Correlation knowledge extraction based on data mining for distribution network planning

Traditional distribution network planning relies on the professional knowledge of planners,especially when analyzing the correlations between the problems existing in the network and the crucial influencing factors.The inherent laws reflected by the historical data of the distribution network are ignored,which affects the objectivity of the planning scheme.In this study,to improve the efficiency and accuracy of distribution network planning,the characteristics of distribution network data were extracted using a data-mining technique,and correlation knowledge of existing problems in the network was obtained.A data-mining model based on correlation rules was established.The inputs of the model were the electrical characteristic indices screened using the gray correlation method.The Apriori algorithm was used to extract correlation knowledge from the operational data of the distribution network and obtain strong correlation rules.Degree of promotion and chi-square tests were used to verify the rationality of the strong correlation rules of the model output.In this study,the correlation relationship between heavy load or overload problems of distribution network feeders in different regions and related characteristic indices was determined,and the confidence of the correlation rules was obtained.These results can provide an effective basis for the formulation of a distribution network planning scheme.

Technical Research on Characteristics and Network Planning of Railway 5G-R Network

The railway 5G-R network is ready for the engineering construction.In order to provide technical reserve for the preliminary engineering stage,it is necessary to study the characteristics of 5G-R network and network planning technology in advance.The 5G-R network,different from the operators'5G network,is mainly available for railway staff and covers the railway line.It is upgraded based on the previous generation of railway communication system-GSM-R technology.By comprehensively summarizing and reviewing the characteristics of 5G-R system architecture,network coverage,networking technology,business characteristics,equipment redundancy,network performance,etc.,we study the network planning technology with 5G-R characteristics based on the above characteristics,including frequency,coverage,capacity,parameters,indoor distribution,switching and other key technologies.On this basis,this paper puts forward 5G-R network planning suggestion,which can provide technical support for subsequent project deployment.

Analysis of effect factors-based stochastic network planning model

Looking at all the indeterminate factors as a whole and regarding activity durations as independent random variables, the traditional stochastic network planning models ignore the inevitable relationship and dependence among activity durations when more than one activity is possibly affected by the same indeterminate factors. On this basis of analysis of indeterminate effect factors of durations, the effect factors-based stochastic network planning （EFBSNP） model is proposed, which emphasizes on the effects of not only logistic and organizational relationships, but also the dependent relationships, due to indeterminate factors among activity durations on the project period. By virtue of indeterminate factor analysis the model extracts and describes the quantitatively indeterminate effect factors, and then takes into account the indeterminate factors effect schedule by using the Monte Carlo simulation technique. The method is flexible enough to deal with effect factors and is coincident with practice. A software has been developed to simplify the model-based calculation, in VisualStudio.NET language. Finally, a case study is included to demonstrate the applicability of the proposed model and comparison is made with some advantages over the existing models.

Application and Realization of Hierarchical Network Planning Based on Web

Making use of Microsoft Visual Studio. NET platform, hierarchical network planning is realized in working procedure time-optimization of the construction by TBM, and hierarchical network graph of the construction by TBM is drawn based on browser. Then the theory of system realization is discussed, six components of system that can be reused are explained emphatically. The realization of hierarchical network panning in Internet provides available guarantee for controlling rate of progress in large-scale or middle-sized projects. Key words Web - network graph - hierarchical network planning CLC number TU721 Biography: WU Shi-jing (1963-), male, Professor, research direction: equipments management engineering, mechatronics, state monitoring and malfunction diagnostics of machine and electronics equipments.

Real-time UAV path planning based on LSTM network

To address the shortcomings of single-step decision making in the existing deep reinforcement learning based unmanned aerial vehicle(UAV)real-time path planning problem,a real-time UAV path planning algorithm based on long shortterm memory(RPP-LSTM)network is proposed,which combines the memory characteristics of recurrent neural network(RNN)and the deep reinforcement learning algorithm.LSTM networks are used in this algorithm as Q-value networks for the deep Q network(DQN)algorithm,which makes the decision of the Q-value network has some memory.Thanks to LSTM network,the Q-value network can use the previous environmental information and action information which effectively avoids the problem of single-step decision considering only the current environment.Besides,the algorithm proposes a hierarchical reward and punishment function for the specific problem of UAV real-time path planning,so that the UAV can more reasonably perform path planning.Simulation verification shows that compared with the traditional feed-forward neural network(FNN)based UAV autonomous path planning algorithm,the RPP-LSTM proposed in this paper can adapt to more complex environments and has significantly improved robustness and accuracy when performing UAV real-time path planning.

