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检索条件"任意字段=3rd Euro-NF Conference on Network Control and Optimization"

共 1643 条记录，以下是311-320 订阅

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Application of radial basis function neural network in optimization of process parameters of cigarette silk making 3

Application of radial basis function neural network in optim...

引用

3rd International conference on Artificial Intelligence, Virtual Reality, and Visualization, AIVRV 2023

作者： Cheng, Leiping Wu, Xiaoyan Xie, Peng Jiang, Shisheng Anhui Zhongyan Industry Co. Ltd. Wuhu Cigarette Factory Wuhu241003 China School of Mechanical Engineering Anhui Polytechnic University Wuhu241000 China

ISBN: (纸本)9781510671485

In view of the instability of the existing cigarette quality control level, there are still large fluctuations in the physical characteristics of tobacco, physical characteristics of tobacco and cigarette smoke quality control indicators. The radial basis function neural network (RBFNN) has the advantages of simple structure, fast convergence and overcoming the local minimum problem. The prediction model of RBFNN cigarette silk process quality control index was established, the parameters of cigarette silk process were optimized, and the optimized results were compared with the traditional orthogonal test results. The results show that the prediction model of RBFNN technology quality control index for cigarette silk production has high accuracy, while the traditional orthogonal test method has differences in parameter setting. Therefore, RBFNN is more accurate in predicting the optimal technological parameters of cigarette silk making and improves the production efficiency of cigarette silk making. © 2023 SPIE.

关键词： Forecasting

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Research of Multipath Routing Processes in Software Defined networks Based on Ant Colony optimization 11

Research of Multipath Routing Processes in Software Defined ...

引用

11th Mediterranean conference on Embedded Computing (MECO) / 3rd Summer School on Cyber-Physical + Systems and Internet of Things (CPS and IoT)

作者： Perepelkin, Dmitry Nguyen, Tin Ryazan State Radio Engn Univ Fac Comp Engn Ryazan Russia

ISBN: (纸本)9781665468282

Currently, the data in the network is increasing in both size and complexity, while network resources are limited, leading to network management becoming more difficult. Traditional network architectures are becoming increasingly unsuitable for the network requirements to respond to rapidly changing parameters of bandwidth, latency, security, etc. Software defined network (SDN) has become a new approach, changing the current network architecture to meet the needs of network resource management and traffic control. The purpose of the work is to study and analyze the multipath routing processes in the software defined network based on ant colony optimization. The simulation results show that the proposed algorithm is effectively used to find the shortest paths. The paths found can be used at the same time to transmit data, instead of just using a single path. From there, the performance of the network is improved, limiting congestion, reducing latency and packet loss.

关键词： software defined network multipath routing ant colony optimization

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Active Distribution network Day-Ahead Day-In Collaborative Dispatching Method Based on Optimal Economic Operation Area 3

Active Distribution Network Day-Ahead Day-In Collaborative D...

引用

3rd International conference on Intelligent Power and Systems, ICIPS 2023

作者： Zhang, Hui Wang, Jiye Zhao, Xiongwen Yuan, Xiaohui School of Electric and Electronic Engineering North China Electric Power University Beijing China Beijing Fibrlink Commnications Co. Ltd. State Grid Information & Telecommunication Group Co. Ltd. Beijing China State Grid Digital Technology Holding Co. Ltd. Beijing China

ISBN: (纸本)9798350328691

The conventional day-ahead and intraday coordinated scheduling typically employs minimizing the deviation from the day-ahead temporal planning curve as the intraday objective function. However, when there is a significant disparity between the intraday renewable energy output forecasts and the day-ahead plans, energy storage systems (ESS), and other controllable devices have limited room for intraday adjustments due to their time-coupled constraints. This limitation leads to reduced economic efficiency and flexibility. In response to this challenge, this paper introduces an Active Distribution network (ADN) day-ahead and intraday coordinated scheduling method based on the Optimal Economic Operation Region (OEOR). In the day-ahead stage, a linearized ADN scheduling model is developed. It leverages a large number of optimized curves for control devices under various random scenarios generated using Latin Hypercube Sampling. The objective is to maximize the number of optimized results within the boundaries of the control device output levels over the entire time span. The model also considers adjacent time constraints on energy storage state-of-charge and the ramp rate of micro gas turbines, thus establishing an OEOR generation model. In the intraday stage, control devices are continuously optimized within the OEOR. When the optimization value for a particular time period approaches the OEOR boundary, constraints on output from adjacent time periods are considered. This extends the OEOR to an Optimal Economic Extreme Operation Region (E-OEOR). The results of the case study indicate that the proposed method offers improved economic efficiency for the distribution network compared to traditional approaches. If you need further revisions or have additional content to translate, please let me know. ©2023 IEEE.

