stability, regulation, efficiency
- Mathematical Approximation and Integration
- Financial Risk and Volatility Modeling
- FinTech, Crowdfunding, Digital Finance
- Advanced Malware Detection Techniques
- Energy, Environment, Economic Growth
- Probabilistic and Robust Engineering Design
- Advanced Decision-Making Techniques
- Risk and Safety Analysis
- Fatigue and fracture mechanics
- Anomaly Detection Techniques and Applications
- Safety and Risk Management
- Neural Networks and Applications
- Market Dynamics and Volatility
Air Force Engineering University
2016-2024
South China University of Technology
2024
Fudan University
2024
Xihua University
2020
Hebei University of Science and Technology
2011-2013
Fuzzy sets theory cannot describe the data comprehensively, which has greatly limited objectivity of fuzzy time series in uncertain forecasting. In this regard, an intuitionistic forecasting model is built. new model, a clustering algorithm used to divide universe discourse into unequal intervals, and more objective technique for ascertaining membership function nonmembership set proposed. On these bases, forecast rules based on approximate reasoning are established. At last, contrast...
Fuzzy sets theory cannot describe the neutrality degree of data, which has largely limited objectivity fuzzy time series in uncertain data forecasting. With this regard, a multi-factor high-order intuitionistic forecasting model is built. In new model, clustering algorithm used to get unequal intervals, and more objective technique for ascertaining membership non-membership functions set proposed. On these bases, forecast rules based on multidimensional modus ponens inference are...
In existing fuzzy time series forecasting models, the accuracy of excessively relies on priori knowledge and output cannot effectively forecast multi values. The reduces drastically when data deviate from experience boundary in most models. generalisation performance is insufficient. To overcome defects traditional methods, this study proposed a long-term intuitionistic (IFTS) model based vector quantisation curve similarity measure. preprocessing model, FTS theory extended to IFTS scope,...
Abstract In this article, we first put forward a new definition of probabilistic Gel’fand- $(N,\delta )$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mo>(</mml:mo><mml:mi>N</mml:mi><mml:mo>,</mml:mo><mml:mi>δ</mml:mi><mml:mo>)</mml:mo></mml:math> -width which is the classical N in setting. Then estimate sharp order finite-dimensional space. Furthermore, obtain exact $(N, \delta univariate Sobolev space by discretization method according to result
This paper presents a novel approach to portfolio optimization in the field of finance, with specific focus on short-term yield. Existing literature has mainly utilized fundamental data predict long-term trends stock prices, but our proposed methodology utilizes technical indicators based theory chasing up. Furthermore, we address non-cooperative nature volume and price fluctuation introduce into selection scheme for first time. We propose an using parallel Data Envelopment Analysis (DEA)...
In the stock exchange, trade duration reflect important information about market exchange. So it has great effects on bargainer's behaviors and liquidity of For testing infection in paper chooses two stocks Shanghai Stock Exchange to study their with ACD model based MCMC, discusses characteristics related duration, checks extent between China Market. The research shows that match well Exchange.
This paper analysed the generating mechanism of university sudden mass incidents based on danger theory, and quantified key points in process, such as risk points, zone, especially determined point by ACD model, which was used ultra-high-frequency financial time series analysis, then proposed early warning model implementation steps. In end, it feasibility effectiveness an example.