With the rapid advancement of large language models, academic topic identification and topic evolution analysis are crucial for enhancing AI’s understanding capabilities. Dynamic topic analysis provides a powerful ap...
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This paper addresses the integrated Earth observation satellite scheduling problem. It is a complicated problem because observing and downloading operations are both involved. We use an acyclic directed graph model to...
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This paper addresses the integrated Earth observation satellite scheduling problem. It is a complicated problem because observing and downloading operations are both involved. We use an acyclic directed graph model to describe the observing and downloading integrated scheduling *** on the model which considering energy constraints and storage capacity constraints, we develop an efficient solving method using a novel quantum genetic algorithm. We design a new encoding and decoding scheme that can generate feasible solution and increase the diversity of the *** results of the simulation experiments show that the proposed method solves the integrated Earth observation satellite scheduling problem with good performance and outperforms the genetic algorithm and greedy algorithm on all instances.
Monitoring the respiratory rate is crucial for helping us identify respiratory disorders. Devices for conventional respiratory monitoring are inconvenient and scarcely available. Recent research has demonstrated the a...
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The role of constraint energy-saving policy (ESP) playing in the coordinated development of energy conservation, emission reduction, and economic growth is of great significance to the country's sustainable progre...
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Accurate and comprehensive forecasting of streamflow plays an important role in the uncertainly analysis of the hydrologic system. It is widely accepted that prediction interval (PI) can provide more precise and detai...
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Accurate and comprehensive forecasting of streamflow plays an important role in the uncertainly analysis of the hydrologic system. It is widely accepted that prediction interval (PI) can provide more precise and detailed information than deterministic forecasting when the uncertainty level of streamflow increases. Support vector regression (SVR) is a supervised learning model for classification and regression analysis based on associated learning algorithms. In this paper, fuzzy information granulation (FIG) is combined with SVR model (FIG-SVR) for uncertainty forecasting of streamflow. On behalf of evaluating the performance of the forecasting results, the evaluation metrics of point forecasting and interval prediction results are introduced. The real streamflow data from the Three Gorges in the Yangtze River are used to validate the proposed method based on the proposed method. The results show that the proposed method provides the high-quality point predictand and PIs, and the uncertainly of streamflow can be well handled.
In order to improve the accuracy of photovoltaic power output prediction, a photovoltaic power prediction method based on similar days and improved artificial bee colony support vector machine is proposed. Firstly, th...
In order to improve the accuracy of photovoltaic power output prediction, a photovoltaic power prediction method based on similar days and improved artificial bee colony support vector machine is proposed. Firstly, through calculating the Euclidean distance of history day and measured day meteorological factors to determine similar days. Secondly, select historical data of photovoltaic power output, temperature, humidity and daily radiation on the slope of similar days and temperature, humidity and daily radiation on the slope of test date as input variables of support vector machine. And we adopt the improved artificial bees colony to optimize kernel function parameters and the penalty factor of support vector machine. Finally get the output in each period of photovoltaic power prediction. The experimental results showed that the proposed method can effectively improve the prediction accuracy of photovoltaic power.
In China, the installed cost of distributed photovoltaic (DPV) is declining rapidly. However, the level of subsidy per kWh for DPV is adjusted less frequently by the Chinese government. This paper proposed a linkage m...
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In China, the installed cost of distributed photovoltaic (DPV) is declining rapidly. However, the level of subsidy per kWh for DPV is adjusted less frequently by the Chinese government. This paper proposed a linkage model to forecast subsidy per kWh of DPV based on net present value (NPV) method. The results show that the increase of subsidy duration, internal consumption proportion and sunshine hours will reduce subsidy level. Therefore, it is suggested that the Chinese government should take varied and targeted measures, such as reducing different subsidies for new DPV users who install DPV in different years, choosing a longer subsidy duration and setting different subsidy levels in different regions. These varied and targeted measures are beneficial to both government and users, because they can reduce the annual financial burden for the government and the surcharges of electricity purchase for users.
This paper studies the problem of using multiple unmanned air vehicles (UAVs) to search for moving targets with sensing capabilities. When multiple UAVs (multi-UAV) search for a number of moving targets in the mission...
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This paper studies the problem of using multiple unmanned air vehicles (UAVs) to search for moving targets with sensing capabilities. When multiple UAVs (multi-UAV) search for a number of moving targets in the mission area, the targets can intermittently obtain the position information of the UAVs from sensing devices, and take appropriate actions to increase the distance between themselves and the UAVs. Aiming at this problem, an environment model is established using the search map, and the updating method of the search map is extended by considering the sensing capabilities of the moving targets. A multi-UAV search path planning optimization model based on the model predictive control (MPC) method is constructed, and a hybrid particle swarm optimization algorithm with a crossover operator is designed to solve the model. Simulation results show that the proposed method can effectively improve the cooperative search efficiency and can find more targets per unit time compared with the coverage search method and the random search method.
Because China’s long-term constant photovoltaic (PV) feed-in tariff policy has not been able to adapt to the decline in the cost of PV equipment, and too broad regional pricing will hinder the development of distribu...
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Because China’s long-term constant photovoltaic (PV) feed-in tariff policy has not been able to adapt to the decline in the cost of PV equipment, and too broad regional pricing will hinder the development of distributed photovoltaic generation (DPVG) to some extent. Therefore, this paper will re-evaluate China’s solar resource endowments into five regions, and based on the accounting cost method, combine the learning curve of PV equipment to accurately measure the dynamic unit generation cost of distributed PV. In addition, considering the reasonable returns to investors and tax factors, this study has obtained a dynamic feed-in tariff model for DPVG. A case study based on the model shows that the results of feed-in tariff is reasonable and effective, and the government should adjust the feed-in tariff more frequently according to the feed-in tariff pricing model in this study.
Understanding tissue motion in surgery is crucial to enable applications in downstream tasks such as segmentation, 3D reconstruction, virtual tissue landmarking, autonomous probe-based scanning, and subtask autonomy. ...
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