Planning and construction of Xiong’an New Area(city of over 5 million people):Contributions of China’s geologists and urban geology

China established Xiong’an New Area in Hebei Province in 2017,which is planned to accommodate about 5 million people,aiming to relieve Beijing City of the functions non-essential to its role as China’s capital and to expedite the coordinated development of the Beijing-Tianjin-Hebei region.From 2017 to 2021,the China Geological Survey(CGS)took the lead in multi-factor urban geological surveys involving space,resources,environments,and disasters according to the general requirements of“global vision,international standards,distinctive Chinese features,and future-oriented goals”in Xiong’an New Area,identifying the engineering geologic conditions and geologic environmental challenges of this area.The achievements also include a 3D engineering geological structure model for the whole area,along with“one city proper and five clusters”,insights into the ecology and the background endowment of natural resources like land,geothermal resources,groundwater,and wetland of the area before engineering construction,a comprehensive monitoring network of resources and environments in the area,and the“Transparent Xiong’an”geological information platform that is open,shared,dynamically updated,and three-dimensionally visualized.China’s geologists and urban geology have played a significant role in the urban planning and construction of Xiong’an New Area,providing whole-process geological solutions for urban planning,construction,operation and management.The future urban construction of Xiong’an New Area will necessitate the theoretical and technical support of earth system science(ESS)from various aspects,and the purpose is to enhance the resilience of the new type of city and to provide support for the green,low-carbon,and sustainable development of this area.

Two-Stage Planning of Distributed Power Supply and Energy Storage Capacity Considering Hierarchical Partition Control of Distribution Network with Source-Load-Storage

Aiming at the consumption problems caused by the high proportion of renewable energy being connected to the distribution network,it also aims to improve the power supply reliability of the power system and reduce the operating costs of the power system.This paper proposes a two-stage planning method for distributed generation and energy storage systems that considers the hierarchical partitioning of source-storage-load.Firstly,an electrical distance structural index that comprehensively considers active power output and reactive power output is proposed to divide the distributed generation voltage regulation domain and determine the access location and number of distributed power sources.Secondly,a two-stage planning is carried out based on the zoning results.In the phase 1 distribution network-zoning optimization layer,the network loss is minimized so that the node voltage in the area does not exceed the limit,and the distributed generation configuration results are initially determined;in phase 2,the partition-node optimization layer is planned with the goal of economic optimization,and the distance-based improved ant lion algorithm is used to solve the problem to obtain the optimal distributed generation and energy storage systemconfiguration.Finally,the IEEE33 node systemwas used for simulation.The results showed that the voltage quality was significantly improved after optimization,and the overall revenue increased by about 20.6%,verifying the effectiveness of the two-stage planning.

Optimizing Rank of Landscape Planning Works of Urban Wetland Park

Classifying and ranking the huge amounts of landscape planning works of urban wetland park is always difficult due to the multi-functions （ecological, leisure, educational and disaster prevention） of the urban wetland park. Therefore, an optimizing rank system is urgently needed. Analytic Hierarchy Process （AHP） and Technique for Order Preference by Similarity to Ideal Solution （TOPSIS） models were used to rank the planning works of 30 urban wetland park based on four mainly factors, which included landscape ecological planning, landscape planning, ecological planning and economic planning. The study indicated that the AHP- TOPSIS model had good discrimination in the classification and ranking of landscape planning works of urban wetland park and it was also applicable to the planning works of other urban greenbelts.