关键词： Energy storage

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Intelligent Trajectory Planning Algorithm for Unmanned Aerial Vehicles Based on Track Deception Against Radar networks 1

引用

3rd International conference on Autonomous Unmanned Systems, ICAUS 2023

作者： Lin, Wenbin Shi, Chenguang Wang, Ziwei Zhou, Jianjiang Ministry of Education Nanjing211106 China Beijing Institute of Control and Electronics Technology Beijing100045 China

ISBN: (数字)9789819710911

ISBN: (纸本)9789819710904

This paper investigates an intelligent trajectory planning algorithm for unmanned aerial vehicles (UAVs) that utilizes track deception techniques against radar networks. The main objective of the algorithm is to minimize the flight distance of UAVs while generating a coherent phantom track to deceive radar networks. Firstly, we analyze the geometric coupling relationship among the false target, the UAV, and the radar, deriving the motion control equations for UAV trajectory planning. Subsequently, we mathematically formulate the problem of intelligent trajectory planning for UAVs based on this coupling relationship. The optimization model aims to reduce the flight distance of the UAVs as much as possible, considering the strict dynamic constraints of UAV platforms. Furthermore, by leveraging the pre-designed phantom track and prior knowledge of radar network locations, we employ the particle swarm optimization (PSO) method to solve the resulting optimization problem. Finally, through simulation results, we validate the effectiveness and feasibility of the proposed algorithm. © Beijing HIWING Scientific and Technological Information Institute 2024.

关键词： Phantoms

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Bacterial Foraging optimization based Recurrent Neural network Approach ForIdentification and Classification of Maize Plant Disease 3

Bacterial Foraging Optimization based Recurrent Neural Netwo...

引用

3rd International conference on Intelligent Computing, Instrumentation and control Technologies, ICICICT 2022

作者： Jayapriya, P. Hemalatha, S. NallamuthuGoundarMahalingam College Department of Computer Science Pollachi India NallamuthuGoundarMahalingam College Department of Computer Applications Pollachi India

ISBN: (数字)9781665410052

ISBN: (纸本)9781665410052

Maize is one of the largest food crops after rice and wheat in all over the world. However it has become a vital part in the agriculture to automatically monitor and diagnosis the plant disease in new era. In this paper, a unique maize plant disease identification system has been modelled using the optimization of recurrent neural network through bacterial foraging technique. Further it can be employed to moderate the search space of the classifier and provides better initial information for recognition network. Initially pre-processing and region growing based segmentation has been approved to identify and determine the neighbour pixel of seed points toward combining it in particular region. It is to increase the efficiency of the network by searching and grouping of seed points having common attributes to generate the optimal features for classification. Obtained segmented region has been processed using Recurrent Neural network in order to capture sequential patterns based on longitudinal data to produce recurrent structures. Finally different classes of the plant disease have been classified and identified with new classic techniques. Experimental analysis using plant village dataset on the proposed model explains the performance measure in rudiments of dice coefficient, similarity and specificity towards disease identification. © 2022 IEEE.

关键词： Recurrent neural networks

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Research of Construction of Large-scale control networks Based on GXCORS and Data Processing Technologies 3

Research of Construction of Large-scale Control Networks Bas...

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3rd International conference on Geology, Mapping and Remote Sensing, ICGMRS 2022

作者： Zhou, Conglin Liao, Chaoming Shi, Bo Yao, Maohua Chen, Xiangping Yang, Yifei Natural Resources Information Center of Guangxi Zhuang Autonomous Region Nanning China Nanning Normal University School of Natual Resources and Surveying Nanning China

ISBN: (数字)9781665485951

ISBN: (纸本)9781665485951

Focusing on the national groundwater monitoring project (Guangxi) D-level control network construction project, a technical method for quick construction and data processing of large-scale control network based on GXCORS was expounded together with the study of technical optimization strategy and the analysis on the result precision of the control network. More precisely, the mean square error of the weakest side length of the baseline was greater than 1/105;and the comparison result of the plane coordinates of the check point was less than ±3cm, with elevation less than ±6cm. The findings proved that it is feasible to carry out quick construction and data processing of large-scale control networks taking advantage of GXCORS without considering jointly measuring the starting points of plane and elevation. In this way, high-precision plane coordinates and elevation value of the point to be measured can be acquired simultaneously from one GNSS observation, which could lead to a revolution in the traditional control measurement operation mode. © 2022 IEEE.

关键词： Mean square error

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Multi-time scale adaptive reactive power and voltage control of distribution network based on random forest algorithm 22

Multi-time scale adaptive reactive power and voltage control...

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3rd Asia-Pacific conference on Image Processing, Electronics and Computers, IPEC 2022

作者： Zhang, Zhang Shuai, Tang Yiliang, Sun State Grid Hebei Economic Research Institute Shijiazhuang050000 China

ISBN: (纸本)9781450395786

Aiming at the current situation of power quality in power grid, a multi-time scale adaptive reactive power and voltage control for distribution network based on random forest algorithm is proposed. In the low-voltage distribution network, three local independent voltage control modes are adopted for real-time reactive voltage control of photovoltaic inverters which do not have a communication network for the time being and cannot realize unified dispatching. In the coordinated control model of reactive power and voltage in multi-voltage distribution network, various reactive power sources including photovoltaic inverter with communication network are considered. In terms of local optimization control, establish indicators of collaborative power factor and dynamic optimization factor, take into account the global demand, and adjust the reactive power output of photovoltaic and equipment;In the aspect of centralized optimization control, the voltage out of limit risk or minimum network loss is selected according to the degree of reactive power adequacy to optimize reactive power: the effectiveness of the proposed strategy is verified by the simulation of an actual distribution network. In the long time scale, the day ahead optimal scheduling strategy aiming at the optimization of economy and security satisfaction is constructed;In a short time scale, the fixed slope of the traditional droop control is dynamically modified by the voltage danger coefficient to release the reactive power margin of the photovoltaic inverter. At the same time, the feedback correction link of long-time scale is added to the short-time scale optimization control. © 2022 ACM.

