A5101764350- Scheduling and Optimization Algorithms
- Target Tracking and Data Fusion in Sensor Networks
- Advanced Control Systems Optimization
- Advanced Manufacturing and Logistics Optimization
- Advanced Measurement and Detection Methods
- Military Defense Systems Analysis
- Optimization and Search Problems
- Radar Systems and Signal Processing
- Infrared Target Detection Methodologies
- Distributed Sensor Networks and Detection Algorithms
- Assembly Line Balancing Optimization
- Fault Detection and Control Systems
- Control Systems and Identification
- Robotics and Sensor-Based Localization
- Remote Sensing and LiDAR Applications
- Neural Networks and Applications
- Advanced Technologies in Various Fields
- Digital Filter Design and Implementation
- Microwave Imaging and Scattering Analysis
- Neural Networks Stability and Synchronization
- Vehicle Routing Optimization Methods
- Advanced Optical Sensing Technologies
- Inertial Sensor and Navigation
- UAV Applications and Optimization
- Color perception and design
First People's Hospital of Yunnan Province
2024
Kunming University of Science and Technology
2024
Tianjin Nankai Hospital
2023
Hangzhou Dianzi University
2009-2020
Heilongjiang Bayi Agricultural University
2011
Shanghai Jiao Tong University
2007-2008
Lidar has received a lot of attention due to its precise ranging accuracy. Ground points filtering is an important task in point clouds processing. It's challenge model the ground surface and filter accurately case complex undulations, occlusions, sparse clouds. A novel modeling method based on hybrid regression technique proposed this paper. The integrates Gaussian process (GPR) robust locally weighted (RLWR) by dividing that are projected polar grid map into radial circumferential...
A modified bottleneck-based (MB) heuristic for large-scale job-shop scheduling problems with a well-defined bottleneck is suggested, which simpler but more tailored than the shifting (SB) procedure. In this algorithm, first scheduled optimally while non-bottleneck machines are subordinated around solutions of schedule by some effective dispatching rules. Computational results indicate that MB can achieve better tradeoff between solution quality and computational time compared to SB procedure...
Persistent surveillance systems using manned or unmanned aerial vehicles play a crucial role in modern intelligence, surveillance, and reconnaissance missions. One of the aspects that determine quality these is path planning. Path planning often attempts to optimize one two objective metrics, such as coverage area, cost, time, while meeting several constraints would challenge missions, weather, downtime, amount information gathered. A number approaches have been proposed literature address...
In this paper, a new model predictive control framework is proposed for positive systems subject to input/state constraints and interval/polytopic uncertainty. Instead of traditional quadratic performance index, simple linear Lyapunov function, cone invariant set with form computation tool are first adopted. Then, law that can handle the robustly stabilise proposed. The advantages lie in following facts: (1) an equivalent problem formulated be easily solved than other problems including...
Vehicle pose estimation plays an significant role in vehicle tracking which is important part autonomous driving. In this paper, a new method based on Edge Distance proposed. The defined to describe the distribution of point clouds with respect their bounding rectangles. Based Distance, rectangle utilized fit outline. For case where are sparse or only one edge visible, modified according preset size. obtained rectangle. Experiments KITTI data sets show that proposed can obtain better...
Long‐time coherent integration is an effective method to implement low‐observable target detection in a complex scenario. Radon‐fractional Fourier transform (RFRFT) can compensate the range and Doppler migration simultaneously obviously improve signal‐to‐clutter‐noise ratio (SCNR) via long‐time integration. However, RFRFT uses combination of moving parameters, i.e. initial range, velocity acceleration, search targets, increasing computational burden. In this study, novel two‐stage proposed...
To enhance the accuracy of medical document classification, we propose an advanced deep fusion model for sorting medicine document. Specifically, text representation using bidirectional encoder from transformers (BERT). BERT is a that considers context information in input sequences. This capability particularly valuable document, as often requires understanding global context, such diagnoses, history, and treatment plans. Furthermore, can learn semantics words phrases, comprehending...
This paper focuses on a job-shop scheduling problem with multiple constraint machines (JSPMC). A method for the JSPMC is proposed. It divides in shop into and non-constraint based new identification method, formulates reduced only while replacing operations of time lags. The are scheduled explicitly by solving an efficient heuristic, earliest operation due date (EODD) dispatching rule. Extensive computational results indicate that proposed algorithm can obtain better trade-off between...
An optimal sensor assignment method based on time-varying measurement variance for tracking multi-targets is presented. It gets the by converted measuring coordinates and estimates covariance with Kalman filtering algorithm. The problem maximizing information gain developed. Then an improved Hungarian algorithm proposed to allocate resources optimally. Finally, simulation results show that can meet accuracy requirements.
The group delay of a linear-phase FIR filter is about half its length. Existing methods for low group-delay design usually result in large error, noticeably towards the band edges. Recently, Lai [2] presented constrained least-squares method that can specify both magnitude-error and phase-error upper bounds. Reduced error be obtained by using sigmoid upper-bound function method. In this paper, we improve modified complex approximation such more flexibly magnitude phase errors, smaller under...
In order to improve the comprehensive defense capability of netted radar system while tracking multi-targets cooperatively, a more reasonable evaluation indicator is required evaluate overall performance system. The new indicators for deployment and allocation in management are proposed quantitatively this paper. As they consist coverage ratio, accuracy anti-jamming capability, can ensure possesses an outstanding through management. Simulations show that arrangement result when applied...
This paper proposes a new approach for the multi-sensor management with multi-target. To meet need of engineering practice, we transform problem into two consecutive optimization processes different objectives. First objective is maximum number tracking-target obtained by assigning one sensor to each target, while second matching sensor-target target at least. Both optimizations are under constraints radar's energy and duty ratio in planning horizon can be solved linear programming method....
This paper addresses the sensor resource scheduling problem that allocating radar resources to track targets under time and energy constrains in multi-radar system. The objective is maximize number of which can be tracked improve utilization resources. optimal with tracking matching developed. We then proposed a decomposition-based procedure solve problem. It decomposes bi-objective into two sub-problems solves optimally implicit enumeration method. simulation results show method improves...
Data association is one of the key and difficult problems for multisensor-multitarget tracking. The classic multidimensional assignment algorithm often uses Lagrange relaxation to solve problem with angle only data obtained by passive sensors in presence clutter, false alarm condition. sub gradient applied update multipliers, but it needs minimize all at every iterative time dual solution algorithm. This leads long compute bad real-time performance. Aimed problem, an improved based on...