Radio Network Planning and Optimization for 5G Telecommunication System Based on Physical Constraints

The paper mainly focuses on the network planning and optimization problem in the 5G telecommunication system based on the numerical investigation.There have been two portions of this work,such as network planning for efficient network models and optimization of power allocation in the 5G network.The radio network planning process has been completed based on a specific area.The data rate requirement can be solved by allowing the densification of the system by deploying small cells.The radio network planning scheme is the indispensable platform in arranging a wireless network that encounters convinced coverage method,capacity,and Quality of Service necessities.In this study,the eighty micro base stations and two-hundred mobile stations are deployed in the-15km×15km wide selected area in the Yangon downtown area.The optimization processes were also analyzed based on the source and destination nodes in the 5G network.The base stations’location is minimized and optimized in a selected geographical area with the linear programming technique and analyzed in this study.

Exploration on MOOC Teaching Pilot College Construction Planning

The spread and innovative application of MOOC in China has rapidly triggered a profound revolution in the curriculum construction and teaching reform of universities,promoting significant results in teaching and talent cultivation.Based on the practice of“MOOC teaching pilot colleges”carried out by the China University Computer Education MOOC Consortium in some universities in China,this paper proposes the overall plan of MOOC teaching pilot colleges construction through the analysis of typical cases,pointing out the purpose and significance of the reform of the pilot college and giving the relevant concepts and requirements.This thesis focuses on the reform of teaching methods,assessment methods,grade calculation and credit recognition,and stress assessment,emphasizing the need for a three-dimensional process management of teachers,students,and college teaching administrators,and the need to focus on institutional development to provide protection.MOOC teaching pilot colleges should reform and innovate in practice,and they should keep solving the problems they encounter and deepen the reform,so as to provide useful experiences and reference practices for the landing and high-quality development of MOOC teaching in more universities.

A hybrid particle swarm optimization approach with neural network and set pair analysis for transmission network planning

Transmission network planning (TNP) is a large-scale, complex, with more non-linear discrete variables and the multi-objective constrained optimization problem. In the optimization process, the line investment, network reliability and the network loss are the main objective of transmission network planning. Combined with set pair analysis (SPA), particle swarm optimization (PSO), neural network (NN), a hybrid particle swarm optimization model was established with neural network and set pair analysis for transmission network planning (HPNS). Firstly, the contact degree of set pair analysis was introduced, the traditional goal set was converted into the collection of the three indicators including the identity degree, difference agree and contrary degree. On this bases, using shi(H), the three objective optimization problem was converted into single objective optimization problem. Secondly, using the fast and efficient search capabilities of PSO, the transmission network planning model based on set pair analysis was optimized. In the process of optimization, by improving the BP neural network constantly training so that the value of the fitness function of PSO becomes smaller in order to obtain the optimization program fitting the three objectives better. Finally, compared HPNS with PSO algorithm and the classic genetic algorithm, HPNS increased about 23% efficiency than THA, raised about 3.7% than PSO and improved about 2.96% than GA.

Thoughts and Strategies of Sponge City Construction Planning: A Case Study of Pingxiang, Jiangxi Province

At present and for a long time in the future, urbanization in China will maintain a rapid development speed. After the rainstorm, the phenomenon of “sea views” is common. The direct reason is that the urban drainage system and the ground drainage system cannot afford the large flow of water in a short period of time, but the most fundamental reason is that the artificial construction environment changes the water storage and drainage function of the ground under the natural state. “Sponge city construction” came into being. This paper mainly analyzes and studies the sponge city construction in Pingxiang City, Jiangxi Province, and uses the method of field investigation and literature data to clarify the ideas of the sponge city construction in Pingxiang City and summarize the successful experience, which can provide a reference for the subsequent “sponge city development” ideas.

Optimal search path planning of UUV in battlefeld ambush scene

Aiming at the practical application of Unmanned Underwater Vehicle(UUV)in underwater combat,this paper proposes a battlefield ambush scene with UUV considering ocean current.Firstly,by establishing these mathematical models of ocean current environment,target movement,and sonar detection,the probability calculation methods of single UUV searching target and multiple UUV cooperatively searching target are given respectively.Then,based on the Hybrid Quantum-behaved Particle Swarm Optimization(HQPSO)algorithm,the path with the highest target search probability is found.Finally,through simulation calculations,the influence of different UUV parameters and target parameters on the target search probability is analyzed,and the minimum number of UUVs that need to be deployed to complete the ambush task is demonstrated,and the optimal search path scheme is obtained.The method proposed in this paper provides a theoretical basis for the practical application of UUV in the future combat.

