A5053726480- Metaheuristic Optimization Algorithms Research
- Advanced Multi-Objective Optimization Algorithms
- Satellite Communication Systems
- Evolutionary Algorithms and Applications
- Optimization and Search Problems
- Vehicle Routing Optimization Methods
- Spacecraft Design and Technology
- Optimal Experimental Design Methods
- Heat Transfer and Optimization
- Reinforcement Learning in Robotics
- High Altitude and Hypoxia
- RNA modifications and cancer
- Image Processing Techniques and Applications
- Industrial Technology and Control Systems
- Advanced Graph Neural Networks
- Heavy Metal Exposure and Toxicity
- Scheduling and Optimization Algorithms
- Advanced Sensor and Control Systems
- Mercury impact and mitigation studies
- Circular RNAs in diseases
- Adaptive Dynamic Programming Control
- MicroRNA in disease regulation
- Physiological and biochemical adaptations
- Energy Harvesting in Wireless Networks
- Advanced Manufacturing and Logistics Optimization
Xiangtan University
2018-2024
National University of Defense Technology
2020-2024
Wenzhou University
2020-2022
Central South University of Forestry and Technology
2019
Central South University
2019
Shenzhen Institute of Information Technology
2019
The First Affiliated Hospital, Sun Yat-sen University
2014
Sun Yat-sen University
2014
Multitype satellite observation, including optical observation satellites, synthetic aperture radar (SAR) and electromagnetic has become an important direction in integrated applications due to its ability cope with various complex situations. In the multitype scheduling problem (MTSOSP), constraints involved different types of satellites make challenging. This article proposes a mixed-integer programming model generalized profit representation method effectively situation multiple...
Esophageal squamous cell carcinoma (ESCC) is the major histological type of esophageal cancer in developing countries. The prognosis and survival rate ESCC are very poor. Recently, microRNAs (miRNAs) have emerged as important regulators biological processes. To better understanding molecular mechanisms by which they regulate behavior cells needed. expression miR-208 was examined lines tumor tissues real-time PCR. Proliferation capability upon regulation detected MTT assay, colony formation...
Earth electromagnetic exploration satellites are widely used in many fields due to their wide detection range and high sensitivity. The complex environment the proliferating number of make management a primary issue. In this article, learning adaptive genetic algorithm (LAGA) is proposed for satellite scheduling problem (EESSP). Control parameters essential successful performance evolutionary algorithms, sensitivity makes tuning very time-consuming. LAGA, gated recurrent unit (GRU) neural...
Earth observation satellites (EOSs) are taking a large number of pictures with increasing resolution which produce massive image data. Satellite data transmission becomes the bottleneck part in process EOS resource management. In this paper, we study earth satellite integrated scheduling problem (EOSIS) where imaging activities and download considered integratively. We propose an integer linear programming model to formulate problem. Due NP-hardness problem, efficient local search heuristic...
Effectively balancing the convergence and diversity in dynamic environments is a challenging task. In order to handle issue, this paper proposes novel prediction strategy based on change degree of decision variables for multi-objective optimization (CDDV), which has ability detect space design different make population adapt new environment. The proposed method can adaptively increase according analysis degree, when an environmental detected. study efficacy usefulness evolutionary...
Dynamic multi-objective optimization problems (DMOPs) provide a challenge in that objectives conflict each other and change over time. In this paper, hybrid approach based on prediction autonomous guidance is proposed, which responds the environmental changes by generating new population. According to position of historical population, part population generated predicting roughly quickly. addition, another guidance. A sub-population from current evolves several generations independently,...
In recent years, many distinguished dynamic multiobjective optimization evolutionary algorithms (DMOEAs) have been derived based on prediction strategies. Prediction-based strategies shown their superiority in tracking the new POS/POF. However, prediction-based will be poor if distribution of Pareto optimal solutions has drastic changes with environmental changes.Therefore, we propose a hybrid multi-scale perturbation and regional search (PPRS) to solve DMOPs. The strategy contains two...