A5101982657- Fault Detection and Control Systems
- Stability and Control of Uncertain Systems
- Neural Networks Stability and Synchronization
- Mineral Processing and Grinding
- Software Engineering Research
- Polymer-Based Agricultural Enhancements
- Distributed Sensor Networks and Detection Algorithms
- Spectroscopy and Chemometric Analyses
- Distributed Control Multi-Agent Systems
- Advanced Algorithms and Applications
- Control Systems and Identification
- Open Source Software Innovations
- Plant Growth Enhancement Techniques
- Forecasting Techniques and Applications
- Place Attachment and Urban Studies
- Engineering Technology and Methodologies
- Complex Network Analysis Techniques
- Spatial and Panel Data Analysis
- Urban Green Space and Health
- Face and Expression Recognition
- Plant responses to water stress
- Advanced Machining and Optimization Techniques
- Domain Adaptation and Few-Shot Learning
- Machine Learning and Data Classification
- Stock Market Forecasting Methods
Lanzhou Institute of Husbandry and Pharmaceutical Sciences
2024
Chinese Academy of Agricultural Sciences
2024
Ministry of Agriculture and Rural Affairs
2024
Zhejiang University
2017
China Waterborne Transport Research Institute
2014-2016
Nanjing University of Finance and Economics
2016
Harbin Institute of Technology
2013-2015
Tianjin University
2015
Heilongjiang Institute of Technology
2014-2015
University of California, Santa Barbara
2015
This paper considers the problem of reset quantized state control for a class continuous-time linear system. The logarithmic quantization scheme is employed in network-based information communication, and observer introduced which based on standard one to suppress sensor effects. A Bernoulli processing approach presented value with random way domain. resulting error system hybrid contains both discrete-time stochastic dynamics. By Lyapunov method, it derived that under proposed technique...
In the era of big data, many urgent issues to tackle in all walks life can be solved via data technique. Compared with Internet, economy, industry, and aerospace fields, application area architecture is relatively few. this paper, on basis actual values Boston suburb houses are forecast by several machine learning methods. According predictions, government developers make decisions about whether developing real estate corresponding regions or not. support vector (SVM), least squares (LSSVM),...
For the complex industrial process, it has become increasingly challenging to effectively diagnose complicated faults. In this paper, a combined measure of original Support Vector Machine (SVM) and Principal Component Analysis (PCA) is provided carry out fault classification, compare its result with what based on SVM-RFE (Recursive Feature Elimination) method. RFE used for feature extraction, PCA utilized project data onto lower dimensional space. PCA<mml:math...
Abstract For obtaining maps of good precision by the spatial inference method, distribution sampling sites in geographical and feature space is very important. a regional variable with trends, predicting error comes from trend estimation, variogram estimation interpolation. Based on cLHS (conditioned Latin hypercube Sampling) method called scLHS (spatial cLHS) considering all these three aspects help ancillary data proposed this article. Its advantage lies simultaneously improving MODIS...
With the rapid development in science and technology, data acquisition, storage mining technology are widely applied to various fields. All aspects of people's lives recorded as data. Through analyzing arranging data, people can get a lot valuable information. In this paper, support vector machine (SVM), least squares (LSSVM) partial (PLS) respectively used field economic research. Real-time monitoring forecasting for stock index is vital market. The changing trend stocks predicted according...
The problem of state estimation is investigated for complex network systems with quantization and event-triggered communication scheme. A method introduced to quantize the output signal, which can reduce burden data transmission; An scheme cited, useful transmission channel. main purpose this paper analyze design a reliable estimator. Firstly, using determine whether newly sampled signal will be sent out. Secondly, signals transmitted estimator by quantizer. Lyapunov functional approach...
Open source software systems are becoming increasingly important these days and will grow stronger in the future. In order to gain more information about them, their structure characteristics behavior need be measured. This paper tests scale free on open real-world empirically. More specially, this checks whether Chidamber Kemerer metrics suite follows power law or not through three versions of Weka. Our empirical results showed that features complex networks didn’t exist
Informal learning is an essential part of students' active in higher education.They are sustainable development's representations to create favorable informal space and energize students colleges, which great significance education.At present, colleges' planning designs focus more on landscapes architectural forms instead superior places.This paper analyzes the correlation between spatial configuration network interactions, basis provides layout strategies, putting into use with empirical study.
Behavior research is limited by the accessibility of microscopic behavior data. In this study, a PEO (Person-Environment-Object) model proposed to decompose diverse in real world into simple and measurable variables such as position, status, time, etc., which serves foundation for behavioral data collection. According model, then framework acquisition program established based on wireless sensor technology, order provide high spatial temporal resolution deep its applications.
Transfer learning is an important research topic in machine and data mining that focuses on utilizing knowledge skills learned previous tasks to a novel but related task. This paper contributes comparison between boosting for transfer boosting. The results, terms of the accuracy, weighted F-Measure, G-Mean, GMPR, precision AUC, are rigorously tested using statistical framework proposed by Janez Demsar. Results show performance difference TrAdaBoost AdaBoost less significant.
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