Efficient Route Planning for Real-Time Demand-Responsive Transit

Demand Responsive Transit (DRT) responds to the dynamic users’ requests without any fixed routes and timetablesand determines the stop and the start according to the demands. This study explores the optimization of dynamicvehicle scheduling and real-time route planning in urban public transportation systems, with a focus on busservices. It addresses the limitations of current shared mobility routing algorithms, which are primarily designedfor simpler, single origin/destination scenarios, and do not meet the complex demands of bus transit systems. Theresearch introduces an route planning algorithm designed to dynamically accommodate passenger travel needsand enable real-time route modifications. Unlike traditional methods, this algorithm leverages a queue-based,multi-objective heuristic A∗ approach, offering a solution to the inflexibility and limited coverage of suburbanbus routes. Also, this study conducts a comparative analysis of the proposed algorithm with solutions based onGenetic Algorithm (GA) and Ant Colony Optimization Algorithm (ACO), focusing on calculation time, routelength, passenger waiting time, boarding time, and detour rate. The findings demonstrate that the proposedalgorithmsignificantly enhances route planning speed, achieving an 80–100-fold increase in efficiency over existingmodels, thereby supporting the real-time demands of Demand-Responsive Transportation (DRT) systems. Thestudy concludes that this algorithm not only optimizes route planning in bus transit but also presents a scalablesolution for improving urban mobility.

Application of Interval Algorithm in Rural Power Network Planning

Rural power network planning is a complicated nonlinear optimized combination problem which based on load forecasting results, and its actual load is affected by many uncertain factors, which influenced optimization results of rural power network planning. To solve the problems, the interval algorithm was used to modify the initial search method of uncertainty load mathematics model in rural network planning. Meanwhile, the genetic/tabu search combination algorithm was adopted to optimize the initialized network. The sample analysis results showed that compared with the certainty planning, the improved method was suitable for urban medium-voltage distribution network planning with consideration of uncertainty load and the planning results conformed to the reality.

Modeling Simulation Technology Research for Distribution Network Planning

This paper proposes to use the power system simulation software CYME to plan, model and simulate for an actual distribution network for improving the reliability and efficiency, enhancing the efficiency and capacity, simulating the abnormal condition of distribution network, and presenting operation program of safe, reliable and having simulation record statements. The modeling simulation results show that the software module has lots of advantages including high accuracy, ideal reliability, powerful practicality in simulation and analysis of distribution network, it only need to create once model, the model can sufficiently satisfy multifarious types of simulation analysis required for the distribution network planning.

Compromise in CDMA Network Planning

CDMA network planning, for example in 3G UMTS networks, is an important task whether for upgrading existing networks or planning new networks. It is a time consuming, computationally hard, task and generally requires the consideration of both downlink and uplink requirements. Simulation experiments presented here suggest that if time is a major consideration in the planning process then as a compromise only uplink needs to be considered.

Optimization of UMTS Network Planning Using Genetic Algorithms

The continuously growing of cellular networks complexity, which followed the introduction of UMTS technology, has reduced the usefulness of traditional design tools, making them quite unworthy. The purpose of this paper is to illustrate a design tool for UMTS optimized net planning based on genetic algorithms. In particular, some utilities for 3G net designers, useful to respect important aspects (such as the environmental one) of the cellular network, are shown.

Research on Distribution Network Automation and Distribution Network Planning Mode

Based on the research of distribution network automation and distribution network planning mode, the analysis of the significance of urban distribution network automation must be performed at the first place. Combined with the problems existing in China’s current distribution network, it is concluded that, establish effective hardware support system, data sharing and feeder automation to ensure automation safety;strengthen power distribution and power line material testing to improve distribution automation system and distribution network planning;research methods of improving the professional skills and comprehensive quality of professionals.