关键词： Reactive power

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Research on the optimal control method of regional road network based on dynamic vehicle distribution 3

Research on the optimal control method of regional road netw...

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3rd International conference on Computer Science and Communication Technology, ICCSCT 2022

作者： Shen, Hui Li, Kun Li, Chuan School of Electronics and Information Mianyang Polytechnic Sichuan Mianyang China

ISBN: (纸本)9781510661240

The traffic optimization control of the regional road network often involves two parts: the internal signal optimization control and the boundary flow control. This paper proposes some new methods for the traffic optimization of regional road network. First, the intersections inside the road network are divided to two types of groups by overlapping division method. Then the internal traffic flow characteristics for each type of group are analyzed to determine the vehicle distribution rate on the section. Based on the vehicle distribution rate, the vehicle capacity of the regional road network is calculated indirectly, providing reasonable threshold for boundary intersection flow control. According to previous research, a two-stage fuzzy control scheme is designed for the type-II central intersection, realizing the coordinated control between adjacent intersections and optimizing the operation of traffic flow in the regional road network effectively. Finally, the effectiveness and rationality of each method proposed in this paper are proved by simulation results. © 2022 SPIE.

关键词： Flow control

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A Concurrent Switching Model for Traffic Congestion control 3

A Concurrent Switching Model for Traffic Congestion Control

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3rd Modeling, Estimation and control conference (MECC)

作者： Rastgoftar, Hossein Liu, Xun Jeannin, Jean-Baptiste Univ Arizona Dept Aerosp & Mech Engn Tucson AZ 85721 USA Villanova Univ Dept Mech Engn Villanova PA 19085 USA Univ Michigan Dept Aerosp Engn Ann Arbor MI 48109 USA

ISBN: (纸本)9781713872344

We introduce a new conservation-based approach for traffic coordination modeling and control in a network of interconnected roads (NOIR) with switching movement phase rotations at every NOIR junction. For modeling of traffic evolution, we first assume that the movement phase rotation is cyclic at every NOIR junction, but the duration of each movement phase can be arbitrarily commanded by traffic signals. Then, we propose a novel concurrent switching dynamics (CSD) with deterministic transitions among a finite number of states, representing the NOIR movement phases. We define the CSD control as a cyclic receding horizon optimization problem with periodic quadratic cost and constraints. More specifically, the cost is defined so that the traffic density is minimized and the boundary inflow is uniformly distributed over the boundary inlet roads, whereas the cost parameters are periodically changed with time. The constraints are linear and imposed by a trapezoidal fundamental diagram at every NOIR road so that traffic feasibility is assured and traffic over-saturation is avoided. Copyright (c) 2023 The Authors. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0/)

关键词： Traffic congestion control model predictive control network dynamics

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Flexible Resource Space-time Layered optimization Scheduling Considering the Partition Characteristics of Active Distribution networks 3

Flexible Resource Space-time Layered Optimization Scheduling...

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2023 3rd International conference on Power System and Energy Internet, PoSEI 2023

作者： Luo, Busheng Lin, Zhichao Guo, Deru Cai, Weijun Zhang, Zuogang Zhou, Haohan Huizhou Power Supply Bureau Guangdong Power Grid Company Ltd. Guangdong Province Huizhou516000 China Beijing Kedong Electric Power Control System Company Limited Haidian District Beijing100089 China

Due to the layout differences between different areas of the distribution network, the electrical characteristics of each partition differ significantly. A flexible resource scheduling model considering distribution network functional zoning is proposed to address this issue. Firstly, electric vehicle charging congestion and willingness indices were proposed in different areas to guide electric vehicle charging, and corresponding controllable load models were established. A cross-regional charging model is proposed to guide users in charging, addressing the imbalance in the number and price of charging stations in each area. Then, a hierarchical scheduling model was developed based on the idea that renewable energy should be fully consumed in the upper layer to minimize the peak-to-valley disparity for the overall scheduling of flexible resources. They were scheduling controllable loads in each area in the lower layer and optimizing the charging positions of vehicles in each area. Finally, taking the IEEE33 node system as an example for simulation, the optimization effect of electric vehicles and controllable loads on the operation of the distribution network was analyzed. The results showed that the proposed method could leverage the resource characteristics of each partition, verifying the effectiveness of the proposed method. © Published under licence by IOP Publishing Ltd.

关键词： Electric loads

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